Browse Topic: Optimization

Items (6,984)

Image Processing-Based Chip Detection by KIZKI Algorithm and Its Optimization

2025-01-0168To be published on 05/02/2025

The process of producing aircraft parts involves the drilling of aluminum alloys. This creates a large amount of chips, which are removed using air, but sometimes they still remain within the holes. This is checked by inspectors through visual inspection. However, the quality of human inspection varies based on skill level and fatigue. Thus, image-based inspection should be used to stabilize and further improve inspection quality. This study aims to build a framework for chip detection based on image processing. Taking into account on-site implementation, the system must have low installation and running costs and be standalone. Therefore, we adopt the KIZKI algorithm, which satisfies these conditions. KIZKI means awareness in Japanese. This is a model of human peripheral vision and saccades. It does not require training like AI and can achieve high-speed and high-performance detection using a low-performance computer. In other words, there is no need for a computer with an expensive

Iinuma, Marin, Sato, Junya, Tsuji, Masahiko

Optimization of the Numerical Spray Modeling for Polyoxymethylene Dimethyl Ethers for Combustion Prediction in CONVERGE

2025-01-5026

04/03/2025

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

On the Characterization and Optimization of Machining Chip Washing System Using Multi-Variable Response Surface and Gradient Descent Method Abstract

2025-01-8637

04/01/2025

The final step in manufacturing high-precision parts for internal combustion engines, such as cylinder heads and blocks, is the removal of machining chips from the finished parts. This step is crucial because the machining chips and cutting oil left on the surface after machining can cause quality issues in the downstream engine assembly and affect the cooling system’s performance during engine operation. This chip removal step is especially critical for parts with internal cavities, such as the water jackets in cylinder heads, due to the difficulty of removing chips lodged in the narrow passages of these internal channels. To effectively remove chips from the water jacket, machining chip washing systems typically utilize multiple high-velocity water jets directed into the water jacket, creating flows with substantial kinetic energy to dislodge and evacuate the machining chips. For machining chip washing systems equipped with dozens of water nozzles, optimizing washing efficiency

Jan, James, Torcellini, Sabrina, Khorran, Aaron, Hall, Mark

A Comprehensive Study of Gaussian Process-Based Multi-Objective Multi-Fidelity Modeling Techniques and its Applications to Shell-and-Tube Heat Exchanger Design

2025-01-8646

04/01/2025

In numerous automotive and industrial applications, efficient heat extraction is crucial to prevent system inefficiencies or catastrophic failures. The design of heat exchangers is inherently complex, involving multiple stages defined by the depth of analysis, number of design variables, and the accuracy of physical models. Designers must navigate the trade-offs between highly accurate yet computationally expensive models and less accurate but computationally cheaper alternatives. Multi-fidelity modeling offers a solution by integrating different fidelity models to deliver precise results at a reduced computational cost. In addition to managing these trade-offs, designers often face multi-objective challenges, where optimizing one aspect may lead to compromises in others. Multi-objective optimization, therefore, becomes essential in balancing these competing objectives to achieve the best overall design. In this context, Gaussian Process-based methods have gained prominence as

Chaudhari, Prathamesh, Tovar, Andres

Tube-MPC Based Path Tracking for I Vehicle Considering Data-Driven Stable Region and External Disturbances

2025-01-8262

04/01/2025

Path tracking is a key function of intelligent vehicles, which is the basis for the development and realization of advanced autonomous driving. However, the imprecision of the control model and external disturbances such as wind and sudden road conditions will affect the path tracking effect and even lead to accidents. This paper proposes an intelligent vehicle path tracking strategy based on Tube-MPC and data-driven stable region to enhance vehicle stability and path tracking performance in the presence of external interference. Using BP-NN combined with the state-of-the-art energy valley optimization algorithm, the five eigenvalues of the stable region of the vehicle β−β̇ phase plane are obtained, which are used as constraints for the Tube-MPC controller and converted into quadratic forms for easy calculation. In the calculation of Tube invariant sets, reachable sets are used instead of robust positive invariant sets to reduce the calculation. Simulation results demonstrates that the

Zhang, Haosen, Li, Yihang, Wu, Guangqiang

Unleash the Power of Generative Design for Lightweighting and Reducing Carbon Footprints in Automotive Engineering

2025-01-8657

04/01/2025

The automotive industry faces ongoing challenges in reducing vehicle mass and carbon emissions while ensuring structural integrity. Traditional design approaches often fail to address these issues comprehensively. This paper explores the application of generative design (GD) to optimize critical automotive components, specifically focusing on reducing mass and in turn carbon emissions. GD builds upon traditional topology optimization by employing iterative method using MELS approach to refine designs providing multiple alternative designs to choose from. MELS (Modified Extensible Lattice Sequence) specifically is used to equally spread-out points (designs) in a space by minimizing clumps and empty spaces. This property of MELS makes lattice sequences an excellent space filling DOE scheme. GD leverages the design of experiments (DOE) to vary key design variables systematically to generate and consider many potential design concepts for a given problem. It also uses artificial

Hosmath, Anjaney, Barai, Jay, Dhangar, Vinaykumar

Machine Learning-Based Digital Twin for Optimizing Automotive Components

2025-01-8206

04/01/2025

This paper presents a Digital Twin approach based on Machine Learning (ML), aimed at creating software-based sensors to reduce the auxiliary devices of the vehicle and enabling predictive maintenance, thus reducing carbon footprint. The solution is applied to the electric Lubrication Oil Pump (eLOP), a crucial component within a vehicle's powertrain system. The proposed eLOP Digital Twin integrates ML-based sensors to estimate critical parameters such as temperature, pressure and flow rate, reducing the reliance on physical sensors and associated hardware. This approach minimizes manufacturing complexity and cost, enhancing energy efficiency during both production and operation. Furthermore, the Digital Twin facilitates predictive maintenance by continuously monitoring the component's performance, enabling early detection of potential failures and optimizing maintenance schedules. This leads to lower energy consumption and reduced emissions throughout the component's lifecycle. The

