Browse Topic: Energy consumption

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The induced and profile power of a hovering rotor was evaluated using experimental and computational methods. Momentum theory principles were coupled with experimental measurements over a range of thrust conditions to characterize the induced and profile power consumption at low Reynolds number conditions ∼ 105. An empirical induced power factor, κi, was extracted to quantify the non-ideal losses. Results show that these losses increase as the Reynolds number reduces, and nearly twice the power is required at Retip = 0.27×105 than the ideal momentum theory prediction. These results were compared with high-fidelity computational fluid dynamics simulations using the partial-pressure field (PPF) force/power decomposition to extract the induced and profile power contributions of the rotor. The PPF method decomposes the static pressure field of a numerical Reynolds-averaged Navier-Stokes solution into Euler and dissipative partial pressure fields. Simulations were performed across a range of thrust conditions, from which the induced power factor and profile drag coefficient,Cd0 , were computed for each simulation from the extracted power contributors.
Moore, ZacharySilwal, LokeshVijayaraj, AdityaRaghav, VrishankAbraham, AlbertSchmitz, Sven
This document covers the requirements for SAE implementations based on ISO 17987:2016. Requirements stated in this document will provide a minimum standard level of performance to which all compatible ECUs and media shall be designed. This will assure full serial data communication among all connected devices regardless of supplier.The goal of SAE J2602-1 is to improve the interoperability and interchangeability of LIN devices within a network by adding additional requirements that are not present in ISO 17987:2016 (e.g., fault tolerant operation, network topology, etc.).The intended audience includes, but is not limited to, ECU suppliers, LIN controller suppliers, LIN transceiver suppliers, component release engineers, and vehicle system engineers.The term “master” has been replaced by “commander” and term “slave” with “responder” in the following sections.
Vehicle Architecture For Data Communications Standards
Advanced Air Mobility (AAM) is an innovative concept that aims to revolutionize air transportation through electric and unmanned aircraft, enabling applications such as urban air taxis and medical transport. However, one of the key challenges to its widespread adoption is ensuring safety, particularly in collision avoidance. This study focuses on the development of a perception and guidance system for avoiding collisions with non-cooperative targets, which do not share their position or trajectory. To achieve this, a Frequency-Modulated Continuous Wave (FMCW) radar and an InfraRed(IR) camera are used. Compared to traditional pulsed or panel radars, FMCW radars offer higher resolution, better detection of small and slow-moving objects, and improved performance in cluttered environments. The IR camera enhances situational awareness by providing visual confirmation and additional tracking capability, making this sensor fusion approach particularly suitable for AAM applications. Our collision avoidance system follows ACAS Xu standards, which provide autonomous conflict detection and resolution for unmanned aerial vehicles. The maneuver selection process is based on precomputed lookup tables generated through a Markov Decision Process (MDP), optimizing responses based on risk and energy consumption. The entire system is tested in a simulation environment using Ansys AVxcelerate, a physics-based simulator capable of generating realistic sensor data. This approach allows for comprehensive testing of detection, tracking, and maneuver execution in a highly realistic scenario, ensuring the effectiveness of the proposed solution before real-world deployment.
Brivio, RiccardoCrippa, AnnaBaiguera, MatteoPortanti, SamueleBertolo, Mattia
Helicopters' Vertical Take-Off and Landing (VTOL) capabilities are essential for maritime operations, especially for small-deck naval vessels. Unmanned Aerial Vehicles (UAVs) offer a cheaper, expendable, and efficient alternative for certain tasks, such as reducing pilot risk and lowering fuel consumption. While the procedures to approach and land on (moving) ships are standardized and bound to established operational limits in the case of crewed helicopters, UAVs lack such guidelines. This study investigates optimal rotary-wing UAV approach trajectories to a moving ship, for varying wind conditions and relative initial positions, and for different objectives. The goal is to provide preliminary guidelines for maritime UAV recovery operations, and a preliminary estimation of performance-based operational limits. The optimal trajectories are obtained using a global path-performance optimization framework based on Optimal Control Theory. The trajectories are compared to each other and to reference cases using the Longest Common SubSequence (LCSS) similarity measure, revealing how the unmanned helicopter adjusts its path to exploit the wind direction and profile for more efficient ground speeds. The violation of performance and/or geometric constraints is used to preliminarily indicate the presence of operational boundaries. The control effort and energy consumption are used to identify optimal starting positions for the helicopter approach phase for a given wind profile and intensity.
Pavel, MarilenaVoskuijl, MarkVarriale, CarmineZilver, Damy
This study investigates the effects of chord-to-radius ratio (c/R) and blade count on the aerodynamic and aeroacoustic performance of cyclorotors through experimental testing and a low-fidelity streamtube model. Cyclorotors with c/R ratios between 0.3 to 0.75 and blade counts ranging from 5 to 9 were tested across pitch amplitudes up to 51°. For a 5-bladed configuration, the pitch amplitude that maximizes the force-to-power coefficient (CF/CP) increases with c/R from approximately 32° at low c/R to around 51° at high c/R. However, the peak attainable CF/CP decreases with increasing c/R, indicating a trade-off between optimal pitch amplitude and aerodynamic efficiency. Increasing blade count enhances the generated force but reduces efficiency in all cases except for the lowest c/R configuration (0.3). Aeroacoustic analysis shows that tonal noise is primarily driven by pitch amplitude and intensifies with increasing c/R, while additional blades effectively mitigate it. In contrast, broadband noise is less sensitive to variations in pitch amplitude, c/R, and blade count. The streamtube model captures key aerodynamic trends, particularly at moderate pitch amplitudes. Scaling studies identify optimal configurations for a given disk loading, balancing power consumption and noise levels and highlighting key trade-offs critical to urban air mobility applications.
