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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
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
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
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
In this paper, based on the cylindrical flow theory of incompressible viscous fluids and the equivalent circuit model of resonant sensing elements, a theoretical model for the measurement of liquid viscosity with a U-Shaped tungsten wire resonance sensor was established. This model can measure the liquid viscosity independently without liquid density or coupled detection of liquid density. The experimental results show that the decoupling of liquid viscosity and its density can be achieved at Re<1. The liquid viscosity is strongly linear with the resonant conductance. The viscosity measurement error is less than 7.24% in the viscosity range of 7.235cP to 85.2cP.
Shan, BaoquanShen, YitaoYang, JianguoWu, Dehong
This research experimentally investigates the spray vaporization of high-pressure dimethyl ether (DME) using a single-hole research injector focusing on nominal operating conditions from the Engine Combustion Network (ECN). DME is a synthetic alternative to diesel fuel, offering both high reactivity and potential reductions in particulate emissions. Because DME only features half of the energy density of diesel fuel, a specifically designed fuel system with a high mass flow rate to meet the energy delivery requirements is needed. The unique physical properties of DME, including higher vapor pressure and lower viscosity, introduce challenges like cavitation and unique evaporation characteristics that deviate from typical diesel fuel. These features are likely to lead to differences in fuel mixing and combustion. This study aims to provide detailed experimental data on DME spray characteristics under engine-like conditions, helping the development of predictive CFD models for optimal
Yi, JunghwaWan, KevinPickett, LyleManin, Julien
Toyota Motor Corporation pursuing an omnidirectional strategy that includes battery electric vehicle (BEV), plug-in hybrid electric vehicle (PHEV), and fuel cell electric vehicle (FCEV) to accelerate electrification. One of the technical challenges with our xEV batteries which feature good degradation resistance and long battery life, is that regenerative braking cannot be fully effective due to the decrease in regenerative power in some situations, such as low battery temperature. For the electrified vehicles with an internal combustion engine such as PHEVs, the solution has been running the engine to increase deceleration through engine braking during coasting. PHEVs are expected to extend their cruising range and enhance EV driving experience as "Practical BEVs". While increasing battery capacity and enhancing convenience, the restrictions on EV driving opportunity due to low battery temperature may negatively affect PHEV’s appealing. As an alternative, introducing a battery heater
Hoshino, Yu
In internal combustion engines, hydrogen is considered as one of the most promising alternatives to replace fossil fuels and reduce CO2 emissions. In such a context, traditional injectors for hydrocarbon fuels are currently being tailored to be used with hydrogen, or a single-hole/multi-hole cap mounted at the injector tip was used to obtain better mixing and air utilization. Nevertheless, the hydrogen injection can be accompanied by the formation of highly under-expanded jets and will significantly influence the downstream mixing process. Therefore, in order to achieve a better understanding on hydrogen-air mixture, this work aims to numerically investigate the influence of the nozzle geometry on the jet behaviors in the near nozzle region. The nozzle diameter ranges from 0.1 mm to 2.0 mm and the nozzle length is from 1mm to 2mm. The injection pressure ranges from 10 bar to 70 bar. As the boundary condition varied, differences in both the internal flow of different nozzle structures
Jiahui, LangLi, YanfeiXu, LubingXiao, MaShuai, Shijin
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, JamesTorcellini, SabrinaKhorran, AaronHall, Mark
Spray washing is commonly used in car manufacturing to clean and prepare surfaces for subsequent processes like coating and painting. It uses high-pressure spray to deliver cleaning solutions or water onto vehicle surfaces to remove dirt, oils, metal shavings, and contaminants. For optimal washing quality, it is important to have proper nozzle arrangements, spray configuration, and vehicle positioning. Numerical simulations can be used to minimize the trial-and-error process and improve the quality. Spray washing involves strong discontinuities, fragmentation, violent free-surface changes, and complex multiphase flow, which are difficult to simulate using conventional grid-based methods. Lagrangian differencing dynamics (LDD) is a novel numerical method which has the features of being Lagrangian, meshless, and second-order accurate. It employs a meshless finite difference approximation scheme over scattered points and solves the incompressible Navier-Stokes equations in an implicit way
Panov, Dmitrii OlegovichZhu, HuaxiangBasic, JosipZhang, LingranChampaneriya, VrajeshSaghatchi, RoozbehPeng, ChongKotian, AkhileshAndo, Yuya
Due to the high-power density, high torque rating, low torque ripples and fault-tolerant capability, the Dual Three-Phase Permanent Magnet Synchronous Motor (DTP-PMSM) has recently emerged as a feasible alternative for automotive applications. However, it comes with its own challenge of increased losses at low torque due to the use of 6-phase inverter or two three-phase inverters. The DTP-PMSM drive model can be designed to function in two operating modes, double-channel (dual three-phase) mode with both the inverters operating, and single-channel (three-phase) with one of the two inverters shut down. This paper proposed an efficiency analysis between single channel and double channel modes in a DTP-PMSM drive. A simulation model is prepared to calculate efficiency, and the losses associated with different parts of battery fed DTP-PMSM drive system operated in both modes. Detailed loss model is simulated to represent efficiency of a battery-fed DTP-PMSM drive system. Both single
Sun, FengyangPradhan, SubarniYang, JingruNahid-Mobarakeh, BabakValencia Garcia, Diego FernandoMavalankar, DrushanAllocco, Alessandro
