Browse Topic: Battery management systems (BMS)

Items (345)
This SAE Information Report describes common practices for design of battery systems for vehicles that utilize a rechargeable battery to provide or recover all or some traction energy for an electric drive system. It includes product description, physical requirements, electrical requirements, environmental requirements, safety requirements, storage and shipment characteristics, and labeling requirements. It also covers termination, retention, venting system, thermal management, and other features. This document does describe guidelines in proper packaging of the battery to meet the crash performance criteria detailed in SAE J1766. Also described are the normal and abnormal conditions that may be encountered in operation of a battery pack system
Battery Standards Testing Committee
This SAE Information Report contains definitions for HEV, PHEV, and EV terminology. It is intended that this document be a resource for those writing other HEV, PHEV, and EV documents, specifications, standards, or recommended practices.
Hybrid - EV Committee
This SAE Recommended Practice (RP) aids in the identification, handling, and shipping of lithium batteries to and from specified locations. It is the specific intent of this RP to identify, utilize, and reference existing U.S. and international hazardous materials (dangerous goods) transportation regulations, which are the only methodologies to be used to establish transportability. It is also the intent of this RP to provide recommendations to be used by service and shipping personnel for the purpose of determining a possibly damaged/defective battery’s transportability. In support of the service and shipping personnel, these recommendations seek to use standard tools of the trade and avoid laboratory type equipment.
Battery Transportation Committee
48 V High-power Battery Pack for Mild-Hybrid Electric Powertrains2020-01-04414/14/2020
Mild hybridisation, using a 48 V system architecture, offers fuel consumption benefits approaching those achieved using high-voltage systems at a much lower cost. To maximise the benefits from a 48 V mild-hybrid system, it is desirable to recuperate during deceleration events at as high a power level as possible, whilst at the same time having a relatively compact and low cost system. This paper examines the particular requirements of the battery pack for such a mild-hybrid application and discusses the trade-offs between battery power capabilities and possible fuel consumption benefits. The technical challenges and solutions to design a 48 V mild-hybrid battery pack are presented with special attention to cell selection and the thermal management of the whole pack. The resulting battery has been designed to achieve a continuous-power capability of more than 10 kW and a peak-power rating of up to 20 kW. The pack has been built and has been subjected to a series of tests at a range of ambient temperatures. The performance of the pack has been validated and the main characteristics, such as the internal resistance and capacity have also been established. The performance targets for the pack have been achieved. Further testing is underway to fully characterize the pack’s capabilities and characteristics, after which it will be installed into MAHLE’s 48 V eSupercharged demonstrator car.
Hall, JonathanBorman, StephenHibberd, BenjaminBassett, MichaelReader, SimonBerger, Martin
Development and Demonstration of a New Range-Extension Hybrid Powertrain Concept2020-01-08454/14/2020
A new range-extension hybrid powertrain concept, namely the Tongji Extended-range Hybrid Technology (TJEHT) was developed and demonstrated in this study. This hybrid system is composed of a direct-injection gasoline engine, a traction motor, an Integrated Starter-Generator (ISG) motor, and a transmission. In addition, an electronically controlled clutch between the ISG motor and engine, and an electronically controlled synchronizer between the ISG motor and transmission are also employed in the transmission case. Hence, this system can provide six basic operating modes including the single-motor driving, dual-motor driving, serial driving, parallel driving, engine-only driving and regeneration mode depending on the engagement status of the clutch and synchronizer. Importantly, the unique dual-motor operation mode can improve vehicle acceleration performance and the overall operating efficiency. The hybrid system controls and energy management strategy based on equivalent fuel consumption minimization were developed and validated. The choice of an operating mode is optimized according to the drivers’ demand, actual vehicle state, operation conditions, and other boundary conditions. In this paper, the powertrain architecture and operating modes are firstly described. Secondly, the hybrid control strategy is introduced, which includes the control architecture, energy management strategy, torque structure and coordination, and controls of the engine, clutch, and synchronizer. Thirdly, the development of a prototype vehicle with the use of the TJEHT system is discussed. Based on the simulation analysis, the key specifications of the major components such as the motors’ peak powers and torques are defined. The vehicle performance is compared in the simulations between using the TJEHT system and the one without the dual-motor driving mode to show the advantages of the TJEHT system. Finally, the results of the powertrain dyno experiments and vehicle road tests are reported. The functional requirements and operating modes of the hybrid powertrain were demonstrated and validated.
Han, ZhiyuWu, ZhenkuoGao, XiaojieSun, YongzhengNi, RunyuFeng, Jianzhong, JianChen, XinboZhao, ZhiguoYu, Zhuoping
Energy Management of Dual Energy Source of Hydrogen Fuel Cell Hybrid Electric Vehicles2020-01-05954/14/2020
With the growing shortage of oil resources and the increasingly strict environmental regulations, countries are vigorously developing new energy vehicles, and as a truly zero-emission vehicle in the application, fuel cell electric vehicles can not only completely replace gasoline cars in term of fuel, but also have the advantages of high energy conversion efficiency, short hydrogenation time and long driving range. For Fuel Cell Hybrid Electric Vehicle (FCEV), and the Energy Management Control Strategy is the "core" of the whole vehicle control system, which has a direct and significant effect on the power and economy of the vehicle. In this paper, the "dual energy source system" composed of fuel cell and power battery is taken as the research object. Based on the proposed power system structure, a fuel cell hybrid power management control strategy is designed, and the simulation model based on Matlab/Simulink and real vehicle are adopted to perform performance verification on standard operating conditions. The strategy aims at optimizing the power and economy, sets the target control value of the SOC, coordinates the power output of the "dual energy source system" of the vehicle, reduces the load power fluctuation of Fuel Cell System(FCS), optimize the working range of fuel engine and improve the energy recovery efficiency according to the vehicle energy demand, the real-time status of the assembly and the vehicle operating conditions, so that the fuel cell and the power battery work as much as possible in the optimal efficiency range. The test results in vehicle show that the energy management control method is effective in engineering application, and the performance has reached the vehicle design goal.
