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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, AndreasHärtl, MartinJaensch, Malte
With the global issue of fossil fuel scarcity and the greenhouse effect, interest in electric vehicles (EVs) has surged recently. At that stage, because of the constraints of the energy density and battery performance degradation in low-temperature conditions, the mileage of EVs has been criticized. To guarantee battery performance, a battery thermal management system (BTMS) is applied to ensure battery operates in a suitable temperature range. Currently, in the industry, a settled temperature interval is set as criteria of positive thermal management activation, which is robust but leads to energy waste. BTMS has a kilowatt-level power usage under high- and low-temperature environments. Optimizing the BTMS control strategy becomes a potential solution to reduce energy consumption and overcome mileage issues. An appropriate system simulation model provides an effective tool to evaluate different BTMS control strategies. In this study, a predictive BTMS control strategy, which adjusts
Huang, ZhipeiChen, JiangboTang, Hai
Increasing global pressure to reduce anthropogenic carbon emissions has inspired a transition from conventional petroleum-fueled internal combustion engines to alternative powertrains, including battery electric vehicles (EVs) and hybrids. Hybrids offer a promising solution for emissions reduction by addressing the limitations of pure EVs such as slow recharge and range anxiety. In a previous research endeavor, a prototype high-power density generator was meticulously designed, fabricated, and subjected to testing. This generator incorporated a compact permanent magnet brushless dynamo and a diminutive single-cylinder two-stroke engine with low-technology constructions. This prototype generated 8.5 kW of electrical power while maintaining a lightweight profile at 21 kg. This study investigates the performance and emissions reduction potential by adapting the prototype to operate on methanol fuel. Performance and emissions were experimentally evaluated under varying operating conditions
Gore, MattNonavinakere Vinod, KaushikFang, Tiegang
Thermal runaway in battery cells presents a critical safety concern, emphasizing the need for a thorough understanding of thermal behavior to enhance battery safety and performance. This study introduces a newly developed AutoLion 3D thermal runaway model, which builds on the earlier AutoLion 1D framework and offers significantly faster computational performance compared to traditional CFD models. The model is validated through simulations of the heat-wait-search mode of the Accelerating Rate Calorimeter (ARC), accurately predicting thermal runaway by matching experimental temperature profiles from peer-reviewed studies. Once validated, the model is employed to investigate the thermal behavior of 3D LFPO cells under controlled heating conditions, applying heat to one or more surfaces at a time while modeling heat transfer from non-heated surfaces. The primary objective is to understand how these localized heating patterns impact temperature profiles, including average core temperatures
Hariharan, DeivanayagamGundlapally, Santhosh
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, SrikanthSousa Schulman, DanielKerr, BradleyYin, SiyuanWachsman, Michael BenPienkny, Jedidiah Ethan ShapiroJalgaonkar, Nishant M.Awtar, Shorya
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, JunZhang, KaidiShi, JunweiYang, WenmiaoZhang, YunqingWu, Jinglai
Nonlinearities in mechanical systems pose significant challenges for efficiently solving multi-body dynamics (MBD) problems. Although simulations of traditional mechanisms with perfect joints can be performed efficiently, joints in practical applications are often characterized by clearances, leading to reduced simulation efficiency and accuracy. Improving solver effectiveness is essential for simulating systems with nonlinearities. This paper explores the use of Julia, a high-performance open-source programming language, to solve MBD problems formulated as index-1 differential-algebraic equations (DAEs). Euler parameters (quaternions) are employed to represent the orientation of rigid bodies. To illustrate the method's adaptability in addressing non-standard joint types, both perfect and imperfect (with clearance or friction) planar roller guide joints are modeled alongside common perfect joints. A case study of a vehicle sliding door system is presented. The numerical results are
Tong, JiachiMeng, DejianLian, YuboGao, YunkaiYang, James
Trajectory tracking control is a key component of vehicle autonomous driving technology. Compared with traditional vehicles, Distributed Driven Electric Vehicle (DDEV) is an ideal vehicle for trajectory tracking control because of its high space utilization, redundant control freedom and fast system response. However, the chassis execution system of DDEV has a relatively large number of sensors, which significantly increases its probability of failure. In this paper, we propose a trajectory tracking fault-tolerant control method for DDEV considering steering actuator faults. Firstly, we establish the dynamic model of the steering actuator and the trajectory tracking model of DDEV. The model is linearized and discretized by using Taylor series expansion and forward Euler method. Next, considering multi-objective constraints such as motion comfort, actuator saturation and road adhesion boundary, the trajectory tracking control strategy of DDEV is designed by using model predictive
Wang, DepingLi, LunTeng, YuhanZhu, BingChen, Zhicheng
This SAE Aerospace Information Report (AIR) describes a method for assessing size dependent particle losses in a sampling and measurement system of specified geometry utilizing the non-volatile Particulate Matter (nvPM) mass and number concentrations measured at the end of the sampling system.1 The penetration functions of the sampling and measurement system may be determined either by measurement or by analytic computational methods. Loss mechanisms including thermophoretic (which has a very weak size dependence) and size dependent losses are considered in this method2 along with the uncertainties due to both measurement error and the assumptions of the method. The results of this system loss assessment allow development of estimated correction factors for nvPM mass and number concentrations to account for the system losses facilitating estimation of the nvPM mass and number at the engine exhaust nozzle exit plane. As the particle losses are size dependent, the magnitude of correction
