Powertrain Fuel Consumption Modeling and Benchmark Analysis of a Parallel P4 Hybrid Electric Vehicle Using Dynamic Programming

The goal of this work is to develop a hybrid electric vehicle model that is suitable for use in a dynamic programming algorithm that provides the benchmark for optimal control of the hybrid powertrain. The benchmark analysis employs dynamic programming by backward induction to determine the globally optimal solution by solving the energy management problem starting at the final timestep and proceeding backwards in time. This method requires the development of a backwards facing model that propagates the wheel speed of the vehicle for the given drive cycle through the driveline components to determine the operating points of the powertrain. Although dynamic programming only searches the solution space within the feasible regions of operation, the benchmarking model must be solved for every admissible state at every timestep leading to strict requirements for runtime and memory. The backward facing model employs the quasi-static assumption of powertrain operation to reduce the fidelity of the model to accommodate these requirements. Verification and validation testing of the dynamic programming algorithm is conducted to ensure successful operation of the algorithm and to assess the validity of the determined control policy against a high-fidelity forward-facing vehicle model with a percent difference of fuel consumption of 1.2%. The benchmark analysis is conducted over multiple drive cycles to determine the optimal control policy that provides a benchmark for real-time algorithm development and determines control trends that can be used to improve existing algorithms. The optimal combined charge sustaining fuel economy of the vehicle is determined by the dynamic programming algorithm to be 32.99 MPG, a 52.6% increase over the stock 3.6 L 2019 Chevrolet Blazer.

OPTIMIZATION APPROACH FOR HYBRID ELECTRIC VEHICLE POWERTRAIN DESIGN

According to bench test results of fuel economy and engine emission for thereal power-train system of EQ7200HEV car. a 3-D performance map oriented quasi-linear model isdeveloped for the configuration of the powertrain components such as internal combustion engine,traction electric motor, transmission, main retarder and energy storage unit. A genetic algorithmbased on optimization procedure is proposed and applied for parametric optimization of the keycomponents by consideration of requirements of some driving cycles. Through comparison of numericalresults obtained by the genetic algorithm with those by traditional optimization methods, it isshown that the present approach is quite effective and efficient in emission reduction and fueleconomy for the design of the hybrid electric car powertrain.

Method of Electric Powertrain Matching for Battery-powered Electric Cars

The current match method of electric powertrain still makes use of longitudinal dynamics, which can’t realize maximum capacity for on-board energy storage unit and can’t reach lowest equivalent fuel consumption as well. Another match method focuses on improving available space considering reasonable layout of vehicle to enlarge rated energy capacity for on-board energy storage unit, which can keep the longitudinal dynamics performance almost unchanged but can’t reach lowest fuel consumption. Considering the characteristics of driving motor, method of electric powertrain matching utilizing conventional longitudinal dynamics for driving system and cut-and-try method for energy storage system is proposed for passenger cars converted from traditional ones. Through combining the utilization of vehicle space which contributes to the on-board energy amount, vehicle longitudinal performance requirements, vehicle equivalent fuel consumption level, passive safety requirements and maximum driving range requirement together, a comprehensive optimal match method of electric powertrain for battery-powered electric vehicle is raised. In simulation, the vehicle model and match method is built in Matlab/simulink, and the Environmental Protection Agency (EPA) Urban Dynamometer Driving Schedule (UDDS) is chosen as a test condition. The simulation results show that 2.62% of regenerative energy and 2% of energy storage efficiency are increased relative to the traditional method. The research conclusions provide theoretical and practical solutions for electric powertrain matching for modern battery-powered electric vehicles especially for those converted from traditional ones, and further enhance dynamics of electric vehicles.

Optimum Driving System Design for Dual-Motor Pure Electric Vehicles

A pure electric vehicle driven by dual motors is taken as the research object and the driving scheme of the driving motor is improved to increase the transmission efficiency of existing electric vehicles.Based on the architecture of the transmission system,we propose vehicle performance parameters and performance indexes of a pure electric vehicle,a time-sharing driving strategy of dual motors.First,the parameters of the battery,motor,and transmission system are matched.Then,the electric vehicle transmission model is built in Amesim and the control strategy is designed in Simulink.With the optimization goal of improving the vehicle’s dynamic performance and driving range,the optimal parameters are determined through analysis.Finally,the characteristics of the motor are tested on the bench.The results show that the energy-saving potential of the timesharing driven double motor is higher,and the driving mileage of the double motor drive is increased by 4%.

ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLES

Energy management strategy (EMS) is the core of the real-time controlalgorithm of the hybrid electric vehicle (HEV). A novel EMS using the logic threshold approach withincorporation of a stand-by optimization algorithm is proposed. The aim of it is to minimize theengine fuel consumption and maintain the battery state of charge (SOC) in its operation range, whilesatisfying the vehicle performance and drivability requirements. The hybrid powertrain bench testis carried out to collect data of the engine, motor and battery pack, which are used in the EMS tocontrol the powertrain. Computer simulation model of the HEV is established in the MATLAB/Simulinkenvironment according to the bench test results. Simulation results are presented for behaviors ofthe engine, motor and battery. The proposed EMS is implemented for a real parallel hybrid carcontrol system and validated by vehicle field tests.

Multi-Criteria Decision Analysis for Usage Based Optimization of Powertrains

The electrification of powertrains leads to an increasing diversification of powertrain configurations. Each single configuration has its specific advantages which appear depending on the usage profile. To find the usage based optimal powertrain in consideration of a variety of evaluation criteria, the powertrains have to be optimized for the usage profile and characteristics have to be extracted from the usage profile. The carbon dioxide emissions of the optimized powertrains and usage based criteria are used in a multi-criteria decision analysis to determine the optimal powertrain for a specific usage profile. The description of characteristic maps forms the objective function of a minimization problem. The determined carbon dioxide emissions are one criterion in a multi-criteria decision process. All considered criteria are at least partly objective so that subjective ratings are eliminated as far as possible. The result is an optimized powertrain for a desired usage under the consideration of objective criteria that are extracted from the usage profile.

Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles

This paper presents a review on the recent research and technical progress of electric motor systems and electric powertrains for new energy vehicles.Through the analysis and comparison of direct current motor,induction motor,and synchronous motor,it is found that permanent magnet synchronous motor has better overall performance;by comparison with converters with Si-based IGBTs,it is found converters with SiC MOSFETs show significantly higher efficiency and increase driving mileage per charge.In addition,the pros and cons of different control strategies and algorithms are demonstrated.Next,by comparing series,parallel,and power split hybrid powertrains,the series-parallel compound hybrid powertrains are found to provide better fuel economy.Different electric powertrains,hybrid powertrains,and range-extended electric systems are also detailed,and their advantages and disadvantages are described.Finally,the technology roadmap over the next 15 years is proposed regarding traction motor,power electronic converter and electric powertrain as well as the key materials and components at each time frame.

纯电动汽车电驱动系统故障诊断研究进展

为全面梳理纯电动汽车电驱动系统故障诊断的发展现状,明确未来发展趋势,本文首先介绍了纯电动汽车电驱动系统的基本架构、功能及发展历程;然后详细总结了纯电动汽车电驱动系统关键部件的故障类型及原因,分析了纯电动汽车电驱动系统关键部件故障诊断方法的主要研究现状;接着将诊断方法从专家知识驱动、模型驱动、信号驱动和数据驱动4个方面详细综述了纯电动汽车电驱动系统国内外研究进展和发展动态,并针对不同方法的优缺点进行了对比;最后对纯电动汽车电驱动系统故障诊断所面临的问题及发展方向进行了分析和展望,进一步讨论并指出未来纯电动汽车电驱动系统故障诊断研究可以集中在变工况耦合故障诊断、微小故障诊断和前期故障诊断研究、实时在线故障诊断、基于故障诊断的智能运维、未知故障诊断与系统自愈技术等方面。

基于概率模型和数据驱动的动力总成悬置系统可靠性优化

针对电动汽车动力总成悬置系统(PMS)一部分参数为概率变量,一部分参数为离散数据的复杂不确定情形,开展了基于概率模型和数据驱动的电动汽车PMS可靠性优化设计研究。首先,基于任意多项式混沌(APC)展开和广义最大熵原理推导了一种求解该复杂不确定情形下PMS响应不确定性和可靠性的高效方法;然后,基于蒙特卡洛抽样,给出了该复杂不确定情形下求解PMS响应不确定性和可靠性的参考方法;接着,提出了一种基于APC展开法的灵敏度分析方法,进一步提出了一种考虑响应不确定性和可靠性的PMS优化设计方法;最后,通过应用算例验证方法的有效性,并对系统进行了灵敏度分析和可靠性优化。结果表明,所提出的方法可有效地处理电动汽车PMS一部分参数为概率变量、一部分参数为离散数据的复杂不确定情形,并能可靠地优化该情形下的系统固有特性,且方法具有较高的计算精度和计算效率。

混合动力汽车动力系统功能分析及仿真研究

在混合动力设计开发前期,利用仿真软件对混合动力系统进行性能仿真和深入研究。通过阐述混合动力汽车动力系统的构型方案,分析了混合动力汽车的动力系统功能、驾驶操作模式以及控制策略。基于AVL CRUISE仿真软件,搭建了某款混合动力汽车的整车及动力系统仿真模型,并进行了整车动力性和经济性的仿真验证。仿真结果表明,混合动力车型性能和功能满足设计要求,为混合动力系统样车试验研究奠定基础。