Venkatraman, KartikBliamis, ChrisCarrasco Larana, Pedrovan Rooij, Anouk
The transition phase of eVTOL aircraft poses a challenge in balancing energy efficiency and stability. This study presents the development and evaluation of an automatic flight control system for eVTOL transition phases, focusing on minimizing energy consumption while ensuring robust performance. The control architecture implements a hybrid response type combining Translational Rate Command below 5 knots and Acceleration Command Speed Hold above 5 knots, with control allocation dynamically adjusted based on airspeed and rotor shaft angle. Stability analysis reveals surge mode instability at high shaft angles due to negative speed stability derivatives, stabilized through carefully tuned feedback control. The system demonstrates Level 1 handling qualities against bandwidth, quickness, and disturbance rejection criteria when evaluated against MIL-DTL-32742 and MIL-STD-1797B standards. Simulation results verify the control system's ability to maintain precise acceleration/deceleration rates and attitude control while ensuring passenger comfort through limited pitch excursions. The control strategy achieves minimum energy transitions by locking rotor shaft angles to optimal schedules while avoiding excessive hub moments. Flight test maneuvers developed specifically for conversion phases confirm the system's capability to execute efficient transitions within defined performance boundaries. This research establishes a framework for certifiable eVTOL flight control systems that balance energy efficiency with robust performance across diverse flight regimes.
Kang, NamukLu, LinghaiWhidborne, James
ABSTRACT Determining the required power for the tractive elements of off-road vehicles has always been a critical aspect of the design process for military vehicles. In recent years, military vehicles have been equipped with hybrid, diesel-electric drives to improve stealth capabilities. The electric motors that power the wheel or tracks require an accurate estimation of the power and duty cycle for a vehicle during certain operating conditions. To meet this demand, a GPS-based mobility power model was developed to predict the duty cycle and energy requirements of off-road vehicles. The dynamic vehicle parameters needed to estimate the forces developed during locomotion are determined from the GPS data, and these forces include the following: the gravitational, acceleration, motion resistance, aerodynamic drag, and drawbar forces. Initial application of the mobility power concept began when three U.S. military’s Stryker vehicles were equipped with GPS receivers while conducting a proofing mission at the Pohakuloa Training Area (PTA) in Hawaii on a soil with a known rating cone index (RCI). An analysis was conducted on the GPS data which allowed for the variation in the Stryker’s mobility power to be estimated as the vehicle traversed the terrain. The subsequent power duty cycle and required energy for the vehicle was determined along with predicted specific energy consumption and production values. Initial validation of the mobility power model began by tracking a hybrid 2006 Toyota Highlander during acceleration tests and on-road maneuvers. The model had an R2 and average absolute percent error of 0.91 and 12.9% respectively during the acceleration tests. The predicted and measured mobility power duty cycles were similar during the on-road maneuvers while an R2 and average absolute error of 0.44 and 7.1 kW was attained.
Ayers, PaulBozdech, George
Design modifications to a 3lb variant of DEVCOM Army Research Laboratory's Common Research Configuration (CRC-3) are assessed using simulation tools. To identify areas for improvement, the baseline CRC-3 is analyzed in hover and forward flight, and contributors to overall power consumption are identified, with the rotor drag consuming the greatest amount of power, due to the high rotational speeds required to maintain thrust in the face of the freestream velocity. Potential areas for improvement are identified as: wing airfoil, rotor blade pitch, and rotor orientation. Changing the airfoil has little to no measurable effect on the overall power consumption. Increasing the blade pitch improves cruise performance considerably, but at the cost of hover efficiency, for an overall range improvement of up to 28%. Changing the rotor orientation improves rotor efficiency as well, without substantial cost to hover power consumption, increasing the range by 37% but will require a redesign of the CRC-3 supporting structure to avoid the blades striking the structure. Experimentally determined trim sweeps of pitch and power requirement are shown for the quadrotor, tailsitter, and three different wing incidence angles (10◦, 20◦, and 40◦), showing up to 28% reductions in minimum power.
Niemiec, RobertGerdes, JohnHensel, RemiReddinger, Jean-PaulGandhi, Farhan
In over actuated aircrafts a simple relationship between control inputs and forces/moments generated does not exist, however they have become very attractive for their wide range of applications. Control allocation aims at finding a unique surface control distribution as function of flight condition to perform the desired maneuver. The goal of this paper is to present a control allocation methodology applied on a generic over actuated aircraft aimed to determine the surface gearing matrix weights in different operative conditions to minimize the total power consumption. First, the non-linear model of the control forces and moments is derived for an over actuated aircraft. Then, two different optimization problems are introduced: the first to compute the trim equilibrium for any flight condition to minimize power consumption by the aircraft; the second to minimize the surface deflections required to produce desired control forces/moments starting from the trim point previously found. Finally, the optimized solution is subjected to engineering judgement to neglect the ineffective surfaces that do not provide a significant contribution to the required maneuver.
