Browse Topic: Optimization

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Quantitative Analysis of a Hybrid Electric HMMWV for Fuel Economy Improvement2024-01-335604/23/2025
ABSTRACT This paper presents a quantitative analysis and comparison of fuel economy and performance of a series hybrid electric HMMWV (High Mobility Multi-purpose Wheeled Vehicle) military vehicle with a conventional HMMWV of equivalent size. Hybrid vehicle powertrains show improved fuel economy gains due to optimized engine operation and regenerative braking. In this paper, a methodology is presented by which the fuel economy gains due to optimized engine are isolated from the fuel economy gains due to regenerative braking. Validated vehicle models as well as data collected on test tracks are used in the quantitative analysis. The regenerative braking of the hybrid HMMWV is analyzed in terms of efficiency from the kinetic energy at the wheels to the portion of regenerative power which is retrievable by the battery. The engine operation of both the series hybrid and conventional HMMWV are analyzed using a 2-D bin analysis methodology. Finally, the vehicle model is used to make
Nedungadi, Ashok, Masrur, Abul, Khalil, Gus
Fatigue Analysis of Motorcycle Rear Swing Arm on Different Road Surfaces2024-32-004604/18/2025
The rear swing arm, a crucial motorcycle component, connects the frame and wheel, absorbing the vehicle’s load and various road impacts. Over time, these forces can damage the swing arm, highlighting the need for robust design to ensure safety. Identifying potential vulnerabilities through simulation reduces the risk of failure during the design phase. This study performs a detailed fatigue analysis of the swing arm across different road conditions. Data for this research were collected from real-vehicle experiments and simulation analyses, ensuring accuracy by comparing against actual performance. Following CNS 15819-5 standards, road surfaces such as poorly maintained, bumpy, and uneven roads were tested. Using Motion View, a comprehensive multi-body dynamic model was created for thorough fatigue analysis. The results identified the most stress-prone areas on the swing arm, with maximum stress recorded at 109.6N on poorly maintained roads, 218.3N on bumpy surfaces, and 104.8N on
Chiou, Yi-Hau, Hwang, Hsiu-Ying, Huang, Liang-Yu
Impacts of Pulsating Flow on Topologically Optimized Porous Reactors in Convection-Diffusion-Reaction Systems2024-32-007004/18/2025
Topology optimization (TO) in electrochemical systems has recently attracted many researchers. Previous studies suggested minimal performance differences between 2D and 3D designs, indicating that 2D models suffice to enhance performance, especially in unidirectional flow scenarios. A later study found that the concentration distribution in an optimized 2D flow system differed from that in a unidirectional flow system. We posited that pulsating flow could further enhance the performance of such systems. First, we initiated TO for a diffusion-reaction system in a steady state. The optimized structure obtained from this process served as the foundation for subsequent investigations involving a pulsating flow source in convection-diffusion-reaction systems. We introduced two different systems with distinct flow natures: one characterized by a flow nature of 1D and the other by a flow nature of 2D. The results demonstrated that the optimized structure with a heterogeneous distribution
Long, Mengly, Alizadeh, Mehrzad, Sun, Pengfei, Charoen-amornkitt, Patcharawat, Suzuki, Takahiro, Tsushima, Shohji
Optimization of the Numerical Spray Modeling for Polyoxymethylene Dimethyl Ethers for Combustion Prediction in CONVERGE2025-01-502604/03/2025
Different approaches are undertaken to mitigate the impact of the transport sector on climate change. Alongside electrifying powertrains, sustainable e-fuels such as polyoxymethylene dimethyl ethers (OME) are considered a promising bridging technology for different applications. However, this requires that the engines are optimized for the new fuels. Accordingly, this study aims to optimize the numerical spray modeling of OME in CONVERGE. Based on the KH–RT break-up model, the spray simulations of three different commercial injectors for heavy-duty applications are analyzed regarding the predictability of the liquid and gaseous penetration lengths and the total simulation time. A sensitivity analysis is conducted for the turbulence model, mesh size, and spray parameters prior to optimizing the spray model and validating it with experimental results. While each parameter individually influences the different phases of the injection event, the sensitivity analysis reveals that the break
Zepf, Andreas, Härtl, Martin, Jaensch, Malte
A review of warm forming for steels: History, Methodology and Emerging trends2025-01-881404/01/2025
Many manufacturing techniques and process modifications have been implemented over the years to improve the formability of sheet metals. Warm forming of sheet metals is one such established method. However, it is more commonly and successfully applied to aluminum grades. The reevaluation of less-used metal forming technologies, such as warm forming and sheet hydroforming for steel, is a response to the challenges posed by competitive processes like large castings and the geometry requirements of new BEV parts. By understanding the effects of elevated temperatures (below recrystallization temperatures) on different steel grades and the impact of various heating methodologies, the industry can adapt and optimize these proven techniques for modern applications. This paper is a comprehensive summary of the effect of elevated temperatures on various grades of steel. Different heating techniques, their cycle times and effects on final forming feasibility is contrasted. The effect of
Kella, Caroline, Wormald, Tom, Gatts, Joshua
Research and Simulation Implementation of Self-Driving Vehicle Trajectory Optimization in Networked Intersection Environment2025-01-719402/21/2025
Nowadays, the rapidly developing Connected and Autonomous Vehicle (CAV) provides a new mode of intersection vehicle cooperative control, which can optimize vehicle trajectories and signal phases in real time and reduce intersection delays through the advantages of vehicle-road cooperative information interaction and the high controllability of CAV. In this paper, the intersection of Jintong West Road and Guanghua Road in Beijing is taken as the research object, and the vehicle trajectory constraints, acceleration constraints, speed constraints, safe driving constraints, signal switch constraints and traffic signal control constraints are set up with the minimization of traffic delay as the objective function. The DQN deep reinforcement learning network is constructed based on vehicle states, vehicle actions, reward functions, and update rules, and starts learning and updating to generate the target network. Then, SUMO software is used to simulate and test and compare the trajectory