Zhao, YongqiangSong, HaoyuanLiu, YuanzhiYu, Zhao
The search for alternative fuel for transport vehicles and also replacement of internal combustion engines in order to reduce the harmful emissions have been forcing the vehicle manufacturers to innovate new technology solutions for meeting the stringent legislative targets. Mexico’s commitment for de-carbonisation of transport sector and meeting the environmental goals is shaping it especially, and with this, it favours the move towards electrification of the vehicles. The aim of the present work is to numerically evaluate the possibility of replacing the IC engine in the existing hybrid vehicles with the Hydrogen fuel cell system. This work modelled a Hydrogen fuel cell vehicle based on Toyota MIRAI and validated the fuel economy performance of the vehicle using experimental data. This validated model was used to estimate the fuel economy for real-world drive cycles generated in 2019 from Mexico City. It considered three different drive cycles representing real-world driving in the Metropolitan Area of the Valley of Mexico. This study estimated the amount of reduction in CO2 and other pollutants for the year 2020, and 2030 and 2040 if the IC engine in the electric hybrid vehicles is replaced with the Hydrogen fuel cell. The study also estimated the amount of Hydrogen fuel required for replacing the IC engines with the Hydrogen fuel cell for moving towards electrification of light duty vehicles.
Samuel, StephenGonzalez-Oropeza, RogelioCedillo Cornejo, Eduardo
Sensorless Individual Cell Temperature Measurement by Means of Impedance Spectroscopy Using Standard Battery Management Systems of Electric Vehicles2020-01-08634/14/2020
Lithium ion technology is state of the art for actual hybrid and electrical vehicles. It is well known that lithium ion performance and safety characteristics strongly depend on temperature. Thus, reliable temperature measurement and control concepts for lithium ion cells are mandatory for applications in electrical cars. Temperature sensors for all individual cells increase the battery complexity and cost of a battery management system. Normally, temperature is measured on module level in current battery packs, without observation of the individual cell temperature. Sensorless cell impedance-based temperature measurement concepts have been published and are validated in laboratory studies. Dedicated test equipment is usually applied, which is not useful for automotive series application. This work describes a practical approach to enable impedance-based sensorless internal temperature measurement for all individual cells using state-of-the art battery management system components. Excitation is generated by DC to DC converters of a standard commercial active balancing systems. For data acquisition, also an established commercial battery monitoring circuit unit is used. To overcome bandwidth limitations, a sub-sampling scheme is presented, which allows to determine the impedance at higher frequencies than the sampling rate. Impedance calculation is performed by means of efficient digital signal processing concepts with low demand on memory and processing power. Thus, the method can be integrated into existing battery management systems with low implementation effort. The concept is demonstrated on a 4-cell submodule of 26 Ah automotive Li-ion cells. It can also be applied in low-cost battery management systems without active balancing capability.
Haussmann, PeterMelbert, Joachim
Direct Yaw Moment Control of Electric Vehicle with 4 In-Wheel Motors to Improve Handling and Stability2020-01-09934/14/2020
More and more OEMs are interested in in-wheel-motor drive vehicles. One of the in-wheel-motor drive vehicle key technologies is multi-motor torque distribution. A direct yaw moment control strategy for torque distribution was introduced in this paper to improve 4 in-wheel-motor electric vehicle’s handling and stability. The control method consists of three components: feedback control based on target yaw rate, feedforward control based on current lateral acceleration and deceleration control based on under/oversteer situation. Feedback control is used to make vehicle’s real yaw rate following the driver’s target yaw rate and improve vehicle yaw rate response and stability. The target yaw rate is calculated by 2DOF vehicle model and limited by lateral acceleration and vehicle current steering condition. The feedforward control is used to increase the vehicle yaw rate gain and reduce the vehicle understeer characteristic when accelerating in a curve. The deceleration control can reduce the driving torque of each motor to slow down the vehicle when in critical steering condition. The proposed control strategy was verified by an in-wheel-motor drive electric vehicle test and the experiment result showed that it can reduce vehicle understeer characteristic in steady steering condition, improve vehicle yaw rate response in transient steering condition and enhance vehicle steering stability in critical steering condition.
Zhao, YongqiangCui, JinlongZhou, ZehuiFang, YangWang, DepingZhang, TianqiangWu, AibinSun, QichunZhao, Yang
Using Design of Experiments to Size and Calibrate the Powertrain of Range-Extended Electric Vehicle2020-01-08494/14/2020
A Range-Extended Electric Vehicle (REEV) usually has an auxiliary power source that can provide additional range when the main Rechargeable Energy Storage System (RESS) runs out. The range extender can be a fuel cell, a gas turbine, or an Internal Combustion Engine (ICE) bolted to a generator. Sizing the powertrain for a REEV is primarily to investigate the relationship between the capacity of the main RESS and the power rating of the range extender. Worldwide harmonized Light vehicles Test Procedures (WLTP) introduced a Utility Factor (UF) which is a curve used to calculate the weighted test results for the Off-Vehicle Charging-Hybrid Electric Vehicle (OVC-HEV) from the measured Charge Depleting (CD) mode range result, and the Charge Sustaining (CS) mode Fuel Consumption (FC). Therefore, the RESS capacity, the range extender power rating, the control strategy, and the UF are the key factors affecting the weighted FC of a REEV on the test cycle. The aim of this study is to demonstrate a fast approach to develop REEV powertrain concepts. It can size the capacity of the RESS (assumed electric battery for this paper), the power rating of the range extender and meanwhile consider the control strategy and the UF for a REEV, using simulation and Design of Experiments (DoE) tools. For the selected REEV powertrain, a DoE test matrix of the battery capacity, range extender power rating, and control strategy was created. The test cases were then imported into the simulation environment to perform the driving cycle simulations. After that, the simulation results (along with the UF) were used to calculate the weighted FC. Finally, a REEV weighted FC emulator model was created and interrogated using model visualisation and optimisation methods. Furthermore, the weighted FC’s calculated by using different regional Utility Factors were compared and discussed.
