试验循环工况下混合动力车用镍氢电池组温度场研究

在镍氢电池生热理论的基础上,根据混合动力汽车试验循环工况获得的充放电电流计算得到电池的生热功率,建立了电池组散热系统的散热模型。应用计算流体力学方法对电池组的温度场进行了数值模拟仿真分析,并进行了混合动力汽车试验循环工况下镍氢电池组的温度场试验。结果表明,模拟值与试验值吻合;电池组具有良好的散热效果,可满足混合动力汽车在生热、散热方面对镍氢电池的使用要求。     

电动汽车电池功率输入等效电路模型的比较研究

为了选取合适的等效电路电池模型应用于电动汽车系统仿真,提出GNL模型,并与R int、Theven in、PNGV、RC模型进行性能比较。以320单体串联的80A.h镍氢电池组为研究对象,基于同一组复合脉冲试验数据,辨识各模型的参数,进而建立各模型基于Matlab/Simulink的功率输入仿真模型。使用20 kW恒功率放电和FUDS工况试验数据验证,并比较各模型性能。仿真与试验的比较表明,功率输入等效电路电池模型的电压误差为主要误差,电流误差为次要误差,5种模型中PNGV和GNL模型更适用于电动汽车仿真,而GNL模型具有更好的精度。     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.     

Novel evaluation method of fuel consumption and emission for heavy-duty hybrid electric vehicles

This paper is a continuation of a previous paper titled “A novel way to calculate energy efficiency for rechargeable batteries” published on Journal of Power Sources/2012 describing a new method to calculate energy efficiency for rechargeable batteries. The present paper further describes the application of energy efficiency model on the evaluation of fuel consumption and emission for the heavy-duty hybrid electric vehicles (HD-HEVs). A more accurate calculation method of net energy change for power battery pack is proposed based on energy efficiency model of power battery pack. A more simplified and accurate correction method of fuel consumption and emission is also presented based on equivalent mileage. The fuel consumption and emission on chassis dynamometer are measured in the HD-HEVs. The experiment results show that relative errors of fuel consumption and emission between equivalent mileage correction results and linear regression correction results are less than 3%, which verifies accuracy and validates the proposed evaluation method for HD-HEVs fuel consumption and emission.     

Implementation of discharging/charging current sensorless state-of-charge estimator reflecting cell-to-cell variations in lithium-ion series battery packs

This paper offers novel insights to the design and implementation of an innovative state-of-charge (SOC) estimator for the lithium-ion (Li-Ion) series battery pack. The most interesting feature of this approach is that it can utilize information from each filtered terminal voltage of the Li-Ion cells connected in series for SOC estimation of the battery pack. Without actual sensing each discharging/charging current (DCC) applied to the Li-Ion cells, it is possible to extract each DCC estimation from the corresponding filtered terminal voltages with an equivalent electrical circuit model (EECM) identification of all Li-Ion cells in the battery pack. There are two advantages to SOC estimation of the battery pack with this approach. First, the proposal can be implemented simply and effectively, reducing the computational steps required for SOC estimation. By reducing computational steps, the proposal is expected to be more cost-effective. Second, the approach guarantees an improved SOC performance, even if the battery pack results in inevitable cell-to-cell variation among Li-Ion cells. Accordingly, there are fewer differences to previously estimated DCCs among Li-Ion cells. Specifically, all values from the estimated DCCs are properly compensated for by simultaneous parameter modification according to each cell’s electrochemical characteristics. Experimental results clearly demonstrate that our DCC sensorless SOC estimator provides robust SOC performance for the battery pack. This approach considered an experimental battery pack (12S1P) connected in series using 2.6 Ah LiCoO2 cells produced by Samsung SDI.     

基于遗传算法的混合动力汽车参数多目标优化

针对混合动力汽车设计参数众多的状况,提出了一种对混合动力汽车传动系统参数和控制参数同时进行优化的多目标优化新方法--自适应遗传算法.在ADVISOR平台上,以一辆使用逻辑门限控制策略的并联混合动力汽车为例,分析并建立了以动力性能指标为约束的混合动力汽车参数优化的非线性规划模型,其目标函数包含最小油耗和最佳排放性能.针对遗传算法容易早熟等不足,采用带自适应交叉和变异算子的遗传算法和模拟退火技术相结合进行求解.仿真结果表明了所提出方法的有效性.     