Bugliari Armenio, LucaCortigiani, NicolaVita, GaspareCadeddu, Davide
Unmanned Aerial Vehicles (UAVs), particularly Vertical Take-Off and Landing (VTOL) aircraft such as quad-rotors and helicopters, have gained attention for diverse applications in military and civilian domains. However, to increase applications, reducing their power consumption and their restricted payload capacity. This paper describes a method to enhance the thrust capabilities of typical shrouded rotors through a novel rotor design. Beginning with an airfoil with a high lift-to-drag ratio. Blade element momentum theory (BEMT) is used to optimize the rotor's chord and twist distributions systematically along with precise induced velocity prediction in shrouded rotors. Furthermore, a validation process requires rotor manufacturing and experimentation. BEMT harmonizes momentum and blade element theories, offering a comprehensive framework for rotor behavior modeling, especially in hovering conditions. First, second, and third degrees functions are used to express both the chord and twist distributions along the rotor radius from where the best rotor design is obtained, for this, an experimental validation is employed. The experimental tests demonstrate improved performance, especially when the rotor designed using the higher degree functions is employed. The proposed approach provides a comprehensive approach to shrouded rotor design, offering advancements.
Dayhoum, AbdallahMartinuzzi, RobertRamirez-Serrano, Alejandro
The paper presents a novel strategy for minimum energy consumption in automatic conversion control of tiltrotor eVTOL aircraft, exemplified by the Aston Martin Volante Vision model. We introduce a tilt schedule methodology that strategically balances conversion and reconversion performance with climb, descent, and cruise phases to minimize overall energy expenditure. Our approach accounts for critical factors such as blade loading, operation handling qualities, and passenger ride comfort within a predefined conversion corridor. The optimized trajectories approximate the minimum energy pathway, essential for operational efficiency in urban air mobility. Analytical results demonstrate that our proposed conversion and reconversion phase profiles significantly reduce energy consumption, contributing to the sustainability of tiltrotor flight operations. This research not only enhances understanding of tiltrotor dynamics but also serves as a pivotal step toward achieving globally optimized energy usage, marking a significant advancement in autonomous flight technology for advanced air mobility systems.
Kang, NamukWhidborne, JamesLu, Linghai
ABSTRACT
Aires, JeremyWithrow-Maser, ShannahRuan,  AllenMalpica, CarlosSchuet,  Stefan
Abstract In today’s era, due to increasing energy demands, it is necessary to make vehicles lightweight without affecting their strength. In order to achieve this, the subassemblies of the automobile should be optimized. Optimizing the product not only saves energy consumption but also reduces the material required for manufacturing and increases the overall performance of the product. Taking the same as the base, this article focuses on optimization of a straight bevel gear pair used in automotive differential and performing finite element analysis (FEA) to validate its results. FEA is carried out on the optimized bevel gear to check its durability, and topology optimization is performed on the optimized gear to reduce the mass. Finally, the optimized gear is checked for fatigue. For design optimization, nonlinear multi-objective problem is formulated with a number of teeth and modules as the design parameters. Nondominated Sorting Genetic Algorithm (NSGA)-II algorithm is chosen for optimization. Also multi-body dynamics is performed on the design optimized and topology optimized gear, and the results are compared to understand the effects of weight reduction in the gear with respect to (wrt) vibrations. Design Optimization is accomplished using MATLAB 2018 optimization toolbox, finite element analysis and topology using ANSYS V16.0, and multi-body dynamics using MSC ADAMS 2016.
Kadge, Rushiraj
Mathematical Programming for Optimization of Integrated Modular Avionics2021-01-00093/2/2021
Every state-of-art aircraft has a complex distributed systems of avionics Line Replaceable Units/Modules (LRUs/LRMs), networked by several Data buses. These LRUs are becoming more complex because of an increasing number of new functions need to be integrated into avionics architecture. Moreover, the complexity of the overall avionics architecture and its impact on cable length, weight, power consumption, reliability and maintainability of avionics systems encouraged manufacturers to incorporate efficient avionics architectures in their aircraft design process. The evolution of avionics data buses and architectures have moved from distributed analog and federated architecture to digital integrated modular avionics (IMA). IMA architecture allows suppliers to develop their own LRUs/LRMs capable of specific features that can then be offered to Original Equipment Manufacturers (OEMs) as Commercial-Off-The-Shelf (COTS) products. In the meantime, the aerospace industry has been investigating new solutions to develop smaller, lighter, and more capable LRUs/LRMs to be integrated into avionics architecture. However, manual design cannot concurrently fulfil the complexity and interconnectivity of system requirements and optimality. Thus, developing computer-aided design (CAD), Model Based System Engineering (MBSE) tools and mathematical modelling for optimization of IMA architecture has become an active research area in avionics systems integration. In this paper, a general method and tool are developed for optimization of avionics architecture and improving its operational capability. The tool has three main parts including a database of avionics LRUs, mathematical modelling of the architecture and optimization algorithms. Finally, the tool provides a semi-automatic optimization of avionics architecture which helps avionics system architects to investigate and evaluate various architectures in the early stage of design from an LRU perspective. It can also be used to upgrade a legacy avionics architecture.