Xu, Yuting, Zhang, Yong, Wu, Xianyu
Intelligent Courier Delivery Scheduling Based on XGBoost Feature Selection and Reinforcement Learning: A Case Study Using Chongqing Cainiao Express Data2025-01-717602/21/2025
This study tackles the issue of order delays in logistics using XGBoost for feature analysis and reinforcement learning for intelligent courier scheduling. Pickup order data from May 1 to October 31, 2023, in Chongqing is analyzed using spatio-temporal statistical methods. Key findings include that order placement peaks at 9:00 a.m., delays peak at 10:00 a.m., and the delay rate is 8.6%. A significant imbalance exists between the regional daily average of dispatchable couriers and order volumes.XGBoost is employed to predict order delays, revealing that pickup location is the most influential factor (27%), followed by courier pickup location (22%). These factors and their relationships are identified as key drivers of delays.To address these issues, a reinforcement learning-based courier scheduling optimization model is developed. The model defines courier location, current time, and pending orders as state variables and adopts an epsilon-greedy strategy for action selection
Wang, Manjun, Yu, Xinlian
SAE TOMORROW TODAY: Optimizing Energy Data for the Cold Supply Chain1350102/09/2025
The growing complexity of fleet electrification has highlighted the importance of understanding how energy is used and where you can reduce waste. To optimize energy intensity at industrial facilities, one company is leveraging integrated data and AI-powered intelligence to reduce both cost and fleet-related emissions, particularly when it comes to cold storage supply chains. Ndustrial helps companies lower energy intensity, decrease costs, and increase sustainable industrial operations with solutions like the Nsight Energy Intensity Platform, a data analytics and monitoring solution central to the management of electric transport refrigeration unit (eTRU) power systems. To learn more, we sat down with Manuel Aguirre VP of Supply Chain Electrification, to discuss Ndustrial's energy optimization solutions and the importance of efficient refrigeration management throughout the cold storage supply chain. We'd love to hear from you. Share your comments, questions and ideas for future
Hineman, Marcie
SAE TOMORROW TODAY: Scaling Connected Vehicles with Over-The-Air Updates1349212/17/2024
As the automotive world shifts toward fully software-defined vehicles (SDVs), many OEMs are hesitant to embrace a consumer-driven model for over-the-air (OTA) updates. Enter Sibros, a company offering holistic OTA software that enables automakers to achieve scalable, software-defined mobility. By providing AI-powered insights that deliver continuous product and service enhancements, OEMs can harness Sibros' single no-code platform to monitor, control and optimize SDVs, thus accelerating time-to-market, reducing code defects and enabling hundreds of connected vehicle use cases at global scale. This presents unique value for consumers, OEMs, commercial fleet operators, and even off-road sectors like agriculture and mining. To learn more, we sat down with Hemant Sikaria, CEO & Co-Founder, Sibros, to discuss the impact of his company's groundbreaking technology, how insurance and regulation come into play, and the importance of robust security measures to ensure the responsible growth of
Hineman, Marcie
AI in Motion Control: Optimizing Servo SystemsTBMG-5218612/01/2024
Maximizing the Potential of TPU Extrusion in Medical Tubing ApplicationsTBMG-5216412/01/2024
Whether for vascular catheters or implantable devices, medical tubing must meet tough standards for flexibility, strength, and biocompatibility. That’s why more manufacturers are turning to thermoplastic polyurethanes (TPUs) that strike the ideal balance between these key properties, making them an excellent choice for high-performance medical tubing. Unlocking the best that TPUs have to offer means optimizing the extrusion process. This article looks at why TPUs are a top pick, the common obstacles in extrusion, and the ways manufacturers can fine-tune their process to get the most out of different grades.
Analog Transformation Complements Open System Designs to Optimize Modern Defense SystemsTBMG-5212112/01/2024
Quantitative Analysis of a Hybrid Electric HMMWV for Fuel Economy Improvement2024-01-3356-TEST-REC11/15/2024
ABSTRACT This paper presents a quantitative analysis and comparison of fuel economy and performance of a series hybrid electric HMMWV (High Mobility Multi-purpose Wheeled Vehicle) military vehicle with a conventional HMMWV of equivalent size. Hybrid vehicle powertrains show improved fuel economy gains due to optimized engine operation and regenerative braking. In this paper, a methodology is presented by which the fuel economy gains due to optimized engine are isolated from the fuel economy gains due to regenerative braking. Validated vehicle models as well as data collected on test tracks are used in the quantitative analysis. The regenerative braking of the hybrid HMMWV is analyzed in terms of efficiency from the kinetic energy at the wheels to the portion of regenerative power which is retrievable by the battery. The engine operation of both the series hybrid and conventional HMMWV are analyzed using a 2-D bin analysis methodology. Finally, the vehicle model is used to make
Nedungadi, Ashok, Masrur, Abul, Khalil, Gus
3D-PRINTING IMPACTS ON SYSTEMS ENGINEERING IN DEFENSE INDUSTRY2024-01-352711/15/2024
ABSTRACT Today’s combat vehicle designs are largely constrained by traditional manufacturing processes, such as machining, welding, casting, and forging. Recent advancements in 3D-Printing technology offer tremendous potential to provide economical, optimized components by eliminating fundamental process limitations. The ability to re-design suitable components for 3D-printing has potential to significantly reduce cost, weight, and lead-time in a variety of Defense & Aerospace applications. 3D-printing will not completely replace traditional processes, but instead represents a new tool in our toolbox - from both a design and a manufacturing standpoint.