Bao, RanBaxter, JamesRevereault, Pascal
Dynamic Load Identification for Battery Pack Bolt Based on Machine Learning2020-01-08654/14/2020
Batteries are exposed to dynamic load during vehicle driving. It is significant to clarify the load input of the battery system during vehicle driving for battery pack structural design and optimization. Currently, bolt connection is mostly applied for battery pack constraint to vehicle, as well as for module assembly inside the pack. However, accurate bolt load is always difficult to obtain, while directly force measurement is expensive and time consuming in engineering. In this paper, a precise data driven model based on Elman neural network is established to identify the dynamic bolt loads of the battery pack, using tested acceleration data near bolts. The dynamic bolt force data is measured at the same time with the acceleration data during vehicle running in different driving conditions, utilizing customized bolt force sensors. A data preprocessing method synthesizing Wavelet denoising method and machine learning algorithm is designed to improve model precision under dynamic condition. Parts of the pretreated acceleration and force data that obtained in various driving conditions are employed for model training, while the rest for model validation. Meanwhile, an index is introduced to quantitatively assess the identification accuracy against the measured force data. The identified loads show good consistency with the tested data. The error of the estimated bolt force result is within 20%. Finally, the reliability and generalization of the method are discussed. This method in this paper does not rely on prior known structural characteristics, and may be further developed for mechanical monitoring and diagnosis in battery modules in the future.
Liu, RuixueHou, ZhichaoWang, ShuyuSheng, DekeLiu, Yuan
Optimization of Diesel Engine and After-treatment Systems for a Series Hybrid Forklift Application2020-01-06584/14/2020
This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle. In addition, the thermal management strategies like retarding injection timing and late post-injection of fuel during cold start are analyzed in this work. The results show the reduction of tailpipe- NOx emission is possible by properly retarding the injection timing without a significant effect on unburned hydrocarbon emissions. The designed series hybrid powertrain uses a heuristic-based controller to define different modes of operation. The performance of powertrain is then evaluated in the VDI 2198 cycle. The energy flows from the battery and the engine fuel consumption are optimized to overcome the rolling resistance and lifting hydraulic load in an energy-efficient way. The energy recuperation possibility in the forklift application is high as it consists of intermittent peak loads in the VDI cycle. The simulation results show that the designed series hybrid powertrain forklift can save fuel up to 20% compared to forklifts with conventional powertrain operating in the VDI 2198 cycle. In addition, the operational cost of the after-treatment system is reduced by 19.8%.
Maharjan, RomanShahbakhti, MahdiRezaei, RezaMöllmann, RicoHuang, YinyanDelebinski, Thaddaeus
Trade-Off Analysis and Systematic Optimization of a Heavy-Duty Diesel Hybrid Powertrain2020-01-08474/14/2020
While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain. However, certain heavy-duty applications, such as Class 6-7 urban vocational trucks, can benefit from hybridization due to their transient operating profiles and relatively lower vehicle weight. While many studies have quantified the fuel consumption benefits of hybridization in this segment, very few studies have outlined the arduous process of selection and sizing of hybrid powertrain components based on the trade-offs between fuel consumption, payback period, cost, weight, packaging, emissions and aftertreatment temperature. To investigate the potential for electrification in heavy-duty applications, FEV has developed a system level approach for the selection and sizing of heavy-duty diesel hybrid powertrain components using GT-SUITE. The approach has been applied for a Class 6-7 urban vocational truck, which typically experiences low speed driving with frequent start-stops. A dynamic model for the baseline vehicle was developed and calibrated to test data that included, fuel efficiency, engine-out NOx, engine-out PM and aftertreatment system temperature. The model was then updated with hybrid powertrain components and evaluated over cycles developed for chassis dynamometer testing of heavy-duty vehicles, specifically the Heavy Heavy-Duty Diesel Truck (HHDDT) schedule and EPA Urban Dynamometer Driving Schedule (HDUDDS). In the evaluation, key trade-offs were identified between fuel consumption, initial cost, payback period, package size, emissions and vehicle weight. The trade-off analysis demonstrated that similar fuel consumption benefits with an identical payback period could be achieved with multiple hybrid powertrain configurations, however package size, initial cost and weight considerations determined the final optimum solution. The final hybrid powertrain configuration for a Class 6-7 urban vocational truck proposed from this study demonstrates a 20.7% fuel consumption reduction when comparing to the baseline vehicle and applying a two year payback period. In addition, the diesel hybrid powertrain configuration provides an 11% reduction in engine-out NOx emissions and an 86% reduction in engine-out PM emissions, while maintaining aftertreatment temperature of the baseline configuration.
Joshi, SatyumDahodwala, MufaddelKoehler, Erik W.Franke, MichaelTomazic, DeanNaber, Jeffrey
Performance Evaluation of a Heavy-Duty Diesel Truck Retrofitted with Waste Heat Recovery and Hybrid Electric Systems08-09-01-00043/11/2020
The interest of long-hauling companies about the conversion of their fleets into low-emission and fuel-efficient vehicles is growing, and retrofitting options may represent a suitable solution. Powertrain hybridization and waste heat recovery are considered among the most promising methods to further improve the fuel economy of road vehicles powered by internal combustion engines. In this article, not only the effect of retrofitting a heavy-duty truck with an electrification-oriented ORC unit or with a series hybrid system is investigated, but also the possibility of implementing both at the same time. The conventional vehicle is powered by a heavy-duty 12.6 liters diesel engine. It is shown that, despite such a large engine has high potential for waste heat recovery, on the other hand it represents a very challenging constraint when designing a hybrid retrofitting. Four powertrain options are considered: conventional vehicle (engine-only powered), waste heat recovery retrofit, hybrid retrofit, waste heat recovery+hybrid retrofit. For the hybrid powertrains, the optimal control strategy is analyzed and used as a starting point to develop an online implementable rule-based control strategy. The performance of the different powertrains have been numerically simulated over a set of driving cycles. The results show that, compared to the conventional powertrain, the hybrid retrofit allows the greatest reduction in fuel consumption (up to 17%), and the best employment of the waste heat recovery system.