Radaei, Mohammad
Eco-profiling of Bio-epoxies via Life cycle AssessmentSAE-PP-002312/3/2021
Epoxies, synthesized from bisphenol-A (BPA) and epichlorohydrin (ECH), are predominantly used as coatings, adhesives, and as matrix material in fiber-reinforced composites for body-in-white (BiW) applications in the automotive sector. However, given the production of conventional epoxies from non-renewable petroleum resource and toxicity of BPA, several initiatives have been undertaken by researchers to synthesize alternative epoxies from various bio-sources that are free of BPA and exhibit similar mechanical performance. As a result, such bio-sourced epoxies are almost immediately termed as “eco-friendly”, despite the lack of comprehensive evaluation of their ecological performance that takes into account enhanced natural resource usage and associated impacts accompanying such epoxies. Hence, this work aims at addressing this gap by evaluating the environmental impacts of such bio-sourced epoxies via cradle-to-gate life cycle assessment to determine the genuine credentials of their ecofriendliness. Epoxies synthesized from three different bio-sources – namely, bark extractives, lignin, and triglyceride – were chosen, to evaluate their ecological performance. ReCiPe midpoint and endpoint methods were used to evaluate these epoxies in accordance with ISO 14040 and 14044 standards. Among the three bio-epoxies, lignin-based epoxy exhibits poor eco-performance mainly due to the use of large amount of chemicals during extraction of lignin, involving delignification and valorization. On the contrary, bio-epoxy synthesized from triglycerides were found to be eco-friendly compared to other bio-epoxies. All bio-epoxies are observed to contribute significantly to toxicity-related categories, mainly due to higher electricity consumption during both epoxy synthesis and manufacturing processes. Overall, this work sheds light on various avenues for synthesizing truly sustainable epoxies that exhibit mechanical performance comparable to their conventional counterparts.
Anthony, LindsayJackson, Alyssa
Battery power and energy density are important parameters for emerging concepts for more / all-electric vehicles. Electric propulsion and power system performance is also important. To better understand how electric propulsion and power systems component performance influences overall vehicle design, a sensitivity assessment was performed noting changes in vehicle gross weight and energy usage. Updated versions of the Revolutionary Vertical lift Technology (RVLT) Project vertical takeoff and landing (VTOL) urban air mobility (UAM) reference vehicles and missions were used. NASA electric vehicle studies are discussed which were used to help select the range of electric propulsion and power system performance parameters used in this assessment. Thermal management systems (TMS) considerations are also important; new and innovative power management and distribution (PMAD) systems can reduce electric system weight and losses, reducing thermal management constraints often imposed by electric systems modest maximum use temperatures. Vehicles with higher disk loadings require higher power levels per unit weight for VTOL operations, which make them more sensitive to electric system weights and efficiencies. Battery, all-electric vehicles show different sensitivities to component performance than turboelectric or hybrids systems. Battery, all-electric propulsion systems may increase vehicle weight and size, but still results in lower mission energy usage than their hydrocarbon-fueled versions. Significant vehicle weight growth to electric propulsion and power system power-to-weight reductions also occurs at different levels among the various concepts. From these results, one can more readily identify required component performance levels, potential component choices, or research and development paths.
Snyder, Christopher
A novel stretchable material, when used in light-emitting capacitor devices, enables highly visible illumination at low operating voltages, and it is also resilient to damage due to its self-healing properties.
Automobile manufactures need to adopt new technologies to meet global CO2 (carbon dioxide) emission regulations and better fuel efficiency demands from customers. Also, the production cost should be as low as possible for an affordable vehicle. Therefore, it is advantageous for OEMs to develop fuel efficient technologies which can be controlled by software without additional hardware costs. The coasting control is a fuel efficiency improvement technology that can be implemented by the change of vehicle software only. The coasting control is a technology that reduces the driving resistance (Deceleration) when the driver releases the gas pedal. This technology leads to reducing the energy required for the vehicle to drive and results in improving the real-world fuel economy. In an internal combustion engine (ICE) vehicle, the coasting state is achieved by changing the gear to neutral, and the effect has been discussed and clarified by many previous studies. On the other hand, in the coasting state of a hybrid vehicle, the regenerative energy to the motor is reduced while the driver releases the gas pedal. The coasting control of a hybrid vehicle tends to be perceived as deteriorating the fuel efficiency because the regenerative energy decreases. In this study, relations of the vehicle deceleration and the fuel economy (vehicle energy consumption) of a hybrid vehicle were studied quantitatively. In addition, we confirmed that the coasting technology was effective to improve fuel economy (reducing CO2) based on the real-world big data.
Yamaguchi, Tomoya
Renewable fuels have an important role to create sustainable energy systems. In this paper the focus is on biodiesel, which is produced from vegetable oils or animal fats. Today biodiesel is mostly used as a drop-in fuel, mixed into conventional diesel fuels to reduce their environmental impact. Low quality drop-in fuel can lead to deposits throughout the fuel systems of heavy duty vehicles. In a previous study fuel filters from the field were collected and analyzed with the objective to determine the main components responsible for fuel filter plugging. The identified compounds were constituents of soft particles. In the current study, the focus was on metal carboxylates since these have been found to be one of the components of the soft particles and associated with other engine malfunctions as well. Hence the measurement of metal carboxylates in the fuel is important for future studies regarding the fuel’s effect on engines. The first aim of this study was to create synthetic soft particles from biodiesel. Accelerated aging of fuels with different contaminations such as engine oil and calcium oxide were used to create the synthetic soft particles. The precipitates were collected and analyzed with different techniques such as FTIR and GC-MS, to identify the main components which were then compared with the results of the previous study. Following this, specific attention was given to calcium methyl azelate as it was shown to be found in field fuel filters. A method using GC-MS was developed to be able to estimate the amount of soft particles by measuring calcium methyl azelate. The specified method proved to be adequate for future studies to evaluate the filtration efficiency of different filter materials against soft particles.