Deters, Jason
A Compact, 100V, 360A Full-Bridge GaN Power Module with Integrated Gate Driver Board2024-01-412709/16/2024
Abstract In this paper, the design analysis and development of a 100V, 360A Gallium Nitride (GaN) module is provided. This module has a full-bridge (FB) configuration with four 100V, 90A GaN bare die in parallel per switching position. The design challenges for current distribution on paralleled GaN bare die in a full-bridge module with a small footprint is elaborated with two module designs. To optimize the layout and perform parasitic extraction, Q3D and SIMPLORER tools in ANSYS simulation are utilized. The selected power module design is fabricated. To validate the design and characterization, static and dynamic tests have been performed on this module. The gate driver design details, and power module loss evaluation techniques are discussed. Moreover, the voltage overshoot and resonance are studied and tested using double pulse test (DPT) setup.
Alizadeh, Rayna, Eddins, Richard, Mahmodicherati, Sam, Shiver, Rick, Mihailovic, Zoran, Sowul, Kevin, Ramabhadran, Ramanujam, Haynes, Aric
SAE TOMORROW TODAY: What is the Future of the Car?1347508/27/2024
From autonomy to software to customization, the future of the car is multifaceted. As one of the world's largest suppliers in the automotive space, Magna International uniquely understands this. The company's capabilities span the entire vehicle -- from design to manufacturing to technology -- thus optimizing vehicle performance and shaping the future of the car. To learn more, we sat down with we sat down with Joerg Grotendorst, Senior Vice President, Corporate R&D, Magna, to discuss advancements in electrification and autonomy, innovative design features, and sustainable technologies -- and why a holistic approach to mobility is necessary.
Hineman, Marcie
SAE TOMORROW TODAY: Making the Most of the Curb1347308/12/2024
While the curb is an often overlooked piece of infrastructure, it is vital to the mobility ecosystem with impacts to parking, delivery, rideshare, and much more. Better curb management is a path towards improving accessibility, optimizing digital infrastructure, scaling autonomy, and opening up municipal revenue streams. To learn more, we sat down with SAE Authors Kelley Coyner, Principal, Innovation4Mobility, and Jason Bittner, Associate Division Manager and Principal, Applied Research Associates, to discuss the importance of improving the efficiency and operations of the curb -- and why it's the unsung hero of mobility.
Hineman, Marcie
Reduced Order Single Parameter Tuning using Dynamic Mode Decomposition: An Application in Vehicle Dynamics2024-26-027401/16/2024
Vehicle design necessarily involves tuning various parameters to optimize automotive performance metrics like ride and handling. The tuning process is iterative and involves a trial-and-error approach to understand the influence of the input parameters on various output metrics. We develop tuning models and run many simulations to optimize various parameters, followed by validation. This process is computationally expensive and contingent on the output metrics. Alternatively, data-driven modelling could overcome shortcomings but requires extensive data sets to train, which may not be feasible in the initial design phase. In this work, we demonstrate how we can use Dynamic Mode Decomposition, commonly used in Fluid Mechanics, to create Reduced Order Single Parameter Tuning Models, which are computationally lightweight and can provide the output metrics as a function of one tuning parameter. It reduces the tuning time and also helps to understand the system better. We developed reduced
Budhi, Veerendra Harshal
Resonator design study to reduce pressure pulsation from CNG Injector2024-26-023301/16/2024
With the advent of upcoming stringent automobile emission norms globally, it is inevitable for OEMs to shift towards greener alternatives. Use of CNG is a preferred solution as it is a relatively clean burning fuel and it doesn’t have significant loss in vehicle efficiency and performance. Current customer has become aware and sensitive towards vehicle NVH. Hence, OEMs have to cater to this demand through optimized design and layout. In a passenger vehicle, CNG is stored at high pressure and delivered to injectors after pressure reduction at a regulator. During engine idling opening and closing motion of the CNG injector generates back pulsation and these pulsations cause vibrations which may propagate through other components in the delivery path and perceived as noise inside vehicle cabin. To identify the frequencies involved in pressure pulsation, a 1-D simulation of CNG fuel system is performed using GT-Suite through which excitation frequencies and pressure pulsation peak
Meena, Deepesh, Sharma, Rohan, KHANDELWAL, ABHISHEK, Jadhav, Praveen Singh, Pai, Devananda
Dual-Motor-BEV Controls Optimization2024-26-024301/16/2024
In this paper we will discuss different techniques of controls optimization for a dual motor BEV model and look at the most optimal solution with an objective to minimize motor losses or maximize efficiency. In a dual motor model, torque split ratio plays a vital role in deciding the operating points for each motor and hence the losses or inefficiency in the system. It is important to find the optimal torque split ratio to improve range and performance. Four techniques covered in this paper includes ECMS (Equivalent Consumption Minimization Strategy, DP (Dynamic Programming), DOE (Design of Experiment) and Empirical relation-based approach. ECMS is a local optimization technique whereas DP is global optimization technique. DOE was used to perform a full factorial analysis with an eventual goal of creating a map which relates TSR (Torque Split Ratio) to the operating points in the form of vehicle acceleration and vehicle speed. A quadratic empirical relation between vehicle acceleration
Chopra, Ujjwal
Lightweighting of Two-Wheeler Frame with CAE - Multi Domain Optimization (MDO)2024-26-026101/16/2024
Lightweighting in the automotive industry without the use of finite element methodologies is now inconceivable. With the development and enhancement of various CAE tools available in the market, CAE-driven optimization has become part of the product development cycle. Using a variety of CAE techniques in a lightweight optimization process can significantly reduce product development lead time with good results. Traditional light weighting can be done through different iterative approaches with different manual inputs from cross-domain teams, which is usually time consuming and leads to repeated analyses, etc. The current method describes the case of a multi-domain optimization (MDO) approach involving E-Motorcycle frame weight reduction while taking into account various important cross-domain load cases using CAE methodologies. For frame optimization, the most important loads - stiffness, durability/strength (Normal & Abusive), and NVH (Modes & Vibration) - were taken into account, as