City-Bus-Route Demand-based Efficient Coupling Driving Control for Parallel Plug-in Hybrid Electric Bus

Recently,plug?in hybrid electric bus has been one of the energy?e cient solutions for urban transportation. However,the current vehicle e ciency is far from optimum,because the unpredicted external driving conditions are di cult to be obtained in advance. How to further explore its fuel?saving potential under the complicated city bus driving cycles through an e cient control strategy is still a hot research issue in both academic and engineering area. To realize an e cient coupling driving operation of the hybrid powertrain,a novel coupling driving control strategy for plug?in hybrid electric bus is presented. Combined with the typical feature of a city?bus?route,the fuzzy logic inference is employed to quantify the driving intention,and then to determine the coupling driving mode and the gear?shifting strategy. Considering the response deviation problem in the execution layer,an adaptive robust controller for electric machine is designed to respond to the transient torque demand,and instantaneously compensate the response delay and the engine torque fluctuation. The simulations and hard?in?loop tests with the actual data of two typical driving conditions from the real?world city?bus?route are carried out,and the results demonstrate that the pro?posed method could guarantee the hybrid powertrain to track the actual torque demand with 10.4% fuel economy improvement. The optimal fuel economy can be obtained through the optimal combination of working modes. The fuel economy of plug?in hybrid electric bus can be significantly improved by the proposed control scheme without loss of drivability.

Evaluation of Waste Heat Recovery of Electrical Powertrain with Electro-thermally Coupled Models for Electric Vehicle Applications

The mile range of an electric vehicle(EV)may be reduced significantly in cold weather owing to the energy demand for meeting thermal comfort in the vehicle cabin,as waste heat from a combustion engine is not available for this purpose.Various heat pump-based heating,ventilation,and air conditioning(HVAC)systems can be employed to absorb the heat energy from the surroundings and/or the waste heat from the electrical powertrain to facilitate cabin thermal comfort,thereby extending the EV mile range.However,there is a lack of research on the electro-thermally coupled modelling and evaluation of the thermal performance of HVAC systems.This paper proposes electro-thermally coupled models for the electrical machine and inverter by modelling the key electromagnetic quantities as functions of the torque and speed based on offline parameter extraction from two-dimensional electromagnetic finite element analysis.The proposed electro-thermally coupled models,which are computationally efficient,are integrated into HVAC thermofluid simulation.Comparative studies of three heat pump-based HVAC architectures(conventional ambient heat only,waste heat only,and dual heat source)are performed using the proposed electro-thermally coupled models.The dual heat source HVAC architecture exhibits superior thermal performance over its counterparts in cold weather conditions.

电动汽车橡胶悬置高频动特性试验

电驱动力总成悬置系统高频结构噪声控制是电动汽车噪声、振动和声振粗糙度(noise,vibration and harshness,简称NVH)开发与研究的重要内容,悬置动特性试验因设备技术更新换代而大幅提升测试频率上限至3 kHz。以某电动汽车橡胶悬置为研究对象,进行高频动特性试验研究。首先,分析悬置动特性试验边界条件,指出悬置的胶体刚度、支架模态以及试验夹具模态是影响高频动特性的3个主要因素;其次,研究橡胶悬置高频动刚度的主要特点,通过附加质量的方案对动刚度峰值及频率与影响因素的对应关系进行了辨识;然后,总结了3个主要因素对动特性的影响规律,提出电动车悬置及其支架的设计与优化原则;最后,用悬置刚度和支架质量对整车主减速器阶次噪声的改善效果进行试验,验证了橡胶悬置高频动特性研究的必要性和结论的正确性。

任意概率不确定情形下的电动汽车悬置系统固有特性分析

针对电动汽车动力总成悬置系统(Powertrain Mounting System,PMS)参数可能被处理为不同类型概率变量的情形,提出了一种基于任意多项式混沌(Arbitrary Polynomial Chaos,APC)展开和最大熵原理(Maximum Entropy Principle,MEP)的电动汽车PMS固有特性不确定性分析方法。采用概率模型描述任意概率不确定情形下的PMS参数,通过APC展开获得任意概率不确定情形下PMS固有特性不确定性响应的前几阶统计矩,通过MEP拟合不确定性响应的概率密度函数(Probability Density Function,PDF)和累积分布函数(Cumulative Distribution Function,CDF)等信息,通过算例分析了5种概率不确定情形下的电动汽车PMS固有特性响应。分析结果表明,以蒙特卡洛法作为参考,所提出的方法可有效地分析不同概率不确定情形下的PMS固有特性响应,分析具有较高的计算精度和计算效率,能进一步获得响应满足设计要求的可靠度。