Villani, ManfrediLombardi, SimoneTribioli, Laura
Optimal Sizing and Control of Battery Energy Storage Systems for Hybrid Turboelectric Aircraft2020-01-00503/10/2020
Hybrid-electric gas turbine generators are considered a promising technology for more efficient and sustainable air transportation. The Ohio State University is leading the NASA University Leadership Initiative (ULI) Electric Propulsion: Challenges and Opportunities, focused on the design and demonstration of advanced components and systems to enable high-efficiency hybrid turboelectric powertrains in regional aircraft to be deployed in 2030. Within this large effort, the team is optimizing the design of the battery energy storage system (ESS) and, concurrently, developing a supervisory energy management strategy for the hybrid system to reduce fuel burn while mitigating the impact on the ESS life. In this paper, an energy-based model was developed to predict the performance of a battery-hybrid turboelectric distributed-propulsion (BHTeDP) regional jet. A study was conducted to elucidate the effects of ESS sizing and cell selection on the optimal power split between the turbogenerators (TGs) and ESS. To this extent, the supervisory energy management strategy is formulated into a discrete time optimal control problem and solved via dynamic programming. The performance of BHTeDP was compared to a turboelectric distributed-propulsion (TeDP) next-gen aircraft that assumes improvements in weight, drag, and engine efficiency consistent with regional jet entering operation in 2035.
Sergent, AaronnRamunno, MichaelD'Arpino, MatildeCanova, MarcelloPerullo, Christopher
Balancing Strategy for a Battery Applied in HEV Based on Bi-directional Flyback Converter and Outlier Detection2019-36-02421/13/2020
Dissipative cell balancing generates heat during its operation. Current techniques do not guarantee optimal balance of battery pack energy, requiring a high-cost Battery Management System (BMS) solution and wasting energy in the form of heat. Mild Hybrid Electric Vehicles uses the combustion engine to recharge the battery. Therefore, this feature requires a BMS balancing system capable of optimizing battery capacity and still be energy efficient. In this way, a non-dissipative balancing system would be interesting, especially if an algorithm works with the former non-dissipative balancing method, which efficiently determines which cells are unbalanced. In this paper, a methodology is proposed to perform non-dissipative balance of lithium-ion cells. This method considers which cells inside a certain range are considered balanced and cells outside this range are considered unbalanced. The range is given by the median of the cells terminal voltage summed with a threshold defined by experimental tests. Due the non-dissipative method presented herein is conceived through Flyback topology, the cells above this range are discharged and their extra energy is employed to charge the lowest charged cells, which were below the range. Simulation results which after the first 5 hours of balancing, the maximum difference does not exceed 1% and the standard deviation 0.5% until the end of the simulation, reducing SOC standard deviation by more than 33 times in one day operation. This result shows the strategy is promising to make a more efficient balancing mechanism for Mild Hybrid Electric Vehicles.
Marques, Felipe L. R.Aranha, Juliana C. M. S.Padela, Fernando F.Rosolem, Maria de Fátima N. C.Beck, Raul F.
Experimental Investigation of Electric Vehicle Performance and Energy Consumption on Chassis Dynamometer Using Drive Cycle Analysis13-01-01-000212/2/2019
This article reports an experimental study carried out to investigate the vehicle performance and energy consumption (EC) of an electric vehicle (EV) on three different driving cycles using drive cycle analysis. The driving cycles are the Indian Driving Cycle (IDC), Modified Indian Driving Cycle (MIDC) and Worldwide harmonized Light vehicles Test Cycle (WLTC). A new prototype electric powertrain was developed using an indigenous three-phase induction motor (3PIM), Li-ion battery (LiB) pack, vector motor controller, and newly developed mechanical parts. In this research work, a pollution-causing gasoline car (Maruti Zen) was converted into an EV by using the new powertrain. The EV conversion vehicle was used as the test vehicle. After the removal of the Internal Combustion Engine (ICE) the new powertrain was integrated with the vehicle’s gearbox (GB) system which was configured on a single motor, fixed gear configuration having a gear ratio of 1.28:1. The EV performance tests were carried out on the chassis dynamometer that followed the driving cycles. The maximum speed test showed a top speed of 64 km/h for the EV. The average vehicle speed and EC of the EV were 21.82 km/h and 106.23 Wh/km for the IDC, 17.75 km/h and 110.91 Wh/km for the MIDC-I, and 19.57 km/h and 87.35 Wh/km for the WLTC-low, respectively. The test results of battery current, input power, mechanical power, and EC with respect to the vehicle speed and torque versus motor rpm were analyzed and discussed. It was observed that the performance and EC of the test EV need to be improved. The study and test results verified the new electric powertrain system (EPT) suitable for a city EV and provided useful data for design and performance improvement of the indigenous battery and motor drive system.
Lairenlakpam, RobindroKumar, PraveenThakre, Gananath Doulat
A Novel Approach on Range Prediction of a Hydrogen Fuel Cell Electric Truck2019-28-251411/21/2019
Today’s growing commercial vehicle population creates a demand for fossil fuel surplus requirement and develops highly polluted urban cities in the world. Hence addressing both factors is very much essential. Battery electric vehicles are with limited vehicle range and higher charging time. So it is not suitable for the long-haul application. In further the hydrogen fuel cell-based electric vehicles are the future of the commercial electric vehicle to achieve long-range, zero-emission and alternate for reducing fossil fuels requirement. The hydrogen fuel cell electric vehicle range, it means the total distance covered by the vehicle in a single filling of hydrogen into the onboard cylinders. And here the prediction of the vehicle range is essential based on optimal parameters; vehicle acceleration, speed, trip time etc. before the start of the trip. If the driver starts the vehicle without range prediction and optimum driving strategy, will be led into midway vehicle stoppage and excessive energy consumption of the trip. This paper deals with different methods of electric vehicle range prediction and optimization, benefits and demerits are listed and discussed, to provide a fair idea on hydrogen fuel cell electric vehicle range prediction. Also, the paper has concluded with the optimization strategy for the vehicle range by analyzing the vehicle powertrain module, battery module, fuel cell module, hydrogen fuel supply module and the vehicle module. The strategy presented in this paper is aiming for assisting the driver in formulating a driving strategy and for trip planning based on optimization trip parameters, considering optimum energy consumption. One fuel cell vehicle tested with proposed strategies and results observed are matching. And there may be a scope of improvement if the researchers test on multiple vehicles.