S, Vishnu, kakanur, Ashok, U PE, Manjunatha, Bhat, Sachin, POOJARY, KIRAN, V N, Kishor
Electromechanical Multiphysics simulation of Motor2024-26-025001/16/2024
These days, the use of virtual Multiphysics simulations through finite element analysis methodology is increasing exponentially during the development phase of automotive products. Thereupon, the automotive industries are becoming competent enough to build an ingenious and creative design with optimal performance within the coherent time. Huge number of electromagnetic forces are being generated inside the Motor, when it is undergoing extreme driving conditions of the application. Hence it becomes vital to reduce the risks, if any, during the development phase by providing an optimal factor of safety within the electromechanical system of the motor. The present study gives details about conducted finite element analysis on an automotive motor to determine its mechanical strength and behaviour. Numerical analysis will also be performed to determine the possibilities of further design optimization within a Motor. This study also focuses on finding the structurally critical regions over
Karale, Ajinkya Sujay
Comparison between state of art performance parameter of GaN and SiC Converters for electric vehicle application.2024-26-013401/16/2024
Various aspects of vehicle design, such as powertrain, infotainment, connectivity, and driving assistance systems, are undergoing significant advancements and innovations in the automotive industry. To enhance the performance and efficiency of electric vehicles, designers are exploring advanced technologies beyond the conventional silicon-based solutions. One such technology that is gaining popularity is the use of wide-bandgap materials like silicon carbide (SiC) and gallium nitride (GaN) for power-semiconductor devices in electric vehicles. Wide-bandgap-based hard-switching voltage source converters made of these materials are superior to their silicon counterparts in terms of efficiency, but their performance depends on their utilization at high switching frequencies. To determine the best technology for future electric vehicle applications, researchers compared the efficiency of SiC and GaN devices by analyzing factors such as blocking voltage, conduction loss, switching loss, and
Mehrotra, Soumya, Ray, Rakesh Kumar, Pandey, Devbrat, Naithani, Hardik
Powertrain Mounting system NVH simulation methodology using transfer path analysis technique for Electric vehicles2024-26-022501/16/2024
In comparison to traditional gasoline-powered vehicles, Electric vehicles (EVs) development and adoption is driven by several factors such as zero emissions, higher performance, cost effective in maintenance, smoother and quieter ride. Global OEMs are competing to provide a reduced in-cab noise for ensuring a smooth and quiet driving experience. Short project timelines for EV demands quick design and development. In initial stages of project, input data availability of EV is limited and a simplified approach is necessary to accelerate the development of vehicle. This paper focuses on simulation methodology for predicting structure borne noise from powertrain deploying Transfer Path Analysis approach. Current simulation methodology involves full vehicle model with multiple flexible bodies and full BIW flexible model which leads to complex modelling and longer simulation times. The proposed transfer path analysis technique utilises, a simplified Multibody Dynamics EV powertrain model
Duraikannu, Dinesh, Iqbal, Shoaib
Test Methodology Development For Rig Level Validation Of Light Weight Stabilizer Link Of EV Bus Suspension2024-26-035701/16/2024
In the modern and fast growing automotive sector, reliability & durability are two terms of utmost importance along with weight ad cost optimization. Therefore it is important to explore new technology which has less weight, low manufacturing cost and better strength. The new technology developed always seek for a quick, cost effective and reliable methodology for its design validation so that any modification can be made by identifying the failures. This paper presents the rig level test methodology to validate and to correlate the CAE derived strain levels, life cycle & failure mode of newly developed light weight stabilizer link for EV Bus suspension. Stabilizer link replaces the existing separate arrangement of anti-roll bar and parallel rods and light in weight by 30kg.This stabilizer link arrangement is having the short lever arms which are connected through torsion bar which goes under twisting moment and the short lever arms are intended to control wheel motion in longitudinal
Tangade, Atul Bandu, Babar, Sunil, Bankar, Milind Achyutrao, Mehendale, Ravindra, Dhumal, Kailas, Bhusari, Deepak
An experimental approach to investigate the FEAD cover failure & its design optimization.2024-26-037101/16/2024
In automotive Front End Accessory Drives (FEAD), the crankshaft supplies power to accessories like alternators, pumps, etc. FEAD undergoes forced vibration due to crankshaft excitation, dynamic tension fluctuations can cause the belt to slip on the accessory pulleys. By considering the criticality of the system, when engine mounting is longitudinally to the vehicle which makes it directly exposed to the air flow containing foreign particles which may cause the damage to the FEAD system and deteriorate the intended functionality. FEAD cover is introduced in the system to enhance belt-pully system functionality by restricting the entry of foreign particles during engine operation. This paper contains study of FEAD cover failure and provide the stepwise approach to capture such issue during novel model development for 4 cylinder naturally aspirated engine during engine bench testing. Failure mechanism was studied using various methodology such as CAE and G-Load measurement to identify the
PATEL, HARDIK MANUBHAI, KUMAR, NITISH, Chand, Subhash, Gupta, Vineet
A novel approach for Combi Braking System design considering tire's nonlinear behavior2024-26-005801/16/2024