Khan, Jalal, D'Alessandro, Stefano, Tramaglia, Federico, Fauda, Alessandro

Machine Learning-Enabled Optimization of Vehicle Restraint Systems – Demonstration in a Real-World Crash Scenario

2025-01-8722

04/01/2025

Vehicle restraint systems, such as seat belts and airbags, play a crucial role in managing crash energy and protecting occupants during vehicle crashes. Designing an effective restraint system for a diverse population is a complex task. This study demonstrates the practical implementation of state-of-the-art Machine Learning (ML) techniques to optimize vehicle restraint systems and improve occupant safety. An ML-based surrogate model was developed using a small Design of Experiments (DOE) dataset from finite element human body model simulations and was employed to optimize a vehicle restraint system. The performance of the ML-optimized restraint system was compared to the baseline design in a real-world crash scenario. The ML-based optimization showed potential for further enhancement in occupant safety over the baseline design, specifically for small-female occupant. The optimized design reduced the joint injury probability for small female passenger from 0.274 to 0.224 in the US NCAP

Lalwala, Mitesh, Lin, Chin-Hsu, Desai, Megha, Rao, Shishir

A Comparative Study of Optimization Algorithms for 6DOF Design in Electric Vehicle Powertrain Mounting Systems

2025-01-8650

04/01/2025

Optimizing engine mounting systems is a complex task that requires balancing the isolation of vehicle vibrations with controlling powertrain movement within a limited dynamic envelope. Six Degrees of Freedom (6DOF) optimization is widely used for mounting stiffness and location optimization. This study investigates the application of various optimization algorithms for 6DOF analysis in engine mount design, where the system’s stochastic behaviour and probabilistic characteristics present additional challenges. Selecting an appropriate optimization framework is essential for achieving accurate and efficient NVH results. Recent advancements in research have introduced several 6DOF optimization algorithms to determine the optimal stiffness and location of engine mounts. The study evaluates a range of optimization methods, including Simultaneous Hybrid Exploration that is Robust, Progressive and Adaptive (SHERPA), Quadratic Programming (QP), Genetic Algorithm (GA), Particle Swarm

Hazra, Sandip, Khan, Arkadip

A Steering Control Method Applicable to an Eight-Wheeled Planetary Laboratory

2025-01-8305

04/01/2025

In future planetary exploration missions, the Eight-Wheeled Planetary Laboratory (EWPL) will have sufficient capacity for tasks but will experience significant lateral slips during high-speed turns due to its large inertia. Modern technology allows for independent steering of all eight wheels, but controlling each wheel's steering angle is key to improving stability during turns. This paper introduces a novel rear-axle steering feed-forward controller to reduce sideslip. First, a mathematical model for the vehicle's steering is established, including kinematic equations based on Ackermann steering. Feed-forward zero side-slip control is applied to the third and fourth axles to counteract the side-slip angle of the center of mass. A multi-body dynamics model of the EWPL is then built in Chrono to evaluate the turning radius and optimize steering angle ratios for the rear axles. Finally, a steady-state cornering simulation on loose terrain compares the performance of the proposed

Liu, Jun, Zhang, Kaidi, Shi, Junwei, Yang, Wenmiao, Zhang, Yunqing, Wu, Jinglai

Research on Noise Optimization Control Based on the New Dead Zone Compensation in Dual Motor Hybrid System

2025-01-8516

04/01/2025

In a three-phase voltage source inverter, in order to prevent the direct short circuit of the upper and lower tubes of the bridge arm and ensure the normal operation of the inverter, microsecond-level dead time needs to be added when the power devices are turned on and off. However, due to the dead-time effect, slight distortion may occur in the inverter within the modulation period, and this distortion will eventually lead to harmonic components in the output current after accumulation, thereby generating torque ripple. Against the above background, implementing dead-time compensation strategies is very important. To compensate for the voltage error caused by the dead-time effect, current polarity determination is required first. Then, the dead time is compensated, thereby indirectly compensating for the voltage error caused by the dead-time effect. Regarding the dead-time compensation time, without changing the hardware, this paper proposes a solution to turn off the dead-time

Jing, Junchao, Zhang, Junzhi, Zuo, Botao, Liu, Yiqiang, Yang, Tianyu, Zhu, Lulong

A Deep Learning Framework for Time Series Prediction of Passenger Motion Sickness Based on Vehicle Dynamics Data

2025-01-8104

04/01/2025

Technology development for enhancing passenger experience has gained attention in the field of autonomous vehicle (AV) development. A new possibility for occupants of AVs is performing productive tasks as they are relieved from the task of driving. However, passengers who execute non-driving-related tasks are more prone to experiencing motion sickness (MS). To understand the factors that cause MS, a tool that can predict the occurrence and intensity of MS can be advantageous. However, there is currently a lack of computational tools that predict passenger's MS state. Furthermore, the lack of real-time physiological data from vehicle occupants limits the types of sensory data that can be used for estimation under realistic implementations. To address this, a computational model was developed to predict the MS score for passengers in real time solely based on the vehicle's dynamic state. The model leverages self-reported MS scores and vehicle dynamics time series data from a previous

Kolachalama, Srikanth, Sousa Schulman, Daniel, Kerr, Bradley, Yin, Siyuan, Wachsman, Michael Ben, Pienkny, Jedidiah Ethan Shapiro, Jalgaonkar, Nishant M., Awtar, Shorya

Integrated Bracket Design Optimizations to Resolve Issues in Vehicle Prototype Stage

2025-01-8614

04/01/2025

The integrated bracket is a plastic part that packages functional components such as the ADAS (Advanced Driver Assistance System) camera, rain light sensor, and the mounting provisions of the auto-dimming IRVM (Inner Rear View Mirror). This part is fixed on the windshield of an automobile using double-sided adhesive tapes and glue. ADAS, rain light sensors, and auto-dimming IRVM play an important part in the safety of the driver and everyone present in the automobile. This makes proper functioning of the integrated bracket very integral to occupant safety. Prior to this work, the following literature; Integrated Bracket for Rain Light Sensor/ADAS/Auto-Dimming IRVM with provision of mounting for Aesthetic Cover [1] outlines the design considerations and advantages of mounting several components on the same bracket. It follows the theme where the authors first define the components packaged on the integrated bracket and then the advantages of packaging multiple components on a single