Chandrasekar, C VenkateshAmruth Kumar, L R
Recent Trends on Drivetrain Control Strategies and Battery Parameters of a Hybrid Electric Vehicle2019-28-015510/11/2019
Environmental consciousness is being developed in each and every sector, automotive industry has concentrated in a greater manner. Reduction of tail pipe emission was concentrated and found that hybridization can ensure better results. Hybrid electric vehicle operates on electric motor as well as internal combustion engine. Battery power is one the major source of energy for driving electric motor and different battery technologies have been developed. Battery management system (BMS) controls battery parameters like State of Charge (SoC), State of Health (SoH) and Depth of Discharge (DoD) which definitely has an impact on power-torque ratings. Various drive train configurations are developed based on the power-torque requirements and size of engine/electric motor. Maintaining proper flow of energy can have better reduction in emissions, more battery life, less fuel consumption and optimum power-torque ratings. Power and torque has to be varied based on the driver’s requirement, maximum power and torque may not be required all the time and that is the area to capitalize some efficiency. Higher fuel efficiency lies in managing energy flow from various power sources to final drive. Energy flow can be controlled by deploying certain logical constraints on battery management system along with drive train which optimises the losses, optimization techniques have shown better results in control of power-torque ratings. This paper explains about the various drive train configurations, battery technologies and their control techniques. Wide range of future scope has been explained by routing each and every technology involved in hybrid vehicles
Bhaskar, Pavan BharadwajaDeshmukh, SandipKhannan, PrashanthShaik, Amjad
Thermal Behavior Analysis of Lithium Ion Cells used in EVs and HEVs2019-28-016310/11/2019
The batteries for electric vehicles (EV) generate heat during discharging cycles. During these rapid discharge cycles the temperature of cell may increase above allowable limits. The high temperature of lithium ion cell is the primary factor affecting the cell performance and life. To develop efficient cooling mechanism for batteries, thermal behavior of secondary cell is must know. In this research, experimentally the thermal behavior analysis of cylindrical lithium ion cells at constant current discharge cycles with different current rates for each cycle is evaluated. The experiments were carried out at three discharge cycles of 1C, 2C and 3C rates and two battery chemistries namely NiMnCo and NiCoAlare considered for analysis. The instantaneous temperature of cell was measured using thermal imager and increase in overall cell surface temperature at different discharge rates, for entire discharging interval has been studied. An empirical relation for average surface temperature of cell at different current rates and depth of discharge has been obtained which may find application in defining the discharge algorithms. The rates of internal heat generation in both types of cell chemistry are calculated from the temperature data obtainedexperimentally. The extensive comparison of two cell chemistries on the basis of internal heat generation rate and rise in average surface temperature of cells for different current rates will help in battery selection and efficient designing of cooling mechanisms in battery pack. The experimental results in this research conclude that NiMnCo cell has least instantaneous internal heat generation rate at all current rates and is therefore safer and more thermally stable than NiCoAl cell.
Lonkar, Shubham GaurishankarJain, AatmeshBhalerao, Vikrant
An Energy Management Strategy for Through-the-Road Type Plug-in Hybrid Electric Vehicles08-08-01-00049/19/2019
This article proposes an energy management strategy for a through-the-road (TTR) plug-in hybrid electric vehicle (PHEV) to achieve efficient fuel consumption performance. The target hybrid powertrain includes an electric traction motor, an integrated starter/generator (ISG), and a gasoline internal combustion engine (ICE) in the front axle and another electric motor in the rear axle. The energy management strategy is organized into six functional modules. The power mode is determined by the driver’s pedal demand, vehicle states, and the characteristics of the related power units to increase the overall system efficiency. The energy management strategy and the vehicle models are established in the Matlab/Simulink by using dSPACE Automotive Simulation Models (ASM) software. The proposed strategy is examined in terms of three test scenarios in the Model-in-the-Loop (MiL) simulations. The vehicle operates in the EV mode in the range from 40% to 70% battery state of charge (SOC) to improve the fuel consumption. The ICE is ignited to charge the battery if SOC is under 40%. In the acceleration simulation, the ICE involves in the power output to compensate the required acceleration torque when the vehicle speed is over 80 kilometers per hour (kph). The simulation results show that the fuel consumption is computed as 77.34 miles per gallon (MPG) by adopting the proposed energy management strategy.