并联式混合动力电动汽车电池参数优选

通过研究双轴并联混合动力电动汽车控制策略,分析电池参数和整车油耗的关系,确定电池电压、容量和最大充放电功率的变化范围。基于CRUISE的仿真平台,以整车循环工况油耗最省为目的,优选电池的各个参数。并将选定的电池参数代入模型中,进行动力性分析计算。计算结果表明,在满足整车动力性的要求下,通过对电池参数的优化,可提高混合动力电动汽车的燃油经济性和动力电池组的性价比。     

电动汽车锂电池建模及参数辨识方法研究

介绍多种电池模型及其参数辨识算法,综合考虑辨识复杂程度和精度,提出一种利用一阶RC电路模型、遗忘因子最小二乘优化算法、监控平台电池孪生模型的锂电池建模及参数辨识方法,并进行实车应用验证。结果表明,该方法能够使SOC的估计误差保持在3%以内。     

燃料电池混合动力汽车动力系统匹配与优化研究

首先,基于中国客车典型循环工况对燃料电池混合动力系统进行匹配计算,确定了电动机、燃料电池发动机和蓄电池的基本参数;然后基于中国客车典型循环工况,建立燃料电池混合动力系统的优化模型,采用序列二次规划算法进行优化,分析了各种参数对整车燃料经济性的影响,包括燃料电池发动机与动力蓄电池之间的功率分配比、SOC的初始值与目标值、变速器传动比及传动比间隔以及主减速比等,为燃料电池混合动力汽车的构型提供指导。     

混合动力电动汽车用蓄电池不一致的影响分析

应用于混合动力电动汽车的铅酸蓄电池，由于其性能参数的不一致而导致使用过程中产生性能参数差别的扩大化，是造成蓄电池使用寿命短以及混合动力电动汽车性能下降的重要因素，从理论上分析了蓄电池性能差别扩大的原因，并通过试验进一步说明性能参数不一致所表现出的特征及影响。     

电动汽车蓄电池键合图建模及仿真

对蓄电池建模方式进行探讨并采用等效电路法建模，对SOC的计算进行比较讨论后采用更加合理的算法，对蓄电池散热系统及热系统的键合图建模方法进行深入探讨，建立了散热系统的键合图模型。利用键合图建模方法的优势，将蓄电池等效电路的键合图模型和散热系统的键合图模型耦合在一起，建立了蓄电池系统的键合图模型，并由此导出数学模型，进一步建立仿真模型，实现了蓄电池的动态仿真，并与试验结果进行比较得到很好的效果。     

电动汽车用电池性能模型研究综述

将电池模型归纳为电化学模型、热模型、耦合模型和性能模型4种类型．并讨论了电动汽车用电池性能模型的研究和应用情况,通过对简化的电化学模型、等效电路模型、神经网络模型、部分放电模型和特定因素模型的分析．总结出电动汽车电池性能模型建模过程的主要环节．指出了性能模型研究的思路。     

混合动力车用蓄电池管理系统设计与研究

阐述了一种混合动力车用电池管理系统的分布式设计方案,并按照模块化的方式设计了下位机电池控制单元的硬件和软件。结合整车道路试验对系统的准确性和可靠性进行了验证。结果表明,本系统运行稳定,符合混合动力汽车对电池管理的要求,达到了预期的效果。     