Chandravanshi, Priyansh, Dharmatti, Girish

Improving Modal Frequencies in Class 5 Truck Fuel Cell Tank Structure through Topology Optimization

2025-01-8648

04/01/2025

In addition to electric vehicles (EVs), hydrogen fuel cell systems are gaining attention as energy-efficient propulsion options. However, designing fuel cell vehicles presents unique challenges, particularly in terms of storage systems for heavy hydrogen tanks. These challenges impact factors such as NVH (noise, vibration, and harshness) and safety performance. This study presents a topology optimization study for Hydrogen Energy Storage System (HESS) tank structure in Class 5 trucks, with a focus on enhancing the modal frequencies. The study considers a specific truck configuration with a HESS structure located behind the crew cab, consisting of two horizontally stacked hydrogen tanks and two tanks attached on both sides of the frame. The optimization process aimed to meet the modal targets of this hydrogen tank structure in the fore-aft (X) and lateral (Y) directions, while considering other load cases such as a simplified representation of GST (global static torsion), simplified

Yoo, Dong Yeon, Chavare, Sudeep, Viswanathan, Sankar, Mouyianis, Adam

Multiphysics-Multiscale Reduced Order Model based Design Optimization of the Immersion Cooled Battery System

2025-01-8185

04/01/2025

A vital aspect of Ultra-Fast Charging (UFC) Li-Ion battery pack is its thermal management system, which impacts safety, performance, and cell longevity. Immersion cooling technology is more effective compared to indirect cold plate as heat can dissipate much quicker and has a potential to mitigate the thermal runaway propagation, improve pack overall performance, and cell life significantly. For design optimization and getting better insight, high fidelity Multiphysics-Multiscale simulations are required. Equivalent Circuit Model (ECM) based electro-thermally coupled multi-physics CFD simulations are performed to optimize the innovative busbar design, of a recently developed immersion cooled battery pack, which enables the capability to remove individual cell. Further, high fidelity 3D transient flow-thermal simulations have helped in optimizing the coolant flow direction, inlet positions, cell spacing and separator design for efficient flow distribution in the module. While high

Tyagi, Ramavtar, Negro, Sergio, Baranowski, Alex, Atluri, Prasad

Lightweight Optimization of an Electric Bus Body Frame Based on the C ² oDE Algorithm

2025-01-8654

04/01/2025

In this work, design optimization for the lightweight of the body frame of a commercial electric bus with the requirements of stiffness, strength and crashworthiness is presented. The technique for order preference by similarity to ideal solution (TOPSIS) is applied to calculate the components that have a great impact on the output response of the static modal model and the rear-end collision model. The thickness of the five components with the highest contribution in the two models is determined as the final design variable. Design of experiment (DOE) is carried out based on the Latin Hypercube sampling method, and then the surrogate models are fitted by the least squares regression (LSR) method based on the DOE sampling data. The error analysis of the surrogate model is carried out to determine whether it can replace the finite element (FE) model for optimization, then the optimization scheme for lightweight optimization of electric bus frame is implemented based on the algorithm of

Yang, Xiujian, Tian, Dekuan, Liu, Jiaqi, Cui, Yan, Lin, Qiang

Solving Vehicle Speed and Acceleration from Video Evidence Using Optimization

2025-01-8683

04/01/2025

Abstract This paper introduces a method to solve the instantaneous speed and acceleration of a vehicle from one or more sources of video evidence by using optimization to determine the best fit speed profile that tracks the measured path of a vehicle through a scene. Mathematical optimization is the process of seeking the variables that drive an objective function to some optimal value, usually a minimum, subject to constraints on the variables. In the video analysis problem, the analyst is seeking a speed profile that tracks measured vehicle positions over time. Measured positions and observations in the video constrain the vehicle’s motion and can be used to determine the vehicle’s instantaneous speed and acceleration. The variables are the vehicle’s initial speed and an unknown number of periods of approximately constant acceleration. Optimization can be used to determine the speed profile that minimizes the total error between the vehicle’s calculated distance traveled at each

Snyder, Sean, Callahan, Michael, Wilhelm, Christopher, Johnk, Chris, Lowi, Alvin, Bretting, Gerald

A Path Tracking Control Method Considering Vehicle Stability and Road Curvature

2025-01-8038

04/01/2025

The current research landscape in path tracking control predominantly focuses on enhancing tracking accuracy, often overlooking the critical aspect of passenger comfort. To address this gap, we propose a novel path tracking control method that integrates vehicle stability indicators and road curvature variations to elevate passenger comfort. The core contributions are threefold: firstly, we conduct comprehensive vehicle dynamics modeling and analysis to identify key parameters that significantly impact ride comfort. By integrating human comfort metrics with vehicle maneuverability indices, we determine the optimal range of dynamics parameters for maximizing passenger comfort during driving. Secondly, inspired by human driving behavior, we design a path tracking controller that incorporates an anti-saturation algorithm to stabilize tracking errors and a curvature optimization algorithm to mimic human driving patterns, thereby enhancing comfort. Lastly, comparative simulations with two

Lu, Jun, Zeng, Dequan, Hu, Yiming, Wang, Xiaoliang, Liu, Dengcheng, Jiang, Zhiqiang

Analysis and Validation of Torque Ripple Cancellation to Reduce Electric Motor Noise for Electric Vehicles

2025-01-8573

04/01/2025

The electric motor is a significant source of noise in electric vehicles (EVs). Traditional hardware-based NVH optimization techniques can prove insufficient, often resulting in trade-offs between motor torque or efficiency performance. The implementation of motor control-based torque ripple cancellation (TRC) technology provides an effective and flexible solution to reduce the targeted orders. This paper presents an explanation of the mathematical theory underlying the TRC method, with a particular focus on the various current injection methods, including those that allow up to 4DOFs (degrees-of-freedom). In the case study, the injection of controlled fifth or seventh order current harmonics into a three-phase AC motor is shown to be an effective method for cancelling the most dominant sixth order torque ripple. A dedicated feedforward harmonic current generation module is developed the allows the application of harmonic current commands to a motor control system with adjustable