Chen, Ming-YenYang, KangSun, Yun-ZhongCheng, Jung-Ho
Downhill Safety Assistant Driving System for Battery Electric Vehicles on Mountain Roads2019-01-21299/15/2019
When driving in mountainous areas, vehicles often encounter downhill conditions. To ensure safe driving, it is necessary to control the speed of vehicles. For internal combustion engine vehicles, auxiliary brake such as engine brake can be used to alleviate the thermal load caused by the continuous braking of the friction brake. For battery electric vehicles (BEVs), regenerative braking can be used as auxiliary braking to improve brake safety. And through regenerative braking, energy can be partly converted into electrical energy and stored in accumulators (such as power batteries and supercapacitors), thus extending the mileage. However, the driver's line of sight in the mountains is limited, resulting in a certain degree of blindness in driving, so it is impossible to fully guarantee the safety and energy saving of downhill driving. Therefore, taking a pure electric light truck as an example, the system proposed in this paper first analyzes the driver's driving intention, proposes the system startup and exit strategy, and then combines the geographic information system (GIS) mountain road information, downslope speed limit and vehicle parameters, considering the motor and battery characteristics, establishes mathematical models such as the regenerative braking model and the brake temperature rise model based on vehicle dynamics and the conservation of energy, determines the appropriate braking mode(There are two braking modes)and the slope top safe speed by calculation, and reminds the driver when going uphill and downhill. The main goal is to use more regenerative braking, reduce the use or duration of the main brake, avoid overheating the main brake, improve the safety during continuous braking, and achieve smarter energy management. Finally, simulations are carried out under different conditions of vehicle speed, slope length, slope gradient and battery SOC. The results show that the system has a good energy-saving effect and can significantly improve the safety of BEVs running downhill.
Feng, Jia'aoTian, ZhongpengCui, JianZhou, FangyuTan, Gangfeng
A Coupled Lattice Boltzmann-Finite Volume Method for the Thermal Transient Modeling of an Air-Cooled Li-Ion Battery Cell for Electric Vehicles2019-24-02079/9/2019
Due to their ability to store higher electrical energy, lithium ion batteries are the most promising candidates for electric and hybrid electric vehicles, whose market share is growing fast. Heat generation during charge and discharge processes, frequently undergone by these batteries, causes temperature increase and thermal management is indispensable to keep temperature in an appropriate level. In this paper, a coupled Lattice Boltzmann-Finite Volume model for the three-dimensional transient thermal analysis of an air-cooled Li-ion battery module is presented. As it has already been successfully used to deal with several fluid-dynamics problems, the Lattice Boltzmann method is selected for its simpler boundary condition implementation and complete parallel computing, which make this approach promising for such applications. The standard Lattice Boltzmann method, here used only for the fluid-dynamic evolution, is coupled with a Finite Volume approach for solving the energy equation and recovering the temperature field throughout the whole domain (air, aluminum and battery). This coupled approach allows having a fully reliable control of the transients in conjugate heat transfer problems without introducing any simplification on thermal capacities, as commonly required by thermal Lattice Boltzmann methods. Prismatic Li-ion cells with a layer of an aluminum heat sink are considered in the battery pack design. Heat generation and voltage variation within each single cell are calculated by using an equivalent circuit model and heat transfer principles. Results are validated against data available in literature ensuring accuracy of the proposed numerical model and showing an excellent agreement with the reference. Finally, a parametric study to evaluate the cooling performance of a battery cell by varying the discharge rate and air velocity through the channels is proposed.
Chiappini, DanieleTribioli, LauraBella, Gino
Modeling of a Spark Ignition Engine with Turbo-Generator for Energy Recovery2019-24-00849/9/2019
Increasingly stringent regulations in the field of pollutant are forcing engine manufacturers to adopt new solutions to contain exhaust emissions, such as Hybrid Electric Vehicles (HEV) or Full Electric Vehicles (FEV). Still far from the wide diffusion of FEV limited from electrochemical storage systems together with the difficulty of creating adequate infrastructure distributed throughout the territory to recharging batteries, the HEV seems to be actually a better solution. The hybrid vehicle is already able to guarantee satisfactory autonomy and low pollution levels by combining the advantages offered by the two technologies of thermal and electric propulsion. Currently on the market there are several types of hybrid vehicles, with different degree of hybridization (electric motor power versus propulsion total power), capacity to store electricity and type of scheme constructive adopted for the integration between the thermal engine and the electric machine. A particular interest is getting the mild-hybrid (or light hybridization) and the micro-hybrid (or minimum hybridization) with 48V electrical system added to the classic 12V one. A possible solution could be the electric turbo-compounding system where a turbine coupled to a generator (turbo-generator) uses the exhaust gas flow of a reciprocating engine to harvest waste heat energy and convert it into electrical power. In this way, the power generated from the system can be used to feed local electrical loads such as engine auxiliaries, increasing the whole system efficiency. The present study deals with the simulation of a spark ignition engine, present in a test room of Istituto Motori (CNR), including a turbo-generator at the exhaust to evaluate the advantages in terms of overall efficiency. The internal combustion engine model was developed by using a 1D code (GT-Power software), while the turbo-generator and the electric system are described in the Matlab/Simulink environment. The results obtained showed an appreciable increase in the overall efficiency.
Arminio, FabioCameretti, Maria CristinaDe Simio, LuigiIannaccone, SabatoTerzo, Teodoro
Dual-Fuel Ethanol-Diesel Technology Applied in Mild and Full Hybrid Powertrains2019-24-01159/9/2019
The increasingly stringent emissions regulations together with the demand of highly efficient vehicles from the customers, lead to rapid developments of distinct powertrain solutions, especially when the electrification is present in a certain degree. The combination of electric machines with conventional powertrains diversifies the powertrain architectures and brings the opportunity to save energy in greater extents. On the other hand, alternative combustion modes as reactivity controlled compression ignition (RCCI) have shown to provide simultaneous ultra-low NOx and soot emissions with similar or better thermal efficiency than conventional diesel combustion (CDC). In addition, it is necessary to introduce more renewable fuels as ethanol to reduce the total CO2 emitted to the atmosphere, also called well-to-wheel (WTW) emission, in the transport sector. Therefore, the combination of these two growing technologies with the use of ethanol (E85) could be a potential way to achieve clean and efficient vehicles. In this work, numerical simulations of full hybrid electric vehicles (series, parallel and series-parallel) and mild hybrid vehicles were performed and compared versus the conventional powertrain in the WLTC driving cycle. The hybrid vehicles are simulated with both CDC and diesel-ethanol RCCI combustion engines as power source. Each powertrain was optimized in terms of electric components (battery capacity, electric motors...), internal combustion engine operating points, power management strategy and transmission/differential ratio to obtain the minimum fuel consumption and NOx emissions. The results show a significant reduction of the total mass consumption as the complexity of the hybrid system increases (more electrical devices needed). In this sense, the series-parallel architecture, which represents the most complex hybrid system, allows reducing the energy consumption around 20% compared to the conventional powertrain operating under CDC. In addition, the combined use of CDC and RCCI in the same engine map showed improvements in NOx, soot and CO2 emissions versus CDC. Moreover, the series hybrid powertrain obtained the lowest NOx and soot emissions values due to using fixed operating conditions in RCCI mode for the thermal engine. Lastly, the mild hybrid technology showed an acceptable balance between complexity and fuel consumption.