E-31P Particulate Matter Committee
This study introduces an innovative torque vectoring control strategy designed to enhance ride comfort in autonomous electric vehicles. The approach seamlessly integrates steering and rear axle force control within a model predictive control (MPC) framework, enabling real-time optimization of comfort and handling performance. The proposed control method is applied to a two-rear-motor vehicle model, where the MPC algorithm adjusts steering angles and tire forces to minimize discomfort caused by yaw rate and lateral acceleration. Simulation results from a lane-change scenario demonstrate significant improvements in comfort metrics compared to conventional torque vectoring control strategies. The findings highlight the ability of the proposed method to significantly enhance ride comfort without compromising vehicle dynamics. This integrated and adaptive control strategy offers a promising solution for improving passenger satisfaction in autonomous electric vehicles, with potential
Zhao, BolinLou, BaichuanHe, XianqiXue, WanyingLv, Chen
Diesel combustion is a highly heterogeneous process in which the fuel must undergo several sub-processes after injection in order to release its heat through combustion. Prior to evaporation, computational fluid dynamic (CFD) simulations track the injected fuel mass using a Lagrangian frame of reference to determine the pathlines of the liquid fuel in the gaseous environment. However, after evaporation, when the fuel mass becomes part of the working fluid, it is no longer tracked in a Lagrangian reference frame as it undergoes its mixing and combustion processes. To gain deeper insights into the diesel combustion process, a methodology is proposed to track the evolution of fuel mass packets while in the gaseous state attaining a Lagrangian-esque description of the fuel’s evolution. This is achieved using the commercially available capabilities in Convergent Science’s CFD package, without requiring user-defined functions. The methodology is applied to a heavy-duty diesel engine and
Gohn, JamesKumar, MohitGainey, BrianLawler, Benjamin
Path tracking control, which is one of the most important foundations of autonomous driving, could help the vehicle to precisely and smoothly follow the preset path by actively adjusting the front wheel steering angle. Although there are a number of advanced control methods with simple structure and reliable robustness that could assist vehicles achieving path tracking, these controllers have many parameters to be calibrated, and there is a lack of guidance documents to help non-professional test site engineers quickly master calibration methods. Therefore, this paper proposes a parameter virtual calibration method based on the deep reinforcement learning, which provides an effective solution for parameter calibration of vehicle path tracking controller. Firstly, the vehicle trajectory tracking model is established through the kinematic relationship between the vehicle and the target path, combined with the Taylor series expansion linearization method. Next, a vehicle path tracking
Zhao, JianGuo, ChenghaoZhao, HuiChaoZhao, YongqiangYu, ZhenZhu, BingChen, Zhicheng
Fuel cell electric vehicles (FCEVs) are gaining increasing interest due to contributions to zero emissions and carbon neutrality. Thermal management of FCEVs is essential for fuel cell lifespan and vehicle driving performance, but there is a lack of specialized thermal balance test standards for FCEVs. Considering differences in heat generating mechanism between FCEVs and internal combustion engine vehicles (ICEVs), current thermal balance method for ICEVs should be amended to suit for FCHVs. This study discussed thermal balance performance of ICEV and FCHVs under various regulated test conditions based on thermal balance tests in wind tunnel of two FCEVs and an ICEV. FCEVs reported overheat risk during low-speed climbing test due to continuous large power output from fuel cell (FC). Frequent power source switches between FC and battery were observed under dual constrains of fuel cell temperature and battery state of charge (SOC). Significant temperature exceedance of ICEV occurred
Fang, YanhuaMin, YihangMing, ChenLi, HongtaoLi, DongshengHe, ChongMao, Zhifei
Trailer parking is a challenging task due to the unstable nature of the vehicle-trailer system in reverse motion and the unintuitive steering actions required at the vehicle to accomplish the parking maneuver. This paper presents a strategy to tackle this kind of maneuver with an advisory graphic aid to help the human driver with the task of manually backing up the vehicle-trailer system. A kinematic vehicle-trailer model is derived to describe the low-speed motion of the vehicle-trailer system, and its inverse kinematics is established by generating an equivalent virtual trailer axle steering command. The advisory system graphics is generated based on the inverse kinematics and displays the expected trailer orientation given the current vehicle steer angle and configuration (hitch angle). Simulation study and animation are set up to test the efficacy of the approach, where the user can select both vehicle speed and vehicle steering angle freely, which allows the user to stop the
Cao, XinchengChen, HaochongAksun Guvenc, BilinGuvenc, LeventLink, BrianHarber, JohnRichmond, PeterFan, ShihongYim, Dokyung
Precise state estimation during a lateral maneuver is not just a theoretical concept but a practical necessity. The performance of the Kalman filter is directly impacted by the comprehensive research and innovative approaches to counter nonlinearity and uncertainty. The use of machine learning in control theory is one such development that has significantly enhanced the effectiveness of our work. This paper provides an enhanced adaptive Kalman filter architecture with a neural network for a rapid obstacle avoidance maneuver. The proposed design exemplifies not just its effectiveness in terms of better state estimation in the presence of complex nonlinear vehicle dynamics and disturbances but also its potential downsides sometimes. Simulation results verify the same by ensuring a significant improvement to the traditional design, demonstrating better accuracy and the need for such advances in vehicle dynamics and control.