The standard usage of Combined Braking System (CBS) in lower cc/power 2-wheeler vehicles serves to reduce stopping distance and improve braking stability. The CBS system achieves this by engaging both the front and rear wheel brakes, taking advantage of the high load transfer characteristic during 2-wheeler braking. However, the current design of the CBS system relies on linear system analysis, based on vehicle geometry, load distribution, and tire-road friction. This approach overlooks the non-linearities inherent in braking dynamics, such as tire behavior and dynamic Center of Gravity (CoG) location. Consequently, the current CBS design methodology exhibits limitations, particularly in extreme scenarios where wheel lock-up may occur, such as on low friction surfaces or during panic braking. This paper proposes the incorporation of tire non-linearities into the design of CBS systems using Pacejka's tire model. Initially, calculations are performed to optimize the braking
Khandekar, Piyush, Badiger, Kartik, Gautam, Ashish, Soni, Lokesh
Measurement uncertainty and its influence on e-Drive optimization applications2024-26-009701/16/2024
This paper gives insights in the theoretical measurement uncertainty of E-Drive rotor position dependent results, like Id and Iq calculations, done by a modern propulsion power analyzer (PA). The calculation of Id and Iq is fundamental to perform control optimization and application tasks for an E-Drive system. In order to optimize the E-Drive system application towards e.g. best efficiency, best performance, or improved NVH the importance of the testing toolchain is described: a power analyzer delivering the required results, an automation system, and a Design of Experiment tool to set improved target values. Consequently, inverters applications featuring field-oriented control (FOC) with permanent magnet synchronous machines (PMSM) are updated with a chosen control strategy. For achieving a certain behavior of an E-Drive, different degrees of freedom in the Inverter Control Unit are available; Lookup tables Id and Iq represent two fundamental application labels to be considered
Platzer, Thomas, Fechter, Michael, Kammerstetter, Heribert, Kolb, Philipp
Regeneration Calibration for optimum Range and effective brakes performances in eSUV2024-26-011001/16/2024
Regenerative braking is an effective approach for electric vehicles (EVs) to extend their driving range. To enhance the braking performances and regenerative energy, regenerative braking control strategy based on multi objective optimisation is explained in this paper. This technical paper would be focusing on extracting optimum Range with effective brake performances without affecting drivability and performances in different drives modes. An extensive research study on public road driving patterns is done to understand the percentage utilisation of brakes at various (low-mid-high) speeds as per the customer driving behavior. Multi-Objective optimisation function with three vital factors is defined where output generated power, torque smoothness and current smoothness are selected as optimisation objective to improve the driving range, braking comfort, and battery lifetime respectively. Braking regeneration maps are calibrated along with optimised foundation brake hardware’s to get
KUMAR, Prabhakar, K, Rajakumar, Krishnan, Nandhakumar, Suhail, Mohammed thamjeed
Automated and Connected SeriesSAE-EPR-0000101/09/2024
Vehicle automation is a complex engineering challenge ranging from how the vehicle works to how it relates to its user and others on the road. Even though humans do make mistakes when driving, it is incorrect to think that their actions tend to be worse than they actually are. On-vehicle automation system is primarily designed to replace the human driving to enhance performance and avoid possible fatalities. However, current implementations in automated vehicles (AVs) generally neglect that human imperfection and preference do not always lead to negative consequences. Disregarding this prevents achieving optimized vehicle performance and maximized road safety. To enhance user-friendliness, as well as in-vehicle task efficiency for AVs, it is important to consider how to improve human driving feature modeling and analysis, provide personalized motion control, and develop true human-like decision-making for AVs. These are aspects that will enhance trust in AVs as they become partners to
Emergency Obstacle Avoidance Trajectory Planning Method of Intelligent Vehicles Based on Improved Hybrid A*10-08-01-000111/14/2023
Abstract In this article, we present a spatiotemporal trajectory planning algorithm for emergency obstacle avoidance. Utilizing obstacle and driving environment data from the sensing module, we construct a 3D spatiotemporal grid map. This informs our improved hybrid A* algorithm, which identifies collision-safe, dynamically feasible trajectories. The traditional hybrid A* algorithm is enhanced in three significant ways to make the search practical and feasible: (1) optimizing search efficiency with motion primitives based on child node acceleration, (2) integrating collision risk into the heuristic function to reduce ineffective node exploration, and (3) introducing a One-Shot search based on the Optimal Boundary Value Problem (OBVP) to improve goal state searches. Finally, the algorithm is tested in two scenarios: (1) a vehicle cut-in from an adjacent lane and (2) a pedestrian crossing. Simulation results indicate that our proposed emergency obstacle avoidance trajectory planning
Chen, Guoying, Yao, Jun, Gao, Zhenhai, Gao, Zheng, Zhao, Xuanming, Xu, Nan, Hua, Min
Analysis of Dynamic Characteristics and Load Sharing Performance of Electric Driven Planetary Gear System Based on Electromechanical Coupling Model2023-01-701110/30/2023
Due to the multi-gear configuration and high integration of electric drive systems in electric vehicles, it is necessary to investigate the influence of drive motor torque fluctuation on the dynamic characteristics and load sharing performance of planetary gear transmission systems. Considering both motor torque fluctuation and internal excitations of the transmission system, a dynamic model of the electromechanical coupled system is established by combining the Maxwell motor electromagnetic model with the planetary gear dynamics model. Based on the proposed model, the dynamic characteristics, dynamic load performance and load sharing performance of the system considering motor torque fluctuation are analyzed, and the improvement of system load sharing performance due to sun gear floating is discussed. The results show that motor torque fluctuation leads to more complex dynamic response and causes the vibration displacement amplitude to more than doubled. Furthermore, the system