He, Song, Gong, Cheng, Chang, Le, Peddi, Vinod, Zhang, Peng, GSJ, Gautam

Virtual Evaluation of Ceramic Glow Plug Design using Multiphysics Simulation Approach

2025-01-8367

04/01/2025

A glow plug is generally used to assist the starting of diesel engines in cold weather condition. Low ambient temperature makes the starting of diesel engine difficult because the engine block acts as a heat sink by absorbing the heat of compression. Hence, the air-fuel mixture at the combustion chamber is not capable of self-ignition based on air compression only. Diesel engines do not need any starting aid in general but in such scenarios, glow plug ensures reliable starting in all weather conditions. Glow plug is actually a heating device with high electrical resistance, which heats up rapidly when electrified. The high surface temperature of glow plug generates a heat flux and helps in igniting the fuel even when the engine is insufficiently hot for normal operation. Durability concerns have been observed in ceramic glow plugs during testing phases because of crack formation. Root cause analysis is performed in this study to understand the probable reasons behind cracking of the

Karmakar, Nilankan, Orban, Hatem

Analysis of Coolant Flowing and Heat Transfer Performance in High Voltage Heater System

2025-01-8194

04/01/2025

A method for performance calculation and experimental method of a high voltage heater system in electric vehicles is proposed. Firstly, heater outlet temperature and pressure drop of the heater are used as metrics to compare simulation results with experimental data, thereby validating the established model. Then, simulations are performed on two heater flow channel configurations: a cavity flow channel and a cooling fin flow channel. It is observed that the latter significantly reduces the heating plate temperature. This reduction enhances the protection of heating elements and extends their operational lifespan, demonstrating the advantages of incorporating cooling fins into the flow channel structure. The optimization variables for multi-objective optimization include the fin unit length, fin height, fin thickness, fin width, and spacing between two adjacent rows of fins. The optimization objectives include pressure drop, heat transfer efficiency, and heating plate temperature

Gong, Ming, Wang, Xihui, Wang, Dongdong, Shangguan, Wen-Bin

Research on Sampling-Based Motion Planning and Control in Spiral Ramp Scenarios of Underground Parking Garages

2025-01-8039

04/01/2025

The slope and curvature of spiral ramps in underground parking garages change continuously, and often lacks of predefined map information. Traditional planning algorithms is difficult to ensure safety and real-time performance for autonomous vehicles entering and exiting underground parking garages. Therefore, this study proposed the Model Predictive Path Integral (MPPI) method, focusing on solving motion planning problems in underground parking garages without predefined map information. This sample-based method to allows simultaneous online autonomous vehicle planning and tracking while not relying on predefined map information,along with adjusting the driving path accordingly. Key path points in the spiral ramp environment were defined by curvature, where reducing the dimensionality of the sampling space and optimizing the computational efficiency of sampled trajectories within the MPPI framework. This ensured the safety and computational speed of the improved MPPI method in motion

Liu, Zuyang, Shen, Yanhua, Wang, Kaidi

Research on the Control Strategy of Permanent Magnet Synchronous Motors with Reduced Rotor Stack Length in Hybrid System

2025-01-8563

04/01/2025

The key issue in the electromagnetic design of permanent magnet synchronous motors is the design of the rotor structure form of the motor. To achieve the goal of reducing the cost of the motor, this paper conducts electromagnetic design, optimal control calibration of the motor, and performance analysis for reducing the rotor lamination structure, and obtains the characteristics of the permanent magnet synchronous motor under this rotor structure. For the permanent magnet synchronous motor with reduced rotor stack length and one less motor temperature sensor, starting from vector control, the conditions for obtaining the maximum electromagnetic torque and the highest rotational speed are derived. Based on these conditions, the vector control strategies for the system operating under different working conditions are designed. At low speeds, the thermal loss of the stator winding is reduced with the maximum torque current ratio to improve the motor efficiency; as the rotational speed of

Jing, Junchao, Zhang, Junzhi, Yu, Pengfei, Liu, Yiqiang, Chen, Yingchao, Dai, Zhengxing

Propulsion System Design of Cadillac Lyriq Electric Vehicle

2025-01-8566

04/01/2025

The propulsion system design of GM-Cadillac’s first electric vehicle Lyriq uses an optimized drive unit comprising interior permanent magnet (IPM) motors and silicon traction inverters. The main objective behind the drive unit design was to minimize energy losses and cost while maximizing hardware consolidation, range, performance, power density, and scalability. Two IPM motors with different length and number of stator turns are designed, while their rotor design and stator-conductor profile are kept the same. A high-speed rotor is designed to achieve higher power density. AC winding effect at higher speeds is mitigated by using a bar-conductor with much smaller cross section. The rotor surface has a special notch design to minimize acoustic noise, without use of rotor or stator skew. Also, the traction inverters in the Lyriq EV are engineered with a significant emphasis on being scalable and adaptable for various vehicle architectures while considering a broad range of requirements.

Momen, Faizul, Jensen, William, He, Song, Chowdhury, Mazharul, Zahid, Ahsan, Forsyth, Alexander, Alam, Khorshed, Anwar, Mohammad, Kim, Young

Application of Model-Based Horizon Prediction to Enhance Control Algorithm Performance by Compensating for Time Delays in Automotive Drivelines

2025-01-8574

04/01/2025

Accurate estimation of crucial quantities in automotive drivetrain systems is essential for optimizing performance, durability, and emissions. However, the presence of time delays, arising from tasks scheduling and communication latency between control units, can significantly hinder the effectiveness of advance control algorithms. Closed-loop performance is often limited by the equivalent time delay between the control action command, its effect on the system, and the measurement of the reaction. Frequently, commands and measurements originate from different sources, requiring precise coordination to accurately estimate the driveline response. This paper presents a novel model-based approach that integrates Kalman filtering with horizon prediction techniques to effectively address time-delay compensation. By leveraging the descriptive capabilities of physics-based models, the proposed method enables to overcome synchronization misalignment between commands, actuations and measurements