Optimized dynamic battery model suited for power based vehicle energy simulation

Ever increasing demand for the petroleum is causing faster than expected oil shortages in the supply and demand balance around the world and furthermore, many specialists in the field of oil production such as Association for the Study of Peak Oil and World Energy Outlook are claiming that the petroleum is around the peak of its production (Figure 1). Such shortage made the greatest impact on the gasoline price hikes at the gas pump and thus, this impact was felt by the consumers severely and became the greatest motivation for automotive industries to strive to pioneer the researches for the next generation vehicle configurations ranging from HEV, PHEV, Pure EV to FCHEV (collectively noted as xEV). While the great deal of researches has been carried over the last few decades, it is still far from mass productions for consumer use except for the HEV mainly due to the high cost involved with other types of xEV configurations. Therefore, it is critical to design the vehicle to maximize the use of each component at its highest point regardless of any cost scenarios and it is clear that this optimization can only be achieved through the accurate energy balance simulation for a specific target vehicle prior to the actual hardware implementation. In this paper, it is our intention to introduce modified dynamic battery modeling scheme that would provide a more accurate way of simulating the battery behavior when used in the vehicle energy simulation system. Starting from a typical battery dynamic model to predict the voltage given an imposed current request, we have introduced a new scheme to establish the relationship between the voltage and the power (rather than the current) requested by the vehicle simulation system. The proposed scheme handles the power request from the vehicle simulator considering the dynamic battery characteristics and in turn, contributes to the better estimation of the current integrated energy usage and battery SOC level in the given battery dynamic system used in the vehicle energy simulation system.     

混合动力电动汽车能量自适应模糊控制研究

为了实现混合动力电动汽车两种能量的最佳分配,确保电机、蓄电池的合理运行,建立了前向并联式混合动力电动汽车动力系统模型,提出了采用自适应模糊控制方法对动力系统进行能量分配,设计了控制器,讨论了自组织控制器的规则自我调整过程。整车循环工况仿真试验表明该控制具有较强的鲁棒性,可使电机、发动机、蓄电池等动力设备工作于最佳工况。     

混合动力汽车镍氢电池组通风结构优化分析

对混合动力汽车现有的镍氢电池组的通风结构进行了研究,分析了不同电池模块配置方式对电池组冷却空气流场和温度场分布的影响.在现有的顺排和叉排的基础上提出了梯形排列,采用ANSYS CFX软件对不同排列进行了数值模拟,结果表明,梯形排列方式可以较好地改善电池组温度分布的均匀性.最后,设计了梯形排列电池组样机,并进行了充放电和温度测量试验,验证了数值仿真的结果.     

电动汽车电池非线性等效电路模型的研究

服务于电动汽车系统仿真,提出一种非线性等效电路电池模型,模型考虑SOC、温度对电池特性的非线性影响。设计了系统的模型参数辨识实验及数据处理方法,使用S imu link建立了以电流为输入和以功率为输入的镍氢电池组模型。通过1 372 s的FUDS实验验证,两个模型最大电压误差分别为电池组额定电压的1.02%和1.39%,精度满足电动汽车系统仿真要求。     

基于捕食搜索策略的混合动力汽车参数优化

混合动力汽车模型是一个较复杂的非线性系统,且设计参数较多,为一种处理燃油经济性和排放的多目标问题。文章以一辆实例样车的动力系统和逻辑门限值控制策略为例,分析并建立了以动力性能为控制约束,以最小化油耗和排放为控制目标的非线性规划模型。采用捕食搜索遗传算法,对模型进行了仿真。结果表明,该方法相对于简单遗传算法更能有效地改善车辆燃油经济性和排放。     

Simulation of a powertrain system for the diesel hybrid electric bus

The plug-in hybrid electric bus (HEB) is designed to overcome the vulnerable driving range and performance limitations of a purely electric vehicle (EV) and have an improved fuel economy and lower exhaust emissions than those of a conventional bus and convention HEBs. The control strategy of the plug-in parallel HEB??s complicated connected propulsion system is one of the most significant factors for achieving a higher fuel economy and lower exhaust emissions than those of the HEV. The proposed powertrain control strategy has flexibility in adapting to the battery??s state of charge (SOC), exhaust emissions, classified driving patterns, driving conditions, and engine temperature. Simulation is required to model hybrid powertrain systems and test and develop powertrain control strategies for the plug-in parallel HEB. This paper describes the simulation analysis tools, powertrain components?? models and modifications, simulation procedure, and simulation results.     

基于自适应卡尔曼滤波的锂离子电池SOC估计

采用自适应卡尔曼滤波方法,基于锂离子动力电池的等效电路模型,在未知干扰噪声环境下,在线估计电动汽车锂离子动力电池荷电状态(SOC)。仿真结果表明,采用自适应卡尔曼滤波方法估计的SOC误差小于2.4%,有效降低了电动汽车行驶时电池管理系统所受到的未知干扰噪声影响,SOC估计精度高于扩展卡尔曼方法,且具有较好的鲁棒性。