Guo, Fang, Li, Chen, Su, Jinzhan, Liu, Chao
Recognition Method for Electronic Component Signals Based on LR-SMOTE and Improved Random Forest Algorithm01-17-01-000506/10/2023
Loose particles are a major problem affecting the performance and safety of aerospace electronic components. The current particle impact noise detection (PIND) method used in these components suffers from two main issues: data collection imbalance and unstable machine-learning-based recognition models that lead to redundant signal misclassification and reduced detection accuracy. To address these issues, we propose a signal identification method using the limited random synthetic minority oversampling technique (LR-SMOTE) for unbalanced data processing and an optimized random forest (RF) algorithm to detect loose particles. LR-SMOTE expands the generation space beyond the original SMOTE oversampling algorithm, generating more representative data for underrepresented classes. We then use an RF optimization algorithm based on the correlation measure to identify loose particle signals in balanced data. Our experimental results demonstrate that the LR-SMOTE algorithm has a better data
Lv, Bingze, Wang, Guotao, Li, Shuo, Wang, Shicheng, Liang, Xiaowen
Application of Hybrid SEA in Vehicle NV Package Optimization2025-01-005005/05/2023
As India’s economy expands and road infrastructure improves, the number of car owners are expected to grow substantially in the coming years. This market potential has intensified competition among original equipment manufacturers (OEMs) to position their products with a focus on cost efficiency while delivering a premium user experience. Noise and Vibration (NV) performance is a critical differentiator in conveying a vehicle's premiumness, and as such, NV engineers must strategically balance the achievement of optimal acoustic performance with constraints on cost, mass, and development timelines. Traditionally, NV package optimization occurs at the prototype or advanced prototype stage, relying heavily on physical testing, which increases both cost and time to market. Furthermore, late-stage design changes amplify these challenges. To address these issues, this paper proposes the integration of Hybrid Statistical Energy Analysis (HSEA) into the early stages of vehicle development
Rai, Nitesh, Mehta, Makrand, Ravindran, Mugundaram
Hybrid 3D Sound Intensity and Simulation for Optimizing Acoustic Output of Truck Rear Axles2025-01-010505/05/2023
This study presents a novel methodology for optimizing the acoustic performance of rotating machinery by combining scattered 3D sound intensity data with numerical simulations, focusing on the rear axle of a truck. Using Scan&Paint 3D, sound intensity data is rapidly acquired over a large spatial area with the assistance of a 3D sound intensity probe and infrared stereo camera. The experimental data is then integrated into far-field radiation simulations, enabling detailed analysis of the acoustic behavior and accurate predictions of far-field sound radiation. This hybrid approach offers a significant advantage for assessing complex acoustic sources, allowing for quick and reliable evaluation of noise mitigation solutions. While the current application focuses on the truck's rear axle far-field radiation, the same method can be extended to predict in-cabin sound pressure, providing a versatile solution for many industrial problems.
Fernandez Comesana, Daniel, Vael, Georges, Robin, Xavier, Orselli, Joseph, Schmal, Jared
Directivity driven simulation methodology for efficient Acoustic Encapsulation2025-01-004805/05/2023
Noise Reduction at the source level is critical to achieve the overall vehicle level interior targets. This method presents a novel approach that integrates directivity analysis with simulation techniques to optimize acoustic encapsulation design for automotive sound sources to achieve the targeted radiation levels. The foundation for this methodology is to measure the angular distribution of sound pressure levels around the noise source so called Directivity, at every frequency of interest and determine the most effective Acoustic encapsulation to achieve the targeted sound radiation. Accurate measurement of directivity in physical testing with fine angular resolutions can be complex and expensive, this study utilizes numerical simulation techniques using FEA to mitigate the challenges in mid frequency range. The scope of the study is focused on mid frequency sound pressure levels between 500-2000 Hz, which are determined to be significant contributors to overall DU noise. The first
KALUVAKOTA, SRIKANTH, Ghaisas, Nikhil, Pilz, Fernando
Experimental Investigation on Genetic Algorithm optimized Proportional Integral Derivative Based Active Suspension System2025-01-001405/05/2023
In this work, Genetic Algorithm (GA) optimized Proportional Integral Derivative (PID) controller is employed. The PID gain values are optimally tuned based on the objective function formulated using the Integral Time Absolute Error (ITAE) criteria of various suspension measures like vehicle body displacement, suspension and tire deflections. The proposed GAPID controller is experimentally validated through the 3-DOF quarter-car test rig model. The fabricated model with passive suspension system (PASS) and active suspension system (ACSS) provided with an electrical actuator as base excitation is pictured. The schematic representation of the fabricated test set-up with and without ACSS is also illustrated. Further, simulation and experimental response of the fabricated model with and without ACSS are compared. It is identified that the proposed GAPID controller attenuates the sprung mass acceleration by about 41.64 % and 29.13 % compared with PASS for the theoretical as well as
A, Arivazhagan
Active noise control with head tracking system2025-01-001205/05/2023
In active noise control, the control region size(zone of control) decreases as the frequency increases, so that even a small moving of the passenger's head causes the ear position to go out of the control region. In order to increase the size of the control region, many speakers and microphones are generally required, but it is difficult to apply it in a vehicle cabin due to space and cost constraints. In this study, we propose moving zone of quite actvie noise control technique. An 2D images based head tracking system captured by a camera to generate the passenger's head coordinates in real time with deep learning algorithm. In the controller, the control position is moved to the ear position using a multi-point virtual microphone algorithm according to the generated ear position. After that, the multi-point adaptive filter training system applies the optimal control filter to the current position and maintains the control performance. Through this study, it is possible to secure the