Rostiti, Cristian, Patel, Nadirsh, Catkin, Bilal

Optimization Design of Formula E Racing Car Transmission and Wheel System

2025-01-8505

04/01/2025

The paper provides a detailed analysis of the transmission system design under the single motor drive scheme, with a focus on the 2024 Formula SAE (FSAE). The selection of the motor type is determined based on race rules and battery box output power limits. In terms of transmission ratio design, this study takes into account the car's power, balancing acceleration ability and maximum speed to determine an optimal transmission ratio through theoretical calculations and empirical values. Furthermore, it explores how to optimize overall drive system performance by considering technical parameters, power requirements, economic considerations of each system assembly, and validates these findings through software simulations. Notably, significant improvements in reliability are achieved with the newly designed transmission system and wheel rim system while also proposing lightweighting methods for key components. We have carried out extensive verification in both simulation and real vehicle

Wang, Liuxin, Li, Chengfeng, Zhu, Xiran, Liu, Minmin

Systematic Design Considerations of Motor Selections for EV Powertrain Abstract

2025-01-8508

04/01/2025

As one of the most important design choices in the powertrain design cycle, motor selection is conventionally performed according to given automotive requirements. Motor-related powertrain design parameters like gear ratio, power output ratio between different axles, are excluded from the motor design process. In this paper, three comparative studies are performed to investigate the impact of these motor-related powertrain design parameters on the motor performance and the weight/cost/efficiency of the entire EV powertrain. In the first study, three PM motor designs—characterized by high, medium, and low rated speeds—will be assessed for a two-axle EV using various gear ratio configurations. The same motor design will be used for both axles. In the second study, five motor designs with varying power and ratings (PM, non-PM) but identical rated speeds will be evaluated for a two-axle EV, permitting different power ratings for the front and rear axles. The design trade-offs between motor

Movahed, Ehsan, Godbehere, Jonathan, Jia, Yijiang

An Efficient CAE-Driven Weight Optimization Approach for an Existing Vehicle BIW

2025-01-8738

04/01/2025

Most of the plug-in electric vehicles (EVs) available today are retrofitted versions of the corresponding co-existing higher-volume internal combustion (IC) engine-based models. In order to make the former category of vehicles more attractive in terms of driving range, a Li-ion battery pack of substantive energy capacity (in kWh) is needed. The latter requirement is likely to add to the weight of an EV in relation to its conventional counterpart. This potential weight increase can to an extent be checked by aggressively scouring for opportunities for weight reduction of the BIW (Body-In-White) of the original platform. The current work suggests a practical and efficient CAE (Computer-Aided Engineering)-driven approach for weight optimization of the BIW of a vehicle without affecting its styling, modal frequencies and front crashworthiness performance. It is assumed that there would be no major changes to manufacturing resources associated with the current design although limited

Deb, Anindya, Zhu, Feng

Reduced Order Model for Viscosity and Mass Density Sensing by A U-Shaped Wire

2025-01-8472

04/01/2025

This paper focuses on the basic principle of measuring viscosity and density with U-shaped tungsten wire sensor, and develops a model for measuring liquid viscosity and density with the help of oscillating ball model. Firstly, the working mechanism of the wire resonator is deeply analyzed. Then, by reducing the order of the fluid dynamic function, a simplified model is established for measuring the viscosity and density of liquid with U-shaped tungsten resonator. The experimental results show that the maximum error of viscosity is 7.22% and the average error is 2.81% when the viscosity ranges from 4.526mPa.s to 62.01mPa.s. In the range of 0.8486g/cm3 to 0.8711g/cm3, the maximum density error is 7.00% and the average density error is 1.89%. In summary, the simplified model proposed in this paper can accurately measure the viscosity and density of liquids.

Shan, Baoquan, Shen, Yitao, Yang, Jianguo, Zhang, Zhaoying, Wu, Dehong, Zhao, Yingke

Automatic Generation of HVAC Ducting System Designs Using Topology and Shape Optimization

2025-01-8656

04/01/2025

In this paper, the topology and shape optimization of a vehicle Heating, Ventilation, and Air Conditioning (HVAC) system is presented. The CFD and optimization methodologies are implemented within AcuSolve™ software. The topology optimization algorithm computes the geometry, where the design domain is parameterized with a field of porosity design variables which indicates the material, fluid or solid, throughout the domain. The optimization is performed using the continuous adjoint approach by the Galerkin Least Squares solver on which the AcuSolve™ solver is based. The design is further improved by using shape optimization. To optimize the geometrical shape, a combination of smooth perturbations, in terms of so called morph shapes, are used to deform the geometrical shape in the optimization algorithm. To this end, a parameterization of the design space is done using a moderate number of design variables, each associated with a morph shape. The two optimization phases are connected by

Papadimitriou, Dimitrios, Sandboge, Robert

Research on Energy Recovery Strategy in Braking of Electric Tractor-Semitrailer

2025-01-8290

04/01/2025

Tractor-semitrailers play an important role in the transportation industry. However, global warming and the rapid advancement of energy technologies have driven the transformation of high-emission vehicles, such as tractor-semitrailers, to be powered by new energy sources in order to achieve goals related to energy conservation, emission reduction, and cost savings. By using the motor as the primary driving force, the energy recovered during braking or coasting can be converted into electricity and stored in the battery for later use. While much research has been conducted on braking control and energy recovery for passenger cars, there is limited research on tractor-semitrailers. Additionally, the jackknife is a critical factor to consider under high-speed conditions. To investigate the braking energy recovery of electric tractor-semitrailers, tire and motor models were developed based on the turning and braking conditions of such vehicles. Taking into account the load transfer effect

Chen, Runping, Duan, Yupeng

MDO Approach for Design Synthesis of Automotive Interior Components Subjected to Conflicting Functional Requirements