Csontos, BotondSwarga, ShriharshaBernemyr, HannaPach, MayteHittig, Henrik
A New Simulation Approach of Estimating the Real-World Vehicle Performance2020-01-03704/14/2020
Due to the variability of real traffic conditions for vehicle testing, real-world vehicle performance estimation using simulation method become vital. Especially for heavy duty vehicles (e.g. 40 t trucks), which are used for international freight transport, real-world tests are difficult, complex and expensive. Vehicle simulations use mathematical methods or commercial software, which take given driving cycles as inputs. However, the road situations in real driving are different from the driving cycles, whose speed profiles are obtained under specific conditions. In this paper, a real-world vehicle performance estimation method using simulation was proposed, also it took traffic and real road situations into consideration, which made it possible to investigate the performance of vehicles operating on any roads and traffic conditions. The proposed approach is applicable to all kind of road vehicles, e.g. trucks, buses, etc. In the method, the real-road network includes road elevation. The traffic conditions and vehicles parameters were the inputs for traffic simulation. Based on the outputs (speed profiles and elevations) of target vehicles in the traffic simulation, then the real-world performance of the vehicle was achieved by vehicle simulation under the given traffic conditions. The fuel consumption of the vehicle calculated using this method was 34.00 L/100 km under free traffic flow conditions over highway route.
Gao, JianbingChen, HaiboChen, JunyanDave, Kaushali
Data-Driven Framework for Fuel Efficiency Improvement in Extended Range Electric Vehicle Used in Package Delivery Applications2020-01-05894/14/2020
Extended range electric vehicles (EREVs) are a potential solution for fossil fuel usage mitigation and on-road emissions reduction. The use of EREVs can be shown to yield significant fuel economy improvements when proper energy management strategies (EMSs) are employed. However, many in-use EREVs achieve only moderate fuel reduction compared to conventional vehicles due to the fact that their EMS is far from optimal. This paper focuses on in-use rule-based EMSs to improve the fuel efficiency of EREV last-mile delivery vehicles equipped with two-way Vehicle-to-Could (V2C) connectivity. The method uses previous vehicle data collected on actual delivery routes and machine learning methods to improve the fuel economy of future routes. The paper first introduces the main challenges of the project, such as inherent uncertainty in human driver behavior and in the roadway environment. Then, the framework of our practical physics-model guided data-driven approach is introduced. For vehicles with small amounts of prior data, a Bayesian method is used to adjust a control parameter in the EMS offline for each vehicle with introduced prior information derived from large numbers of trips from other vehicles in the fleet. For vehicles with many delivery trips, a reinforcement learning algorithm is used to optimize the parameter in real-time without requiring future information of the trip. Although our data-driven framework cannot achieve a globally optimal solution with respect to the fuel efficiency, it provides a systematic and immediate solution for in-use EREVs used for package delivery with a very low computation cost and no change of vehicle hardware. Also, this framework is ready to be extended for further fuel economy improvements if more information is available from advanced transportation infrastructures like Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) connectivity.
Wang, PengyueNorthrop, William
A Connected Controls and Optimization System for Vehicle Dynamics and Powertrain Operation on a Light-Duty Plug-In Multi-Mode Hybrid Electric Vehicle2020-01-05914/14/2020
This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization. Tools at the powertrain level include PHEV mode blending, predictive drive-unit state control, and non-linear model predictive control powertrain power split management. These tools were developed with the capability of being implemented in a real-time vehicle control system. As a result, many of the developed technologies have been demonstrated in real-time using a fleet of four instrumented Chevrolet Volts which are equipped with on-board sensors, rapid prototyping embedded controllers, and V2X communication devices. This paper provides an overview of each tool developed, its implementation, energy reduction in isolation, and the net energy reduction of various tool combinations. A breakdown of the energy savings and range extension possible for the connected vehicle control and optimization tool set is provided which shows energy reduction benefits approaching 20% and range extension upwards of 8%, dependent on the driving and traffic scenarios and initial vehicle state of charge.
Oncken, JosephOrlando, JoshuaBhat, Pradeep K.Narodzonek, BrandonMorgan, ChristopherRobinette, DarrellChen, BoNaber, Jeffrey
Design of a Mild Hybrid Electric Vehicle with CAVs Capability for the MaaS Market2020-01-14374/14/2020
There is significant potential for connected and autonomous vehicles to impact vehicle efficiency, fuel economy, and emissions, especially for hybrid-electric vehicles. These improvements could have large-scale impact on oil consumption and air-quality if deployed in large Mobility-as-a-Service or ride-sharing fleets. As part of the US Department of Energy's current Advanced Vehicle Technology Competition (AVCT), EcoCAR: The Mobility Challenge, Mississippi State University’s EcoCAR Team is redesigning and doing the development work necessary to convert a conventional gasoline spark-ignited 2019 Chevy Blazer into a hybrid-electric vehicle with SAE Level 2 autonomy. The target consumer segments for this effort are the Mobility-as-a-Service fleet owners, operators and riders. To accomplish this conversion, the MSU team is implementing a P4 mild hybridization strategy that is expected to result in a 30% increase in fuel economy over the stock Blazer. MATLAB models of the vehicle system shows the potential for additional improvement with the use of connected and autonomous features in the vehicle. This paper presents the design rationale for selection of the P4 strategy, vehicle modeling, and fuel economy simulation results completed during Year 1 of the competition. A detailed discussion of further improvements arising from incorporating connected and autonomous technology strategies, focusing on longitudinal control methods is also presented.