Benajes, JesusGarcia, AntonioMonsalve-Serrano, JavierMartinez, Santiago
Combined Sizing and EMS Optimization of Fuel-Cell Hybrid Powertrains for Commercial Vehicles2019-01-03874/2/2019
During the last years, fuel-cell-based powertrains have been attracting a lot of attention from commercial vehicle manufacturers for reducing vehicle-related Greenhouse Gas (GHG) emissions. Compared to Battery-Electric Vehicles (BEV), fuel-cell-based powertrains has the strong advantage of dealing with range-anxiety, which is crucial for commercial vehicle with high duty-cycle energy requirements. Amongst the different fuel-cell types, Proton Exchange Membrane Fuel-Cells (PEMFC) have the greatest potential for utilization in automotive applications, due to their relatively high technical readiness, market availability and utilization of hydrogen (H2) fuel. In addition, Solid Oxide Fuel-Cells (SOFC) show good potential due to existing re-fueling infrastructure for light hydrocarbon fuels or heavier hydrocarbon fuels (e.g. diesel). This study focuses on the application of both PEMFCs and diesel-fueled SOFCs in Fuel-Cell Hybrid Electric Vehicle (FCHEV) architectures for commercial vehicles. Delivery vans in the 2.5 t-3.5 t weight range, coach buses and 3-axle tractor-type long-haul trucks are considered energy-driven types and highly suitable for fuel-cell systems, which offer high energy density values. Due to the high number of vehicle application types and system configurations, and due to the complexity of such hybrid architectures, powertrain design loops can be very time-consuming and model-based systems engineering becomes necessary. This study proposes a combined model-based component sizing process with Energy Management Strategy (EMS) optimization for determining powertrain performance and total system costs. In the suggested approach, the initially considered design space is reduced to a lower number of feasible power source combinations based on initial estimations, fixed component efficiencies and vehicle performance requirements. An optimization algorithm is then utilized for all the feasible combinations on different drive-cycles, i.e. the time-based WLTP drive-cycle for delivery vans and modified distance-based VECTO drive-cycles for coach buses and long-haul trucks, with more detailed component performance characteristics, for vehicle sub-categories defined based on the market in the United Kingdom. The suggested design approach for FCHEV powertrain architectures is analyzed and presented.
Jokela, TommiIraklis, AthanasiosKim, BillGao, Bo
Design of a Grid-Friendly DC Fast Charge Station with Second Life Batteries2019-01-08674/2/2019
DC-fast charge (DCFC) may be amenable for widespread EV adoption. However, there are potential challenges associated with implementation and operation of the DCFC infrastructures. The integration of energy storage systems can limit the scale of grid installation required for DCFC and enable more efficient grid energy usage. In addition, second-life batteries (SLBs) can find application in DCFC, significantly reducing installation cost when compared to solutions based on new battery packs. However, both system architecture and control strategy require optimization to ensure an optimal use of SLBs, including degradation and thermal aspects. This study proposes an application of automotive SLBs for DCFC stations where high power grid connection is not available or feasible. Several SLBs are connected to the grid by means of low power chargers (e.g. L2 charging station), and a DC/DC converter controls the power to the EV power dispenser. The architecture of the DC bus, the size and state of health of the battery system determine efficiency, cost, and reliability of the station. A technical and economic comparison is proposed, evaluating solutions with different battery pack sizes and control strategies. An accurate numerical model is used to evaluate the performance of the different architectures. A realistic usage profile of the charging station is defined and real-world scenarios are considered for the SLB parameters.
D'Arpino, MatildeCancian, Massimo
Genetic Algorithm-Based Parameter Optimization of Energy Management Strategy and Its Analysis for Fuel Cell Hybrid Electric Vehicles2019-01-03584/2/2019
Fuel cell hybrid electric vehicles (FCHEVs) composed of fuel cells and batteries can improve the dynamic response and durability of vehicle propulsion. In addition, braking energy can be recovered by batteries. The energy management strategy (EMS) for distributing the requested power through different types of energy sources plays an important role in FCHEVs. Reasonable power split not only improves vehicle performance but also enhances fuel economy. In this paper, considering the power tracking control strategy which is widely adopted in Advanced Vehicle Simulator (ADVISOR), a constrained nonlinear programming parameter optimization model is established for minimizing fuel consumption. The principal parameters of power tracking control strategy are set as the optimized variables, with the dynamic performance index of FCHEVs being defined as the constraint condition. Then, the genetic algorithm (GA) is applied in the control strategy design for solving the optimization problem. The GA is combined with the vehicle model in ADVISOR to optimize parameters of control strategy respectively for two standard driving cycles, i.e. the Urban Dynamometer Driving Schedule (UDDS) and the Highway Fuel Economy Test (HWFET). Finally, the control strategies before and after optimization are simulated, then the related performances compared, and the optimal control parameters under different driving cycles analyzed. The simulation results demonstrate that by using the optimized power tracking control strategy, total fuel consumption of FCHEVs can be reduced by 17.6% and 9.7%, respectively, under UDDS and HWFET without compromising dynamic performance. Therefore, the GA optimization approach has the potential to reasonably adjust the parameters of EMS. In addition, even with the same control strategy, there should be different optimal control parameters value for different driving cycles.