2025-01-8649

04/01/2025

Light weighting has been one of the focus areas in automotive design, which has assumed greater importance for electric vehicles due to sensitivity of electric range to mass of the vehicle and increased cost of the battery packs to meet range target with increasing mass of vehicle. Mass of vehicle interior components have significant impact of overall vehicle mass due to cascading effect. Hence mass of such components must be minimized during design synthesis, where multiple design configurations may be explored with tradeoffs with regard to meeting functional requirements which are often conflicting. Assist handle bracket is one of such components in vehicle which needs to meet mandatory safety requirement of FMVSS 201U that requires the bracket to be soft. At the same time, the bracket needs to have adequate stiffness and strength to meet perceived quality and durability requirements. These are conflicting requirements which are often difficult to meet using manual design iterations

R, Rajapandian, Koppaka, Vinaya

Control Trajectory Optimization of Electric Vehicle Heat Pump-Based Cabin Heating System

2025-01-8144

04/01/2025

Optimal control of battery electric vehicle thermal management systems is essential for maximizi ng the driving range in extreme weather conditions. Vehicles equipped with advanced heating, ventilation and air-conditioning (HVAC) systems based on heat pumps with secondary coolant loops are more challenging to control due to actuator redundancy and increased thermal inertia. This paper presents the dynamic programming (DP)-based offline control trajectory optimization of heat pump-based HVAC aimed at maximizing thermal comfort and energy efficiency. Besides deriving benchmark results, the goal of trajectory optimization is to gain insights for practical hierarchical control strategy modifications to further improve real-time controllers’ performance. DP optimizes cabin inlet air temperature and flow rate to set the trade-off between thermal comfort and energy efficiency while considering the nonlinear dynamics and operating limits of HVAC system in addition to typically considered cabin

Cvok, Ivan, Deur, Josko

Different Methods-Based Curvature Estimation and its Effect on the Lane Centering Performance

2025-01-8055

04/01/2025

Lateral driving features used in Advanced Driver Assistance Systems (ADAS) rely heavily on inputs from the vehicle's surroundings and state information. A critical component of this state information is the curvature of the Ego Vehicle, which significantly influences performance. Curvature is often utilized in lateral trajectory generation and serves as a key element of the lateral motion controller. However, obtaining accurate curvature data is challenging due to the scarcity of sensors that directly measure this parameter. Instead, curvature is typically derived from various vehicle signals and additional sensor data, often employing sophisticated estimation techniques. This paper discusses several methods for estimating vehicle curvature using diverse information sources, evaluates their effectiveness, and investigates their impact on lateral feature performance, while analyzing the associated challenges and advantages.

Awathe, Arpit, Varunjikar, Tejas, Jain, Arihant

Research on the Thermal Performance of Thick Film Heater for Electric Vehicle Battery

2025-01-8154

04/01/2025

A specific thick film heater (TFH) for electric vehicles is investigaed in this study, and its three dimensional heat tansfer analysis model is estab-lished. The heat transfer and fluid performance of the TFH is analyzed using a computational fluid dynamics soft-ware. The performance of TFH is measured on a test bench, and the measured data is used to validate the developed model. Using the established model, the heating efficiency of TFH is studied for different inlet temperatures and flow rates, and the influence of the fin spoiler structure on TFH heating efficiency and the heating board temperature is investigated. The result indicates that the spoiler structure has a large effect on the board heating temperature, but has little effect on the heating efficiency. An orthogonal experimental design method is used to optimize the design of the fins and water channels, and the purpose is to reduce the board heating temperature for preventing over burning. Under the 25°C inlet

Guan, Wenzhe, Guo, Yiming, Wu, Xiaoyong, Wang, Dongdong, Shangguan, Wen-Bin

Optimal Investigation About Cab of BSC Racing Car Based on Ergonomics

2025-01-8669

04/01/2025

In the Baja race, off-road vehicles need to run under a variety of real and complex off-road conditions such as pebble road, shell pit, stone bad road, hump, water puddle, etc. In the process of this high-intensity and high-concentration race, the unoptimized design of the cab in ergonomics will easily cause the driver's visual and handling fatigue, so that the driver's attention is not concentrated. Cause the occurrence of security accidents. Moreover, lower back pain, sciatic nerve discomfort, lumbar spine diseases and other occupational diseases are basically caused by uncomfortable driving posture and unreasonable control matching, and these have a lot to do with unreasonable ergonomic design. In order to solve these problems, firstly establish the human body model of the driver, and then build the BSC racing car model by using 3D modeling software Catia. Then use the ergonomics simulation software Jack to analyze the visibility, accessibility and comfort. Based on the simulation

Liu, Yuzhou, Liu, Silang

Active Suspension System Optimal Control Strategy Considering Vehicle Ride Comfort and Road Maintenance Capability

2025-01-8277

04/01/2025

The suspension system could transmit and filter the forces between the body and road surface, which affects vehicle ride comfort and road maintenance capability. Compared to traditional passive and semi-active suspension, Active Suspension Systems (ASS) could automatically adjust the suspension stiffness, damping force, and body height according to changes in the vehicle's load distribution, travelling speed, and braking action through the addition of a power source such as a linear motor. Although the existing advanced control methods could help to effectively improve the driving quality of vehicles equipped with ASS, the conflict between ride comfort and road maintenance capacity is still a difficult problem to be solved. Therefore, an Active Suspension System optimal control strategy considering vehicle ride comfort and road maintenance capability is proposed in this paper. Firstly, a quarter ASS model and a road model are respectively developed based on the system dynamics

Zhu, Bing, Zhang, Chaohui, Sun, Jihang, Wang, Shiwei, Ding, Shuwei, Li, Lun, Chen, Zhicheng

Multi-Objective Optimization of the Electric Bus Body Frame Based on the PSO-BP-MOMVO Approach

2025-01-8652

04/01/2025

This paper focuses on the design optimization of a commercial electric bus body frame with steel-aluminum heterogeneous material orienting the performances of strength, crashworthiness and body lightweight. First, the finite element (FE) model of the body frame is established for static and side impact analysis, and the body frame is partitioned into several regions according to the thickness distribution of the components. The thicknesses of each region are regarded as the variables for the sensitivity analysis by combining the relative sensitivity method and the Sobol index method, and nine variables to which the performance indexes are more sensitive are selected as the final design variables for design optimization. Then the surrogate models are developed, and in order to improve the accuracy of the surrogate models, a model-constructing method called the particle swarm optimization BP neural network (PSO-BP) data regression prediction is proposed and formulated. In this method