电动车动力总成悬置系统的可靠性分析方法

针对电动车动力总成悬置系统(Powertrain Mounting System,PMS)不确定参数同时存在不精确信息和相关性的复杂情形,提出一种考虑参数不精确信息和相关性的电动车PMS的可靠性分析方法 .首先,采用证据变量处理PMS参数的不精确信息,并引入相关系数矩阵描述变量间的相关性;然后,利用仿射变换并结合标准化技术,将相关的证据变量转化为标准的不相关证据变量;最后,通过求解PMS的固有特性响应及其满足设计要求的可信度与似真度,对PMS的可靠性概率区间进行分析.某电动车PMS可靠性分析算例结果表明:采用相关的证据变量能有效地处理PMS参数的不精确信息与相关性;参数的不精确信息对系统的可靠性有较大影响,尤其是Roll方向固有频率的可靠性;随着参数相关性增大,系统的可靠性出现明显变化,忽略参数的相关性可能导致较大的可靠性分析误差.

纯电动汽车悬置系统固有特性的不确定性和相关性传播分析

针对纯电动汽车动力总成悬置系统(Powertrain Mounting System,PMS)参数同时存在不确定性和相关性的情形,开展了纯电动汽车PMS固有特性的不确定性和相关性传播分析研究。利用多维平行六面体模型量化系统参数不确定性和相关性;基于多维平行六面体模型,将正则化法、泰勒展开法及中心差分法相结合,提出了一种PMS固有特性响应不确定性传播分析的MP摄动法。结合系统固有特性响应数据,基于蒙特卡罗法和置信度,提出了一种系统固有特性响应的相关性传播分析方法。以某纯电动汽车PMS算例验证了方法的有效性。分析结果表明:系统参数的不确定性会使得系统响应具有不确定性,而系统参数的相关性会使得系统响应具有一定的相关性。

电动车动力总成悬置系统的全局灵敏度分析

针对电动汽车动力总成悬置系统(Powertrain Mounting System,PMS)参数同时存在不确定性和相关性的情形,开展考虑不确定参数相关性的电动汽车PMS固有特性的全局灵敏度分析研究.采用含相关性的概率变量描述系统的不确定参数,基于方差分解推导考虑概率变量相关性的一阶和总体全局灵敏度公式;基于蒙特卡洛法(Monte Carlo Method,MCM)提出一种求解全局灵敏度指数的方法;推导当概率变量服从正态分布时的全局灵敏度公式,给出采用MCM计算全局灵敏度指数所需样本集的构造方法;以某电动汽车PMS算例验证方法的有效性.分析结果表明,相关性会影响系统固有频率和解耦率响应对不确定参数的敏感性,考虑不确定参数的相关性可获得更加合理的灵敏度分析结果.

Configurations and Control of Traction Motors for Electric Vehicles:A Review

In recent decades,worldwide global warming and reduction in petroleum resources have accelerated researcher’s attention to produce alternative sustainable and environmentally clean transportation systems.Electrification of vehicular technology is capable of curbing the environmental pollution problem in an efficient and effective way,due to high efficiency electric motors,development and advancement in the field of power electronic devices,digital signal processing and advanced control techniques.This article presents a comprehensive review on different configurations/architecture of electric vehicles(EVs)and hybrid electric vehicles(HEVs),traction motors for electric propulsion system and high performance speed sensorless control of traction drive.The basic architecture key components of hybrid vehicle and different power train configurations with respect to applications and limitations are discussed.The integral part of electric propulsion system,traction motor classes for desired operational characteristics and limitations are summarized from a system perspective with the latest improvements.High performance traction motor control techniques are discussed with respect to automotive applications.Finally,speed sensorless control techniques research trends as well as an extensive review on rotor speed estimation techniques for robust and efficient sensorless traction drive control are highlighted.This article provides state of the art key global trends and tradeoff of various technologies with future trends and potential areas of research.

Progress review of US-China joint research on advanced technologies for plug-in electric vehicles

The United States and China are the world's largest automobile markets and oil consumers, and both face a severe challenge to conserve energy and reduce tailpipe emissions. Thus, both countries urgently need to transform conventional internal combustion engines to electrified powertrains. Targeting the advanced core technologies of plug-in electric vehicles(PEVs), a joint research collaboration between China and the US, called the "Clean Vehicle Consortium"(CVC), was set up in 2010. Six years of collaboration on PEV technologies has resulted in significant progress in three technical areas. Based on CVC publications,we review herein the progress made by the CVC research efforts on three key advanced PEV technologies. This includes the development of a safe battery with an energy density of 260 W h kg^(-1) and a systematic method for designing safe traction battery systems. Thus, a breakthrough in high power density and efficient traction motor systems has occurred. In addition to discussing advanced electric-drive powertrains, we also discuss global energy management strategies that aim to improve PEV energy efficiency. This discussion covers scientific and comprehensive analysis methods to analyze energy systems, which include costbenefit analyses of plug-in hybrid electric vehicles, life-cycle assessments for evaluating vehicle emissions, and PEV-ownership projections.