Taoudi, AmineHaque, Moinul ShahidulStrzelec, AndreaFollett, Randolph
Evaluation of Methods for Identification of Driving Styles and Simulation-Based Analysis of their Influence on Energy Consumption on the Example of a Hybrid Drive Train2020-01-04434/14/2020
Due to current progresses in the field of driver assistance systems and the continuously growing electrification of vehicle drive trains, the evaluation of driver behavior has become an important part in the development process of modern cars. Findings from driver analyses are used for the creation of individual profiles, which can be permanently adapted due to ongoing data processing. A benefit of data-based dynamic control systems lies in the possibility to individually configure the vehicle behavior for a specific driver, which can contribute to increasing customer acceptance and satisfaction. In this way, an optimization of the control behavior between driver and vehicle and the resulting mutual system learning and -adjustment hold great potential for improvements in driving behavior, safety and energy consumption. The submitted paper deals with the analysis of different methods and measurement systems for the identification and classification of driver profiles as well as with their potential to optimize both vehicle driving behavior and energy consumption on the example of a hybrid drive train. A literature research results in a number of different approaches of evaluation, which are analyzed, linked and adapted in the publication. As a result, an evaluation of the connection between different methods of driver profile determination is given. Data collection and interviews have been performed during twenty test drives on a defined route profile with different measurement systems and methods. The acquired data form the basis for a comparison and an analysis of a comprehensive driving style classification. Subsequently, a framework for computer-aided investigations of the influences of driver behavior on the control of drive trains is established by use of an existed simulation model of a hybrid drive train. Finally, a driver model is implemented based on the learnings out of analyzing the measurements and surveys. The evaluation of the measurement campaigns delivers detailed information about vehicle longitudinal acceleration behavior in different driving scenarios. This information is used to classify the individual driving styles into the types calm, normal and aggressive. This driving style-related information can be integrated into the control strategy of a hybrid power train to support operation strategy optimization regarding both driver satisfaction and reduction of energy-, respectively fuel consumption.
Domijanic, MarkoHirz, MarioPucher, Gregor
The assessment of fuel economy of new vehicles is typically based on regulatory driving cycles, measured in an emissions lab. Although the regulations built around these standardized cycles have strongly contributed to improved fuel efficiency, they are unable to cover the envelope of operating and environmental conditions the vehicle will be subject to when driving in the “real-world”. This discrepancy becomes even more dramatic with the introduction of Connectivity and Automation, which allows for information on future route and traffic conditions to be available to the vehicle and powertrain control system. Furthermore, the huge variability of external conditions, such as vehicle load or driver behavior, can significantly affect the fuel economy on a given route. Such variability poses significant challenges when attempting to compare the performance and fuel economy of different powertrain technologies, vehicle dynamics and powertrain control methods. This paper describes a methodology to benchmark the fuel consumption reduction potential of a Level 1 Connected and Automated Vehicle (CAV) with advanced cylinder deactivation and 48V mild hybridization, in the presence of variability induced by route characteristics, traffic and driver behavior. An Intelligent Driving system utilizes advanced route information available from the navigation system and GPS, as well as a V2X communication module to determine the optimal vehicle velocity and battery state of charge profiles that aim at minimizing fuel consumption along a driver-selected route without sacrificing travel time. Since the presence of traffic and the behavior of different drivers strongly affects the fuel consumption and vehicle travel time, a Monte Carlo simulation is conducted to determine the statistical distribution of the results when introducing variability in the inputs. Fuel efficiency benefits are dependent on the route characteristics, traffic conditions and driver behavior. For the route evaluated in this paper, numerical results show as much as 15% to 19% reduction in fuel consumption, compared to a mild hybrid baseline vehicle without cylinder deactivation and CAV features.
Gupta, ShobhitRajakumar Deshpande, ShreshtaTufano, DanielaCanova, MarcelloRizzoni, GiorgioAggoune, KarimOlin, PeteKirwan, John
Onboard Ethanol-Gasoline Separation System for Octane-on-Demand Vehicle2020-01-03504/14/2020
Bioethanol is being used as an alternative fuel throughout the world based on considerations of reduction of CO2 emissions and sustainability. It is widely known that ethanol has an advantage of high anti-knock quality. In order to use the ethanol in ethanol-blended gasoline to control knocking, the research discussed in this paper sought to develop a fuel separation system that would separate ethanol-blended gasoline into a high-octane-number fuel (high-ethanol-concentration fuel) and a low-octane-number fuel (low-ethanol-concentration fuel) in the vehicle. The research developed a small fuel separation system, and employed a layout in which the system was fitted in the fuel tank based on considerations of reducing the effect on cabin space and maintaining safety in the event of a collision. The total volume of the components fitted in the fuel tank is 6.6 liters. It was demonstrated that the onboard fuel separation system possessed sufficient control performance in practical use in actual driving environments. In addition, measurements of fuel separation speed in LA4 driving cycle showed that the system was able to separate the fuel at a speed higher than the speed of consumption of high-octane-number fuel necessary for the engine. The ethanol concentration of the separated fuel was approximately 90%. This figure represents a sufficient octane number to control knocking in high-compression-ratio engines under high-load conditions. The power consumption of the fuel separation system was approximately 350W. Taking the increase in engine fuel efficiency into consideration, it is possible to expect an increase of approximately 15% in fuel efficiency for the vehicle as a whole.
