混合动力车控制策略的逆向研发与仿真

介绍混合动力车控制策略研发的新思路,通过逆向较成熟的混合动力车型,借鉴其控制策略来编写混动车控制策略。以某合资品牌并联混动车型为例,利用Matlab/Simulink搭建整车控制策略模型,并利用Matlab与Cruise进行联合仿真验证所搭建的策略模型的仿真效果。     

基于PSAT的混合动力系统仿真实验研究

和传统汽车的仿真研究一样,建立正确的模型是混合动力汽车仿真研究的前提。和传统汽车相比,在控制上混合动力汽车多了更复杂的整车控制策略这一关键技术,因此所建立的模型更强调检验其在不同整车控制策略时的动态适应能力。基于先进实时系统分析工具PSAT,提出了一套混合动力汽车模型科学仿真研究过程。对某混合动力系统进行的仿真实践表明,所制定的方案科学合理,修正优化后的整车模型能准确贯彻执行混合动力汽车的控制策略指令,为后面基于不同优化目标的详细整车控制策略的开发打下了基础。     

插电式四驱强混汽车整车控制策略开发

在介绍和分析四驱强混系统架构和零部件功能特性的基础上,系统地提出了插电式四驱强混汽车的整车控制策略开发方法,包括考虑整车舒适性的减振控制、整车经济性的再生制动控制和整车驱动模式的切换、AMT换挡控制等策略。由Matlab/Simulink搭建整车控制策略模型并生成代码,目前策略已在奇瑞自主开发的整车控制器上得以实现,并完成了在整车仿真平台上的仿真验证和在插电式混合动力样车上的试验验证,通过对试验数据的分析,验证了该控制策略的可行性。     

正向仿真模型与反向软件ADVISOR的集成开发

混合动力汽车仿真软件ADVISOR是一种反向仿真软件,介绍在ADVISOR2002平台下如何通过修改进行正向仿真软件的开发,并嵌入到其GUI平台下进行仿真。仿真结果表明,在ADVISOR平台下可以进行正向模型的仿真,这对实际混合动力控制策略的开发具有重要意义。     

混合动力汽车正向建模与仿真

根据正向建模的思想建立了基于Matlab／Simulink平台的并联双轴混合动力汽车正向仿真模型,该模型既可以用踏板信号作为输入也町以运行循环工况。仿真结果与试验结果的对比表明,所建模型可以用于分析评价不同的设计方案和控制策略的优化,还可以进行实际控制系统的开发。     

基于混沌神经网络的混合动力汽车状态切换协调控制策略研究

针对并联混合动力汽车在发动机和电动机工作状态切换过程中非线性动力耦合系统工作状态所具有的混沌特征,提出了基于混沌神经网络的混合动力汽车状态切换协调控制策略。建立了协调控制总体模型构架,设计了混沌神经网络工作状态识别器,并通过试验对该识别器的准确性进行了验证。在此基础上搭建了协调控制系统整车控制模型,针对协调控制策略进行了仿真试验。结果表明,采用该控制策略能够有效提高整车动力性、燃油经济性与SOC平衡性,实现了对状态切换过程的协调控制。     

基于AMESim的混合动力汽车控制策略设计与优化

为改善汽车的经济性和排放性能,本文以并联式混合动力汽车为研究对象,首先根据某款混合动力汽车设计要求,计算各个部件参数,并在AMESim软件上搭建了整车模型;然后采用逻辑门限值控制策略中的电力辅助控制策略,基于Matlab-Simulink搭建电力辅助控制策略,并在NEDC工况下进行联合仿真,最后集成Isight,采用NSGA-Ⅱ算法对控制参数进行优化,并进行优化后的整车经济性和排放性能仿真分析对比,验证了本文的控制策略设计与优化方法可行性。     

基于Advisor二次开发的6×4混合动力汽车建模与仿真

建立了6×4三轴汽车动力学模型,基于该模型对Advisor进行了二次开发。对牵引力耦合式并联混合动力汽车结构和控制策略进行了分析。搭建了某6×4牵引力耦合式并联混合动力汽车和与之参数相同的6×4传统燃油汽车Advisor仿真模型,进行了燃油经济性对比仿真分析。仿真结果表明:该牵引力耦合式并联混合动力汽车相比传统燃油汽车在山区高速工况下的油耗降低9.4%;牵引力耦合式并联混合动力汽车发动机工作点和发动机工作效率分布相对传统燃油汽车更加经济。     

并联混合动力客车控制策略比较

控制策略的制定是混合动力电动汽车开发的关键,因为其直接影响着能量在车辆内部的流动及整车的性能。本文首先介绍了3种不同的并联混合动力客车控制策略:电动助力控制策略、实时控制策略及模糊逻辑控制策略,然后利用ADVISOR建立的SY6480整车模型在SIMULINK环境下进行整车仿真,根据仿真结果考察这些控制策略对于这一并联混合动力客车的燃油经济性的影响,最后通过分析,对于不同的控制策略的适用性作出评价。     

基于驾驶意图识别的HEV模糊控制策略研究

文章以并联式混合动力汽车为研究对象,针对混合动力汽车的燃油经济性及其控制策略进行研究,采用了驾驶意图识别的模糊控制策略,并通过MATLAB平台和CRUISE软件进行联合仿真实验。仿真结果表明,相比于逻辑门限控制策略,驾驶意图识别的模糊控制策略可以明显提升整车燃油经济性,验证了所提出控制策略的有效性和实用性。     

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.     