In order to manage the serious global environmental problems, the automobile industry is rapidly shifting to electric vehicles (EVs) which have a heavier weight and a more rearward weight distribution. To secure the handling and stability of such vehicles, understanding of the fundamental principles of vehicle dynamics is inevitable for designing their performance. Although vehicle dynamics primarily concerns planar motion, the accompanying roll motion also influences this planar motion as well as the driver's subjective evaluation. This roll motion has long been discussed through various parameter studies, and so on. However, there is very few research that treats vehicle sprung mass behavior as “vibration modes”, and this perspective has long been an unexplored area of vehicle dynamics. In this report, we propose a method to analytically extract the vibration modes of the sprung mass by applying modal analysis techniques to the governing equations of vehicle handling and stability
Kusaka, KaoruYuhara, Takahiro
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, PrathameshTovar, Andres
Less costs and higher efficiency may be constant technological pursuit. Despite the great success, data-driven AI development still requires multiple stages such as data collection, cleaning, annotation, training, and deployment to work together. We expect an end-to-end style development process that can integrate these processes, achieving an automatic data production and algorithm development process that can work with just clicks of the mouse. For this purpose, we explore an end-to-end style parking algorithm development pipeline based on procedural parking scenario synthetic data generation. Our approach allows for the automated generation of parking scenarios according to input parameters, such as scene construction, static and dynamic obstacles arrangement, material textures modification, and background changes. It then combines with the ego-vehicle trajectories into the scenarios to render high-quality images and corresponding label data based on Blender software. Utilizing
Li, JianWang, HanchaoZhang, SongMeng, ChaoRui, Zhang
Emerging automotive technologies like advanced driver assistance systems (ADAS) and automated driving systems (ADS) hold promise for improving safety for the traveling public; however, effective verification and validation (V&V) of these systems has proven to be challenging. Traditional testing methodologies may serve in limited cases for systems exhibiting low levels of automation, but recent studies show that these systems that have been brought to market perform poorly in practice. Further, these traditional methods do not serve for testing systems with high levels of automation where a human driver simply serves as a fallback ready user or is out of the loop altogether. New V&V methods are required to assess whether these systems can perform their intended functions in their intended operating environments, and to assess whether they can do so safely across the expansive and variable operating space. This paper presents an overview of ADAS and ADS challenges and novel approaches to
Thorn, EricKnisley, VeronicaAuchter, Joseph
Vehicles with SAE J3016TM Level 3 systems are exposed to road infrastructure, Vulnerable Road Users (VRUs), traffic and other actors on roadways. Hence safe deployment of Level 3 systems is of paramount importance. One aspect of safe deployment of SAE Level 3 systems is the application of functional safety (ISO 26262) to their design, development, integration, and testing. This ensures freedom from unreasonable risk, in the event of a system failure and sufficient provisions to maintain Dynamic Driving Task (DDT) and to initiate Minimum Risk Maneuver (MRM), in the presence of random hardware and systematic failures. This paper explores leveraging ISO 26262 standard to develop architectural requirements for enabling SAE Level 3 systems to maintain DDT and MRM during fault conditions and outlines the importance of fail-operability for Level 3 systems, from a functional safety perspective. At a high-level, UN Regulation No. 157 – Automated Lane Keeping Systems (ALKS) is used as a baseline
Mudunuri, Venkateswara RajuJayakumar, Namitha
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, HaosenLi, YihangWu, Guangqiang
As the high-quality development of the new energy vehicle (NEV) and traction battery industries, the safety of traction batteries has become a global focus. Typically mounted at the bottom of NEVs, traction battery systems are particularly vulnerable to mechanical damage caused by bottom impacts, posing serious safety risks. This study investigates the damage sustained by NEV traction battery systems during bottom impact collisions, using computer tomography analysis to detail the damage mechanisms. The findings provide valuable data to enhance the safety and protective performance of traction batteries under such scenarios.
Yan, PengfeiWang, FangMa, TianyiHan, CeHe, Gaiyun
Accurate battery capacity estimation is critical for ensuring the safe and reliable operation of electric vehicles (EVs) and addressing user range anxiety. However, predicting battery health is challenging due to the non-linearity, non-measurability, and complex multi-stress operating conditions that characterize battery performance. Incremental capacity curves and electrochemical impedance spectroscopy (EIS) are effective tools for reflecting battery aging, but their practical application has limitations. This paper presents a novel method for battery capacity estimation using charging segment data derived from real-world operating conditions monitored by the vehicle's Battery Management System (BMS). The proposed approach begins with a detailed statistical analysis of voltage data to determine optimal charging capacity intervals and involves selecting appropriate voltage ranges to compute equivalent full-charge capacities. Experimental tests are performed to measure battery charging
Tao, SiyiZhu, JiangongLi, YuanChang, WeiDai, HaifengWei, Xuezhe
Based on the harmonic current injection method used to suppress the torsional vibration of the electric drive system, the selection of the phase and amplitude of the harmonic current based on vibration and noise has been explored in this paper. Through the adoption of the active harmonic current injection method, additional torque fluctuations are generated by actively injecting harmonic currents of specific amplitudes and phases, and closed-loop control is carried out to counteract the torque fluctuations of the motor body. The selection of the magnitude of the injected harmonic current is crucial and plays a vital role in the reduction of torque ripple. Incorrect harmonic currents may not achieve the optimal torque ripple suppression effect or even increase the motor torque ripple. Since the actively injected harmonic current is used to counteract the torque ripple caused by the magnetic flux linkage harmonics of the motor body, the target harmonic current command is very important
Jing, JunchaoZhang, JunzhiLiu, YiqiangHuang, WeishanDai, Zhengxing