Chishima, HiroshiTsutsumi, DaikoKitamura, Toru
Experimental Comparison of Biogas and Natural Gas as Vibration, Emission, and Performance in a Diesel Engine Converted to a Dual Fuel04-13-01-00041/27/2020
Biogas, natural gas, and their usage in the diesel engine will be important in the future. For this purpose, the effects of biogas on engine performance, emissions, and engine vibrations of the diesel engines with dual fuel system are investigated in comparison with natural gas. It has also been included in evaluating the deformation of the engine oil due to hydrogen sulfide combustion reactions. In this study, a constant speed, naturally aspirated, and direct injection of the diesel engine with volume of 2.5 liter has been converted into a dual fuel system that can be included in gas fuels. In order to determine engine performance, exhaust emissions, engine vibration, and noise, the tests were carried out at load stages of 5, 10, 15, 20, and 25 kW and at a constant speed of 1500 rpm. The experiments were first performed in a mono operation condition of the conventional diesel fuel. Subsequently, tests were repeated under natural gas/diesel and biogas/diesel dual fuel operation conditions, respectively. As a result of the tests, it was observed that the vibration amount decreased and the noise emission was reduced by 3.5% in all stages where biogas was used as the main fuel. Depending on fuel or operation system change, no significant change was observed in cylinder block, cylinder heat, exhaust, and intake manifold temperature. The exhaust gas temperature is measured to be lower because of the carbon dioxide (CO2) content in the biogas. When approaching from the point view of engine emissions, it was determined that the carbon monoxide (CO) emission increased at all engine loads while a decrease of 50% in oxides of nitrogen (NOx) emission occurred.
Aytav, EmreKoçar, GünnurTeksan, Abdulhalik Emre
Real-time Long Horizon Model Predictive Control of a Plug-in Hybrid Vehicle Power-Split Utilizing Trip Preview2019-01-234112/19/2019
Given a forecast of speed and load demands during a trip, a hybrid powertrain power-split Trajectory Optimization Problem (TOP) can be solved to optimize fuel consumption. This can be done on desktop to set performance benchmarks; however, it has been believed that the TOP could not be solved in real-time and is not a realizable controller. As such, several approximations of the TOP have been made in the interest of obtaining a real-time near-optimal controller, for example, Equivalent Consumption Minimization Strategies (ECMS) and their adaptive counterparts. These strategies decide on the power-split by, at each sampled time instant, minimizing a Horizon-0 (without predicting forward in time) composite function of fuel consumption and equivalent battery energy. The fuel economy that results from these strategies is highly sensitive to the calibration of the associated equivalence factor, and furthermore, must be chosen differently for different drive cycles. This paper presents a strategy for solving the TOP in real-time, i.e., as an Economic Model Predictive Controller (MPC) with horizon length sufficiently long to cover the entire trip. Unlike ECMS, this MPC is arguably calibration-free. Simulation results demonstrate the performance and robustness of the MPC by comparing the fuel consumption improvements to a rule-based Charge Deplete Charge Sustain (CDCS) strategy under both a perfect forecast assumption and a simple forecasting scheme using driving patterns in the California Household Travel Survey.
Huang, MikeZhang, ShengqiShibaike, Yushi
Fuel Cell Vehicles: An Opportunity for China's Greenhouse Gas Reduction2019-01-226312/19/2019
Fuel cell vehicle and battery electric vehicle are two environmentally benign vehicle technology types possibly meeting the zero-emission regulations in the future. The premise is they can achieve parity with conventional vehicle both environmentally and economically. Besides, it is necessary to distinguish which technology is more suitable in China's current and future context. This paper compares their cost-effectiveness for reducing greenhouse gas emissions, examining the life-cycle greenhouse gas emissions of conventional gasoline vehicle, battery electric vehicle and fuel cell vehicle in China's energy context under three different scenarios. The results indicate that under the 500km drive range, fuel cell vehicles are less competitive than battery electric vehicles currently. Fuel cell vehicles generate much more greenhouse gas emissions than battery vehicles and conventional gasoline vehicles. While with the optimization of energy context, fuel cell vehicles can gain competitiveness with battery electric vehicles in terms of greenhouse gas emissions, and with mass production as well as fuel cell system cost reduction, fuel cell vehicles can realize a better cost-effectiveness. Based on this analysis, it is recommended that the energy context should be optimized before deploying the fuel cell vehicles on a large scale in China. Technology enhancement both in hydrogen production and fuel cell, as well as manufacture optimization for fuel cell systems are equally essential in improving its cost-effectiveness.
Mu, ZhexuanHao, HanLiu, ZongweiZhao, Fuquan
Modeling the Impact of Alternative Fuel Properties on Light Vehicle Engine Performance and Greenhouse Gases Emissions2019-01-230812/19/2019
The present-day transport sector needs sustainable energy solutions. Substitution of fossil-fuels with fuels produced from biomass is one of the most relevant solutions for the sector. Nevertheless, bringing biofuels into the market is associated with many challenges that policymakers, feedstock suppliers, fuel producers, and engine manufacturers need to overcome. The main objective of this research is an investigation of the impact of alternative fuel properties on light vehicle engine performance and greenhouse gases (GHG). The purpose of the present study is to provide decision-makers with tools that will accelerate the implementation of biofuels into the market. As a result, two models were developed, that represent the impact of fuel properties on engine performance in a uniform and reliable way but also with very high accuracy (coefficients of determination over 0.95) and from the end-user point of view. The inputs of the model are represented by fuel properties, whereas output by fuel consumption (FC). The parameters are represented as percentage changes relative to standard fossil fuel, which is gasoline for spark ignition (SI) engines and diesel for compression ignition (CI) engines. The methodology is based on data-driven black-box modeling (input-output relation). The multilinear regression was performed using the data from driving cycles such as the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) and New European Driving Conditions (NEDC). The FC of SI engines proved to be dependent on mass-based Net Calorific Value (NCV), Research Octane Number (RON), oxygen content and density. However, CI engines performance is affected by NCV, density and Cetane Number (CN). The models were additionally subject to quantitative analysis, where input parameters in both models turned out to be statistically significant (p-value below 5%). Additionally, the validation stage consisted of residual analysis confirmed the accuracy of both models. The GHG part estimates the change of carbon dioxide emissions based on fuel consumption, which represents the tailpipe emissions.