Yang, Xiujian, Tian, Dekuan, Cui, Yan, Lin, Qiang, Song, Yi

Predictive Steering Angle Generation Algorithm for High Efficiency Vehicle’s Path Optimization

2025-01-8791

04/01/2025

Predictive performance simulation of a high-efficiency lightweight vehicle is performed through development of a multi-physics MATLAB Simulink model including advanced vehicle dynamics. The vehicle is put into a three-dimensional representation of the racetrack, including its dimensions, slope, banking, and adhesion coefficient along the model space, elaborated from the track GPS data points. The vehicle’s reference trajectory is not priorly provided to the model at the simulation start as, during run-time, a predictive Steering Angle Generation (SAG) algorithm based on Nonlinear Model Predictive Control (NMPC) computes the optimal steering angle input needed to drive the vehicle on the track within its limits. Computation is based on fast predictive simulations of a simplified version of dynamics modelling of the vehicle. Each single simulation exploits a different possible steering angle to be applied by the virtual driver, starting from the initial conditions given by the actual

De Carlo, Matteo, Manzone, Simone, de Carvalho Pinheiro, Henrique, Carello, Massimiliana

A Novel Nonlinear Model Predictive Control Strategy for a Class of Nonlinear Systems with Multiple Actuators’ Response Time-Delays

2025-01-8028

04/01/2025

This paper investigates the problem of nonlinear model predictive control (NMPC) strategy for a class of nonlinear systems with multiple actuators’ response time-delays. Conventional approaches that incorporate these time-delays into the NMPC formulation typically result in a significant increase in the optimization problem's scale. To address these problems, we propose a novel NMPC strategy. In the first stage, the NMPC strategy is designed for the nonlinear system without considering actuator’s response time-delay, thereby maintaining the original scale of the optimization problem. The optimal control sequence derived from this NMPC is then fitted to a time-continuous polynomial function, serving as a reference signal for the actuators' response time-delay models. In the second stage, combining inverse model and inverse Laplace transform techniques, a novel inverse model compensation control (IMCC) strategy is designed for actuators’ response time-delays. This IMCC strategy enables

Wang, Bin

Correlation Study of Low-Frequency Engine Order Noise Prediction at Compressor Inlet for a PHEV and Resonator Tuning

2025-01-8643

04/01/2025

Sound pollution has become one of the major environmental concerns for the global automotive industry. Air Induction System (AIS) plays an important role in engine performance and vehicle noise. An ideal design of AIS provides debris-free air for combustion and reduces the engine noise that is heard while snorkeling. This work aims to correlate low-frequency engine order noise prediction at the compressor inlet and snorkel inlet for a 2.0L I4 turbo engine of a Plug-in hybrid vehicle (PHEV) for better acoustic performance without compromising on engine performance. 1D simulation software GT-POWER, Simcenter 3D, and Hypermesh are used for this work. Transmission loss (TL) results with respect to the frequency of the air-box with ducts and intake manifold with charge air cooler are plotted from 0 to 1000 Hz. The air intake system TL results show a good correlation between 3D and 1D till 600 Hz. Compressor and snorkel noise simulation results, especially the firing order and its harmonic

Dixit, Manish

Design of a Stability Compensator to Optimize Steering Feel in Electric Power Steering Systems

2025-01-8750

04/01/2025

The speed-dependent steering assistance is a fundamental function in electric power steering (EPS) systems. However, excessive levels of steering assistance can result in system instability, causing steering oscillations that compromise steering safety. Consequently, ensuring steering stability has become a primary focus in EPS development. Currently, the design of stability compensators for speed-dependent steering assistance has primarily focused on achieving system stability, often neglecting the attenuation of the designed assist gain by the compensator. In this paper, a novel method for the design of stability compensators within speed-dependent steering assistance is presented, aimed at ensuring system stability while reducing the attenuation of the designed assist gain by the compensator. First, a dynamic model of the EPS system is established, incorporating system inertia and viscous damping. The frequency response characteristics of the EPS system are obtained through vehicle

Kong, Yi, Wei, Zhengjun, Duan, Xiaocheng, Shangguan, Wen-Bin

Verification of the Impact of Coefficient of Drag Variation Due to Natural Wind on Fuel Consumption Based on Actual Driving Data

2025-01-8778

04/01/2025

The natural wind experienced on public roads can increase the yaw angle and therefore drag coefficient (CD), which may contribute to the discrepancy between catalog fuel economy and actual fuel economy. The impact of yaw characteristics alone on fuel economy during actual driving has not been verified or proven as it is difficult to obtain actual driving data under uniform conditions. For this reason, shape optimization is normally performed at zero-yaw through the aerodynamic development phases. In this paper, two vehicles with different yaw sensitivity characteristics are driven simultaneously, and fuel economy measurements are performed simultaneously with ambient airflow, environment, and vehicle conditions. The results where the conditions of the two vehicles match are extracted to clarify the impact of the differences of yaw characteristics on fuel economy. The obtained results matched the values predicted by theoretical calculations for the impact of yaw angle on fuel economy

Onishi, Yasuyuki, Nichols, Larry, Metka, Matt, masumitsu, Yasutaka, Inoue, Taisuke

AI-Enhanced CAE Simulations: A Revolutionary Approach to Automotive Design and Engineering

2025-01-8241

04/01/2025

In the automotive industry, the durability and thermal analysis of components significantly impact vehicle component robustness and customer satisfaction. Traditional computer-aided engineering (CAE) methods, while effective, often involve extensive design iterations and troubleshooting, leading to prolonged development times and increased costs. The integration of artificial intelligence (AI) and machine learning (ML) into the CAE process presents a transformative solution to these challenges. By leveraging AI and ML, the durability simulation time of automobile components is significantly enhanced. Altair’s Physics AI tool utilizes historical CAE data to train ML models, enabling accurate predictions of model performance in terms of durability and stiffness. This reduces the necessity for multiple simulations, thereby decreasing CAE model design and solution completion times by 30%. By predicting potential issues early in the design phase, AI and ML allow engineers to make informed