Oh, ChiSung
Virtual Gear Noise Analysis and Case Design Investigation for Concept Parallel Axis Drive Unit2025-01-010205/05/2023
For electric vehicles, it is critical to develop drive units that produce a minimal amount of noise while meeting efficiency needs for a given application. Modern computational resources and accumulated experience allow for engineers to evaluate gear noise early in the development process and influence the design of the drive unit. This paper documents a high-fidelity virtual engineering approach to evaluate gear noise in a concept parallel axis drive unit and provide learnings to influence design of the external structure to improve NVH performance. By using the latest simulation tools to calculate and visualize the noise and vibration characteristics of the drive unit, designers and developers can implement design changes in optimization iterations to reduce noise and vibration. Gear harmonic response is firstly analyzed through a system model which considers structural deflection and misalignment, then a FE housing model is incorporated which is used for noise radiation evaluation
Lima, Luiz, Shi, Zhenghong, Xu, Hai, REYNOLDS, CRAIG, Miller, John
Co-relation of NVH results with housing modal analysis and improvement of the BEV transmission.2025-01-010605/05/2023
The battery electric vehicle (BEVs) are very sensitive in terms of NVH requirements. While the engine is getting replaced with an almost silent electric motor, the transmission noise appears persistent and demands more silent transmission. This has raised demand for improvement in design as well as manufacturing quality. Various innovations are being done to drive an improvement in the NVH. Following paper will discuss the improvement in NVH achieved through a design optimization of the housing using modal analysis. Firstly, the NVH results were co-related with the modal analysis and the cause for the dominant peak in amplitude of the NVH graph associated with the housing modes were mapped. A simple Excel based correlation matrix used to map the list of all Eigenfrequencies of housing and it’s corresponding gear tooth frequency. Further optimization is done in housing design to defer the modal frequencies and another NVH test was run. It was proven that the housing optimization using
Pingale, Abhijeet Satish, Deshpande, Prasannakumar
Asymmetric Gear Blank Optimization to Reduce Gear Noise for Electric Drive Units2025-01-007905/05/2023
Gear whine has emerged as a significant challenge for electric vehicles (EVs) in the absence of engine masking noise. The demand from customers for premium EVs with high speed and high torque density introduces additional NVH risks. Conventional gear design strategies to reduce the pitch-line velocity and increase contact ratio may impact EV torque capacitor or its efficiency. Furthermore, microgeometry optimization has limited design space to reduce gear noise over a wide range of torque loads. This paper presents a comprehensive investigation into the optimization of transfer gear blanks in a single-speed two-stage FDW electric drive unit (EDU) with the objective of reducing both mass and noise. A detailed multi-body dynamics (MBD) model is constructed for the entire EDU system using a finite-element-based time-domain solver. This investigation focuses on the analysis and optimization of asymmetric gear blank design features with three-slot patterns. A DOE methodology is employed to
He, Song, Bahk, Cheonjae, Li, Bo, Du, Isaac, Patruni, Pavan Kumar, Baladhandapani, Dhanasekar
Designing Rubber Flaps for Resonance Management: High-Frequency Tuning in Electric Vehicles Using AI/ML Approaches2025-01-012505/05/2023
High-frequency whine noise in electric vehicles (EVs) poses a significant challenge, affecting customer perception and the overall vehicle experience. One primary source of this undesirable noise is the interaction between motor pole resonance and the resonance of the engine mount rubber. This paper presents an innovative method for predicting and tuning the frequency response of engine mounts by precisely adjusting the dimensions of rubber flaps, specifically their length and width. The proposed solution employs a dual approach: fine-tuning rubber flap dimensions and utilizing machine learning (ML) techniques. An ML model, trained on historical data, predicts how varying flap dimensions impact frequency response, providing a data-driven foundation for optimization. This prediction capability is enhanced by a Python program that automates the optimization process using a linear combination formula, efficiently addressing resonance issues. By integrating ML insights with the linear
Hazra, Sandip, Khan, Arkadip
Navigating Evolving Vehicle NVH Challenges with Application of Emerging Technologies in Artificial Intelligence and Machine Learning2025-01-013005/05/2023
The multifaceted, fast-paced evolution in the automotive industry includes noise and vibration (NVH) behavior of products for regulatory requirements and ever-increasing customer preferences and expectations for comfort. There is pressing need for automotive engineers to explore new and advanced technologies to achieve a ‘First Time Right’ product development approach for NVH design and deliver high-quality products in shorter timeframes. Artificial Intelligence (AI) and Machine Learning (ML) are trending transformative technologies reshaping numerous industries. AI enables machines to replicate human cognitive functions, such as reasoning and decision-making, while ML, a branch of AI, employs algorithms that allow systems to learn and improve from data over time. The purpose of the paper is to show an approach of using machine learning techniques to analyze the impact of variations in structural design parameters on vehicle NVH responses. The study begins by executing the Design of
Miskin, Atul R., Parmar, Azan, Raj, Sonia, himakuntla, Uma Maheswar
Data-Driven Machine Learning Approach for Rattle Risk Mitigation2025-01-012605/05/2023