并行再生制动系统控制器的设计与开发

分析了混合动力汽车再生制动系统的特点及其应用前景,提出了一种基于并行控制的再生制动控制策略;针对某款并联式混合动力轿车,采用并行再生制动控制策略,进行了制动控制器的软硬件开发;搭建了硬件在环仿真试验系统对控制器进行了硬件在环仿真验证,并对控制器进行了实车测功机试验和实车道路试验。试验结果表明:该控制器运行稳定、可靠,整车平均制动能量回收效率达15%左右,显著提高了汽车的能源利用效率。     

并联式HEV制动能量回收控制策略的仿真研究

以某并联混合动力电动汽车为研究对象，提出了一种用于汽车制动过程中制动能量回收的控制策略，并利用在MATLAB／Simulink平台上建立的仿真模型和Advisor仿真软件对控制策略进行了仿真分析。仿真结果表明，在各种工况下车辆的能量利用率都有明显的提高，验证了所提控制策略的有效性。     

大负荷工况下并联混合动力电动汽车控制策略仿真分析

分析了ADVISOR2002中并联混合动力电动汽车的电力辅助控制策略，指出了其中存在的不足。开发了新的控制策略，仿真结果表明，在大负荷工况下电池的荷电状态SOC得到了明显改善。     

基于ADVISOR2002混合动力汽车控制策略模块开发

介绍了混合动力汽车仿真软件ADVISOR中的并联控制策略，结合课题的实际情况，对ADVISOR2002的并联控制策略进行了二次开发，并针对某一车型进行了仿真对比，结果表明所提出的控制策略不仅能够鲁棒地在ADVISOR2002界面中运行，而且合理、可靠，满足实际需要。     

Bees-algorithm-based optimization of component size and control strategy parameters for parallel hybrid electric vehicles

This paper presents the optimization of key component sizes and control strategy for parallel hybrid electric vehicles (parallel HEVs) using the bees algorithm (BA). The BA is an intelligent optimization tool that mimics the food foraging behavior of honey bees. Parallel HEV configuration and electric assist control strategy were used to conduct the research. The values of the key component size and the control strategy parameters were adjusted according to the BA to minimize the weighted sum of fuel consumption (FC) and emissions, while the vehicle performance satisfies the PNGV constraints. In this research, the software ADVISOR was used as the simulation tool, and the driving cycles FTP, ECE-EUDC and UDDS were employed to evaluate FC, emission and dynamic performance. The results demonstrate that the BA is a powerful tool in parallel HEV optimization to determine the optimal parameters of component sizes and control strategy, resulting in the improvement of FC and emissions without sacrificing vehicle performance. In addition, the BA is able to define a global solution with a high rate of convergence.     

Combined control of a regenerative braking and antilock braking system for hybrid electric vehicles

Most parallel hybrid electric vehicles (HEV) employ both a hydraulic braking system and a regenerative braking system to provide enhanced braking performance and energy regeneration. A new design of a combined braking control strategy (CBCS) is presented in this paper. The design is based on a new method of HEV braking torque distribution that makes the hydraulic braking system work together with the regenerative braking system. The control system meets the requirements of a vehicle longitudinal braking performance and gets more regenerative energy charge back to the battery. In the described system, a logic threshold control strategy (LTCS) is developed to adjust the hydraulic braking torque dynamically, and a fuzzy logic control strategy (FCS) is applied to adjust the regenerative braking torque dynamically. With the control strategy, the hydraulic braking system and the regenerative braking system work synchronously to assure high regenerative efficiency and good braking performance, even on roads with a low adhesion coefficient when emergency braking is required. The proposed braking control strategy is steady and effective, as demonstrated by the experiment and the simulation.     

混合动力轿车多能源动力总成控制系统研制与开发

介绍某型混合动力轿车多能源动力总成控制系统的设计思想和关键技术,着重阐述混合动力系统功能设计、控制逻辑和策略、系统硬软件设计以及动力系统台架联合调试的情况。研究轻度并联混合动力系统的控制策略、CAN通信、测试和试验等技术和方法,通过提高系统的控制功能和性能,最终达到改善混合动力汽车的动力性、经济性及排放等目的。     

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.     

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.