Kroyan, YuriWojcieszyk, MichalLarmi, MarttiKaario, OssiZenger, Kai
Experimental Investigation on the Performance and Emission Characteristics of a Direct Injection Diesel Engine Using Blends of Ethyl Ester of Jatropha Oil and Ethanol2019-28-237811/21/2019
The need of Diesel as fuel has greatly pressurized the now scarcely available natural resources and is likely to become a luxury for the future generations. This paper aims at finding an alternate for diesel that can hopefully reduce the pressure on its existing demand. This paper presents a comparative study on use of different blends of Jatropha Oil (J) and Ethanol (E) as fuel in a diesel engine to observe its performance and emission characteristics. The findings are later compared with corresponding values of neat Diesel as fuel. Since Jatropha oil is more viscous and has polyunsaturated characteristics in its natural form, its ethyl ester was produced by transesterification process and later blended with Ethanol in different proportions like 90% J 10%E, 80J-20E, 70J-30E and 60J-40E. A Kirloskar make single cylinder Diesel engine coupled with Eddy Current dynamometer was used at a constant speed of 1500 RPM as a test bed to measure the performance characteristics of the blends at various loads of 0, 3, 6, 9 kg. A Crypton make five gas analyzer was used to analyze the Emission characteristics. A specific combination of Jatropha oil and Ethanol showed improvements in Volumetric efficiency, Mechanical efficiency and Thermal efficiency when compared to neat diesel. Also, the same blend showed less emission of NOx and CO compared to neat diesel. The findings and the recommended blend were discussed in detail in this paper. It could be concluded that this blend can be used as an alternate fuel in Diesel engines. Further, Parametric study of the engine and the investigation on effects of oil deposits in the engine may help to improve its performance.
TN, Varun RajJayaprakash, VijaykrishnaCharles, Terrance
Analysis of Accelerator Hardware for Autonomous Vehicles and Data Centers2019-01-261510/22/2019
The development of Autonomous Vehicles (AV) has become a popular subject in academia and industry. Companies and cities are quickly realizing the opportunities that AVs can generate from Mobility as a Service to traffic safety. The challenges for the infrastructure to incorporate AVs as a viable transportation source are immense, from an outdated infrastructure to radical Smart-City designs. Historically, the transportation infrastructure has faced challenges from underfunding, economics, and much needed improvements. With the current infrastructure unable to support many of the services required by a fully connected network, a transformation will be necessary to meet growing mobility needs. The role of accelerating technology in data centers are key for production operations among industry leaders such as Amazon and Microsoft for real-time processing. The same accelerating technology that has successfully impacted data centers will play the same role in much smaller micro data centers (mDC) for Smart-City design in the transportation infrastructure. These mDCs and Edge computing sites will be tasked with the latency, tasking caching and offloading (TCO), and processing of millions of connected vehicles simultaneously. With the recent upgrade of 5G from 4G wireless connectivity will invariably provide lower latency to Edge computing devices used in real-time applications. This paper provides an analysis of accelerator technology for real-time processing in the transportation infrastructure. Accelerator hardware such as FPGAs, GPUs, and ACISs will be highlighted from current research that support real-time capabilities. As the popularity of AVs and a connected network continues to grow, the role of accelerator technology will enable large scale real-time processing in AVs and the transportation infrastructure.
Brown, Kyle W.
Eco-Driving Strategies for Different Powertrain Types and Scenarios2019-01-260810/22/2019
Connected automated vehicles (CAVs) are quickly becoming a reality, and their potential ability to communicate with each other and the infrastructure around them has big potential impacts on future mobility systems. Perhaps one of the most important impacts could be on network wide energy consumption. A lot of research has already been performed on the topic of eco-driving and the potential fuel and energy consumption benefits for CAVs. However, most of the efforts to date have been based on simulation studies only, and have only considered conventional vehicle powertrains. In this study, experimental data is presented for the potential eco-driving benefits of two specific intersection approach scenarios, for four different powertrain types. The two intersection approach scenarios considered in this study include an approach to a red light where coming to a complete stop is avoidable (short red light) and one where a complete stop is determined necessary (long red light) thanks to advance information from vehicle-to-infrastructure communication (V2I). The four powertrain types tested in this study include an advanced conventional vehicle, a conventional vehicle with idle stop-start capability, a hybrid electric vehicle (HEV), and a battery electric vehicle (BEV). The experimental results are compared to simulation results for the same intersection approach scenarios and eco-driving strategies, and show the difference in benefits for different powertrain types. Based on the eco-approach strategies for these two scenarios, a maximum fuel/energy consumption benefit of almost 8% was observed for the intersection with a short red light and almost 20% for the intersection with a long red light, in both cases by the HEV.
Iliev, SimeonRask, EricStutenberg, KevinDuoba, Michael
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