In the modern automotive industry, squeak and rattle issues are critical factors affecting vehicle perceived quality and customer satisfaction. Traditional approaches to predicting and mitigating these problems heavily rely on physical testing and simulation technologies, which can be time-consuming and resource-intensive, especially for larger models. In this study, we propose a data-driven machine learning approach to mitigate rattle risks more efficiently. In this study, a floor console model has been evaluated using the traditional simulation-based E-line method to pinpoint high-risk areas. Data generation is performed by varying material properties, thickness, and flexible connection stiffness using the Modified Extensible Lattice Sequence (MELS) sampling algorithm, creating a diverse and comprehensive dataset for generating a machine learning (ML) model. Utilizing the dataset, the top contributing variables were identified for training the ML models. Various machine-learning
Parmar, Azan, Rao, Sohan, Reddy, Hari Krishna
Tire simulation to optimize road noise2025-01-011105/05/2023
Tires have a significant impact on vehicle road noise. In the past, tire development has been driven by testing that is costly and time-consuming. Simulation approaches are becoming more important as the need for NVH performance requirements rises and vehicle development cycles get shorter. Therefore, simulation techniques should be used to tires at an early stage. Among various road noise, the noise of 80~160 Hz is easily felt when driving on the rough road, and this noise has a great relationship with the tire structural design. How to improve the road noise problem through tire simulation has become an important issue, so this paper puts forward the concept of virtual tire design and clarifies the responsibility of automotive enterprises and tire suppliers. In virtual tire design or tuning, an appropriate tire model is crucial for road noise performance. The CDtire model can meet the requirements, so in this article, CDtire is used to improve road noise at 80-120Hz. To obtain an
zhang, Ben, Yu Sr, Jing, Chen, Qimiao, Liu, Xianchen, Gu, Perry
A Methodology to Design the Flow Field of PEM Fuel Cells2023-01-049504/11/2023
Proton Exchange Fuel Cells (PEMFCs) are considered one of the most prominent technologies to decarbonize the transportation sector, with emphasis on long-haul/long-range trucks, off-highway, maritime and railway. The flow field of reactants is dictated by the layout of machined channels in the bipolar plates, and several established designs (e.g., parallel channels, single/multi-pass serpentine) coexist both in research and industry. In this context, the flow behavior at cathode embodies multiple complexities, namely an accurate control of the inlet/outlet humidity for optimal membrane hydration, pressure losses, water removal at high current density, and the limitation of laminar regime. However, a robust methodology is missing to compare and quantify such aspects among the candidate designs, resulting in a variety of configurations in use with no justification of the specific choice. This contrasts with the large operational differences, especially regarding the pressure loss
Corda, Giuseppe, Cucurachi, Antonio, Diana, Martino, Fontanesi, Stefano, D'Adamo, Alessandro
Optimization of Buckling Load of Thin Hybrid Composite plate of Carbon/Glass Epoxy using Taguchi Approach2022-28-050211/18/2022
The aim of the paper is to analyze the effect of the design factors on the buckling load of the thin hybrid laminated composite plate made of Carbon/Glass Epoxy fiber. The detailed investigation is done on the stacking sequence, stacking angle, cut-out orientation whose shape is elliptical and thickness of the plate. For optimization the Taguchi approach of Design for Experiments (DOE) is being considered. For obtaining the combinations L16 orthogonal array is implemented using MINITAB and analysis is carried using ANSYS software. Analysis of each factor is done and significance of each factor is decided based on the 0.05 confidence level. Normal Probability and Residual versus Fitted Values plot is being obtained. Based on the delta values rank for each factor which have four levels are given. The boundary condition of simply supported on all edges is considered during the simulation for calculating the critical buckling load.
Gore, Renuka, Bhaskara Rao, Lokavarapu
AC System COP Optimization Through Major or Minor Adjustment of Component Design2022-28-042311/09/2022
In the process of designing of complete cycle of vapour compression refrigerant system, most important part is optimization of performance of all components including compressor, condenser, expansion valve, evaporator and piping and COP of the system . For balancing and COP optimization of air conditioning cycle, it is extremely important that all component selected must be balanced and synchronized with other components relatively. Many researches have been done related to system COP and performance optimization through various method as well as component performance optimization. While optimizing the cycle, changing one component parameter effects the other components behavior and becomes challenge to control all other characteristic. Sometimes even a minor adjustment in the cycle leads change in output result of components which are not preferable. The present paper is about optimization of system COP of refrigerant cycle through various combination of iteration that includes
raj, Abhishek, Bajpai, Himanshu, Agarwal, Roopak, Anal, Rajeev
Design Optimization and Thermal Simulation of a Plate Type Heat Exchanger (“Chiller”) for EVs Applications2022-28-044111/09/2022
The rapid evolution of electric vehicles (EVs) has considerably forced the automotive industry to design compact & highly efficient heat exchangers due to lower temperature applications. The plate type heat exchangers (Also known as "Chillers" in automotive industry) are one of the most important components in EVs thermal management systems. It is a type of heat exchanger, which uses metallic plates arranged like a staggered sandwiched structure to exchange heat between two working fluids. The heat transfer between the plates occurs due to highly compact structural design as compare to any conventional heat exchangers. The chiller is having very large surface area, which is exposed to the working fluids as the distribution happens all across the plates. The chillers are more suitable design for transferring heat between ranges of working fluids pressure varying from low to high pressures. Various types of welded, semi-welded plate heat exchangers are available. The working fluids flow
Suman, Saurabh, Kushwah, Yogendra Singh, SHUKLA, ANKIT, Singh, Shobhit Kumar
electric - take 2SAE-PP-0779211/04/2022
electric
SintzADMIn, Jeneane
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