Zhou, SuWen, ZejunZhi, XueleiJin, JieZhou, Shangwei
CVT Ratio Scheduling Optimization with Consideration of Engine and Transmission Efficiency2019-01-07734/2/2019
This paper proposes a transmission ratio scheduling and control methodology for a vehicle with a Continuous Variable Transmission (CVT) and a downsized gasoline engine. The methodology is designed to deliver the optimal vehicle fuel economy within drivability and performance constraints. Traditionally, the Optimum Operating Line (OOL) generated from an engine brake specific fuel consumption map is considered to be the best option for ratio scheduling, as it defines the points at which engine efficiency is maximized. But the OOL does not consider transmission efficiency, which may be a source of significant losses. To develop a CVT ratio schedule that offers the best fuel economy for the complete powertrain, an empirical approach was used to minimize fuel consumption by considering engine efficiency, CVT efficiency, and requested vehicle power. A backward-looking model was used to simulate a standard driving cycle (FTP-75) and develop a new powertrain-optimal operating line (P-OOL). Simulation results using the backward-looking model show a significant improvement in overall fuel economy when using the P-OOL (considers engine and CVT efficiency) compared to the OOL (considers only engine efficiency). Next, a forward-looking, velocity-driven model was developed to simulate the real-time behavior of a vehicle. Fuel economy results were compared when implementing the P-OOL and the OOL with a hardware-based CVT shift rate constraint. Finally, a control algorithm that considers powertrain loss and inertia torque due to CVT ratio changes is proposed to minimize powertrain response lag when operating along the P-OOL. This combined ratio scheduling and response lag control methodology is shown to improve vehicle fuel economy with real-time simulated driving conditions.
Deshmukh, PareshBeuerle, StevenHudson, JenniferChen, WeitianDai, EdwardHu, GuopengXu, Yang
Development of an Advanced Motor Control System for Electric Vehicles2019-01-05974/2/2019
Electric vehicles are considered as one of the most popular way to decrease the consumption of petroleum resources and reduce environmental pollutions. Motor control system is one of the most important part of electric vehicles. It includes power supply module, IGBT driver, digital signal processing (DSP) controller, protection adjustment module, and resolver to digital convertor. To implement the control strategies on motor control system, a lot of practical aspects need to be taken into accounts. It includes setup of the initial excitation current, consistency of current between motor and program code, over-modulation, field weakening control, current protection, and so on. In this paper, an induction motor control system for electric vehicles is developed based on DSP. The control strategy is based on the field-oriented control (FOC) and space vector pulse width modulation (SVPWM). Speed calculation, over-modulation, field weakening control, PI controller, and fault diagnosis are also applied in this DSP algorithm. As an industry product running on a real electric bus with a 100kW induction motor, communication with vehicle control unit (VCU) by CAN bus, control system safety and PC software designed for lab experiments are also discussed. This paper focused on how to develop the advanced motor control system for electric vehicles for industrial application. The steady-state and transient performances of this motor control system are analyzed by both test-bench experiments and road experiments. Its performance is satisfactory when applied to the real electric vehicle.
Men, XiaojinWu, GangGuo, YouguangZhu, ZhongwenGao, Jidong
Sensorless On Board Cell Temperature Control for Fast Charging2019-01-07914/2/2019
Fast charging capability is one of the key requirements for the success of electric vehicles. Considering the growing energy storage capacity of automotive batteries, fast charging can only be achieved using high-power charging systems. This leads to increased power dissipation inside the battery cells. The resulting heat generation inside the battery cell is a critical effect, as cell safety, performance and life time strongly depend on cell temperature and current. This must be considered by a simultaneous current and thermal battery management strategy, which requires reliable information about the individual cell temperature. Sensorless cell temperature can be derived from the cell impedance, where the charging current profile is superimposed by an excitation current and the resulting cell voltages are observed by the battery management system (BMS). An efficient algorithm for the impedance and temperature calculation can be implemented in actual BMS. In this work, this concept is verified by fast charging experiments. The thermal properties of a prismatic cell for electric vehicle energy storage are investigated under real boundary conditions, including effects of active fluid cooling. For a more detailed thermal analysis and modeling, cell surface temperature distribution is monitored by a temperature sensor array. The internal and external cell temperature increase is analyzed for different fast charging profiles. 3-dimensional thermal modeling is used to determine the internal peak temperature from the average measured temperature for a given cell type and assembly. The results can be used to define fast charging and thermal management strategies that are optimized for safe operation and long life.
Haussmann, PeterMelbert, Joachim
Full Battery Pack Modelling: An Electrical Sub-Model Using an EECM for HEV Applications2019-01-12034/2/2019
With a transition towards electric vehicles for the transport sector, there will be greater reliance put upon battery packs; therefore, battery pack modelling becomes crucial during the design of the vehicle. Accurate battery pack modelling allows for: the simulation of the pack and vehicle, more informed decisions made during the design process, reduced testing costs, and implementation of superior control systems. To create the battery cell model using MATLAB/Simulink, an electrical equivalent circuit model was selected due to its balance between accuracy and complexity. The model can predict the state of charge and terminal voltage from a current input. A battery string model was then developed that considered the cell-to-cell variability due to manufacturing defects. Finally, a full battery pack model was created, capable of modelling the different currents that each string experiences due to the varied internal resistance. The model was then validated with real-life data from the “Hill Route” section of the First Group Millbrook Fuel Economy Test Version 5.0 drive cycle of a mild hybrid electric bus. Results showed a strong correlation with the measured data and both the state of charge and terminal voltage simulations of the model. For the string model, results showed that there was a slight variance in the state of charge between cells in a string with varied capacities. However, terminal voltages between cells did not vary significantly with variances in internal resistance. Future work includes the creation of a thermal sub-model and an ageing sub-model, which considers whether the location of a cell within a pack has a correlation with its degradation. These sub-models will then be integrated and used as a full battery pack model.
Rolt, RyanDouglas, RoyNockemann, PeterBest, Robert
Items per page:
1 – 50 of 345