Sudhakhar, Monish Dev
This study focuses on the dynamic behavior and ride quality of three different modes of oil-gas interconnected suspension systems: fully interconnected mode, left-right interconnected mode, and independent mode. A multi-body dynamics model and a hydraulic model of the oil-gas suspension were established to evaluate the system's performance under various operating conditions. The research includes simulations of pitch and roll excitations, as well as ride comfort tests on different road surfaces, such as Class B roads and gravel roads. The analysis compares the effectiveness of the modes in suppressing pitch and roll movements and their impact on overall ride comfort. Results show that the independent mode outperforms the other two in minimizing roll, while the fully interconnected mode offers better pitch control but at the cost of reduced comfort. These findings provide valuable insights for the future design and optimization of oil-gas interconnected suspension systems, especially in
Xinrui, WangChen, ZixuanZhang, YunqingWu, Jinglai
This paper introduces a new approach for measuring changes in drag force across different vehicle configurations using an on-road testing technique. The method involves fixing the vehicle’s power across configurations and then measuring the resulting speed differences. A detailed formulation is provided on how these speed variations can be used to calculate the change in drag force for each configuration. The OBD II port is used to access and record additional data necessary for the calculations. The method is applied to both a passenger car and a commercial van to evaluate drag changes for different vehicle add-ons. A roof sign was installed at various positions along the roof of the vehicles to assess drag increases, while novel rear appendages were fitted to both vehicles to evaluate the resulting drag reductions. Detailed CFD simulations were performed on the road-tested configurations to compare the simulated drag changes with those measured on the road. Excellent agreement was
Connolly, Michael GerardIvankovic, AlojzO'Rourke, Malachy J.
As a distributed wire control brake system, the electro-mechanical brake (EMB) may face challenges due to the need to integrate the actuator in the limited space beside the wheel. During extended downhill braking, especially on wet roads with reduced adhesion, the EMB must operate at high intensity. The significant heat generated by friction can lead to thermal deformation of components, such as the lead screw, compromising braking stability. This paper focuses on pure electric light trucks and proposes a tandem composite braking method. This approach uses an eddy current retarder (ECR) or motor to provide basic braking torque, while the EMB supplies the dynamic portion of the braking torque, thereby alleviating the braking pressure on the EMB. First, a driver model, tire model, motor model, and braking models are developed based on the vehicle's longitudinal dynamics. In addition, the impact of various factors, such as rainfall intensity, road slope, ramp length and vehicle speed, on
Liu, WangZhang, YuXiao, HongbiaoShen, Leiming
The Guangzhou Automotive Group Co., Ltd (GAC Group) wind tunnel, located in Guangzhou, China, is a state-of-the-art facility that uniquely integrates world-class aerodynamic flow quality, acoustic capability, and thermal conditions into a single system for the development of passenger vehicles. This closed return, ¾ open jet wind tunnel features a nozzle with a cross-section of 20 m2 and a 2.5 MW fan, capable of delivering a maximum wind speed of 200 km/h. The wind tunnel is equipped with a ±90° turntable, a boundary layer control system, and a 5-belt moving ground plane system for aerodynamic tests. Comprehensive acoustic treatments in the test section and throughout the wind tunnel circuit establish a hemi-anechoic test environment with minimal background noise levels for acoustic tests. For thermal tests, the wind tunnel includes a 4-wheel chassis dynamometer system downstream of the turntable, with temperature control ranging from 20°C to 60°C and humidity control between 15% and
Bender, TrevorNasr Esfahani, VahidLiu, ZhengYang, HuiLi, ShuyaSong, XinLiu, ManMa, Zhijian
This paper presents findings on the use of data from next-generation Tire Pressure Monitoring Systems (TPMS), for estimating key tire states such as leak rates, load, and location, which are crucial for tire-predictive maintenance applications. Next-generation TPMS sensors provide a cost-effective and energy-efficient solution suitable for large-scale deployments. Unlike traditional TPMS, which primarily monitor tire pressure, the next-generation TPMS used in this study includes an additional capability to measure the tire's centerline footprint length (FPL). This feature offers significant added value by providing comprehensive insights into tire wear, load, and auto-location. These enhanced functionalities enable more effective tire management and predictive maintenance. This study collected vehicle and tire data from a passenger car hatchback equipped with next-generation TPMS sensors mounted on the inner liner of the tire. The data was analyzed to propose vehicle-tire physics
Sharma, SparshSon, Roman