Patil, Amol, Sonavane, Pravinkumar

Influence of Prediction Horizon on Trajectory Optimization for Autonomous Vehicle Maneuvers

2025-01-8309

04/01/2025

The advent of autonomous vehicles (AVs) marks a revolutionizing transformation in transportation, with the potential to significantly enhance safety and efficiency through advanced trajectory planning and optimization capabilities. A crucial component in realizing these benefits is the use of optimization-based control strategies for real-time path planning. Among these, model predictive path integral (MPPI) control algorithms stand out as a sampling-based stochastic control method, offering precise control in dynamic environments through random sampling. While the MPPI control has shown promising results, there has been limited investigation into the effects of different prediction horizon times on control performance of these algorithms. This paper seeks to address this gap by proposing a multi-input MPPI control method for AVs using a single-track vehicle dynamic model. Our research focuses on the influence of various prediction horizon times on trajectory optimization during lane

Yang, Yanwen, Negash, Natnael, Yang, James

Modeling and Evaluation of FSAE Vehicle Cockpit Ergonomics

2025-01-8610

04/01/2025

This paper seeks to define an analytical approach to ergonomic cockpit design for SAE formula style vehicles. The proposed approach uses a data driven driver model based on RAMSIS ergonomic FEA that considers the discomfort, fatigue, and force availability to evaluate cockpit designs that are generated considering defined constraint inputs, such as driver gender and size. The multifunctional model is applicable to various settings of vehicle design and is tuned toward proving performance in operation tasks, as well as setting the groundwork for a multi-variable optimization to determine the preferred driver controls positions for minimum effort and fatigue. In this initial research, RAMSIS ergonomic software is used to generate fatigue and joint discomfort data related to individual joint angles. Anthropometric data is used to calculate the proportional limb lengths from an individual’s gender and height percentile. The optimization function works by selecting a range of driver

Mayor, J.Rhett, Bezaitis, Megan, Oromi, Negar, Winters, Emily, Repp, Alex

Simulation and Parameter Optimization of Commercial Vehicle Cab Suspension System

2025-01-8268

04/01/2025

Taking a commercial vehicle cab suspension system as the research focus, a rigid-flexible coupled dynamics model was established based on the nonlinear characteristics of the integrated damper air spring and bushings. Time-domain vibration acceleration signals were acquired at the connection points between the frame, cab, and suspension. The vibration signals at the frame and suspension connection points were input into the simulation model, where the vibration responses at the cab and suspension connection points were calculated and analyzed using the established cab suspension system model. The accuracy of the model was verified by comparing the simulation results with experimental data. The established cab suspension system model was further used to evaluate human vibration comfort within the cab, following national standards for subjective human perception. A piecewise polynomial function was employed to fit the stiffness-damping characteristics of the integrated damper air spring

Hao, Qi, Zhu, Yuntao, Sun, Wen, Sun, Kai, Sun, Zhiyong, Huang, Yu, Zhen, Ran, Shangguan, Wen-Bin

Design Parameter Impact of Wind-Averaged Drag Optimization

2025-01-8772

04/01/2025

With the increasing prevalence of electric vehicles (EVs), decreasing vehicle drag is of upmost importance, as range is a primary consideration for customers and has a direct bearing on the cost of the vehicle. While the relationship between drag and range is well understood, there exists a discrepancy between the label range and the real-world range experienced by customers. One of the factors influencing the difference is the ambient wind condition that modifies the resultant air speed and yaw angle, which is typically minimized during SAE coast-down testing. The following study implements a singular wind-averaged drag (WAD) coefficient which is derived from a 3-point yaw curve to show the impact of yaw as compared to the zero-yaw condition. This leads to an interesting dilemma for the vehicle aerodynamicist: whether to optimize the vehicle's exterior shape for low wind (zero yaw) conditions or for real-world conditions where the ambient wind generally produces a few degrees of yaw

Kaminski, Meghan, D'Hooge, Andrew, Borton, Zackery

Efficient Sidewalk Route Planning on Aerial Images with Cost-Based A* and Mini-Max Objective Function

2025-01-8032

04/01/2025

With the growing diversification of modern urban transportation options, such as delivery robots, patrol robots, service robots, E-bikes, and E-scooters, sidewalks have gained newfound importance as critical features of High-Definition (HD) Maps. Since these emerging modes of transportation are designed to operate on sidewalks to ensure public safety, there is an urgent need for efficient and optimal sidewalk routing plans for autonomous driving systems. This paper proposed a sidewalk route planning method using a cost-based A* algorithm and a mini-max-based objective function for optimal routes. The proposed cost-based A* route planning algorithm can generate different routes based on the costs of different terrains (sidewalks and crosswalks), and the objective function can produce an efficient route for different routing scenarios or preferences while considering both travelling distance and safety levels. This paper’s work is meant to fill the gap in efficient route planning for

Bao, Zhibin, Lang, Haoxiang, Lin, Xianke

Research on Control Algorithm for Active Rear Wheel Steering System of Passenger Cars

2025-01-8755

04/01/2025

With the continuous development of automobile technology, vehicle handling performance and safety have become increasingly critical research areas. The active rear-wheel (ARW) steering system, a technology that significantly enhances vehicle dynamics and driving stability, has garnered widespread attention. By coordinating front-wheel steering with rear-wheel angle adjustments, ARW improves handling flexibility and stability, particularly during high-speed driving and under extreme conditions. Therefore, designing an efficient ARW control algorithm and optimizing its performance are vital to enhancing a vehicle's overall handling capability. This study delves into the control algorithm design and performance optimization of ARW. First, a comprehensive vehicle dynamics model is constructed to provide a solid theoretical basis for developing control algorithms. Next, optimal control theory is applied to regulate the rear-wheel steering angle, and an LQR control strategy with variable

Zhang, Yi, Zheng, Hongyu, Kaku, Chuyo, Zong, Changfu, Zhang, Yuzhou

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