混合动力汽车发动机转矩突变过程动态协调控制

针对混合动力汽车急加速时由于混合气瞬间加浓引起动态油耗增加的问题,本文中提出了基于转矩动态补偿的混合动力汽车发动机转矩突变过程动态协调控制方法。设计了基于转矩变化率限制的发动机转矩控制策略,避免了发动机转矩突变过程中动态油耗的增加,同时保证了加速过程中整车的动力性。实车试验结果表明,提出的动态协调控制方法不仅降低了加速过程中发动机的动态油耗,同时提高了整车动力性。     

ISG柴油混合动力客车能量分配策略研究

以ISG柴油混合动力客车整车控制策略为基础,综合考虑客车燃油经济性和排放,提出一种基于模糊神经网络的能量分配策略,该策略根据模糊控制原理,结合人工神经网络自主学习功能,以电池SOC、整车需求转矩以及发动机转速为模糊输入来确定发动机和电机的最佳输出转矩分配,再以神经网络对控制的模糊规则进行记忆.仿真结果表明,该策略比普通逻辑控制更加有利于燃油经济性的提高,并在一定程度上改善了排放性能.     

双离合ISG混合动力汽车控制策略

对双离合ISG混合动力汽车的结构和工作要求进行分析,针对双离合ISG混合动力汽车动力系统提出了动态、静态相结合的逻辑门限控制策略。根据设定的静态逻辑门限值判断整车所处的工作模式,在确定的工作模式下查找最佳工作点以控制发动机和ISG电机的输出转矩。基于Matlab/Simulink仿真软件建立动力系统仿真模型,并进行仿真分析。仿真结果表明,所采用的控制策略能够满足整车动力性要求,燃油经济性较传统汽车提高了19%,能有效降低混合动力汽车的尾气排放。     

ISG型混合动力汽车发动机启动过程分析

针对ISG(integrated-starter-generator)型混合动力汽车建立相应的ISG电机-发动机仿真模型,研究不同的电机控制策略对发动机启动性能的影响,通过控制电机的转速和转矩快速拖动发动机启动,并根据发动机台架试验确定最优的电机控制策略.试验结果表明,通过合理控制ISG电机能够实现发动机快速启动,取消发动机启动加浓过程,降低启动时的油耗及排放.     

并联混合动力电动汽车的转矩控制策略

讨论了并联混合动力电动汽车的能量管理策略,阐述了一种基于规则转矩的控制策略,并在ADVISOR2002仿真软件上结合模型作了仿真分析。仿真试验证明这种转矩控制策略是一种合理的能量优化管理策略,提高了并联式混合动力电动汽车系统效率,获得了整车最大的燃油经济性、最低的排放以及平稳的驾驶性能。     

并联式混合动力汽车遗传模糊控制策略的研究

为带双离合器和单轴转矩耦合的某并联混合动力汽车开发了模糊控制策略,采用遗传算法对转矩分配模糊控制器进行了优化。在Matlab/Simulink和ADVISOR环境下基于试验数据建立了仿真模型,并进行了NEDC循环下只考虑经济性的控制策略优化和综合考虑经济性和排放性能的多目标控制策略优化。结果表明,应用遗传算法对模糊控制策略进行多目标优化后,油耗降低了3.65%,同时整车排放也有明显降低。     

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。     

插电式串联混合动力汽车发动机起停控制策略的优化

利用AVL-CRUISE软件对某插电式串联混合动力汽车进行整车建模与仿真,并在不同的行驶循环工况和车辆行驶里程下优化发动机的起停控制策略。结果表明:根据不同的行驶循环工况和行驶里程来修正发动机起停时刻的SOC值,可以有效缩短发动机的运行时间,从而降低油耗和能量损失。该方法也可为增程型电动汽车发动机的起动控制提供参考。     

基于模糊控制与微粒群优化的混合动力客车控制策略的研究

为一辆混合动力客车(HEB)提出了一种模糊控制与微粒群优化相结合的控制策略.构建了以需求转矩与发动机最佳转矩之差和超级电容荷电状态为输入,以发动机转矩为输出的模糊控制器,并以等效燃油消耗为优化目标,利用微粒群算法对模糊隶属度函数和模糊控制规则进行优化.基于Matlab/Advisor建立了HEB模糊控制策略模型和整车模型,并进行HEB整车动力性和经济性分析.结果表明所提出的控制策略能够满足HEB的设计要求,等效燃油消耗量约降低了10.1%.     

计及发动机冷热效应的插电式混合动力汽车最优控制策略研究

为了缩短发动机的冷机工作时间,降低发动机的油耗和排放,以计及发动机冷热效应的燃油消耗最小为目标函数,依据庞特里亚金极小值原理建立了Hamilton函数,对目标泛函进行求解,获得了计及发动机冷热效应的最优控制策略,并将该控制策略分别与CD-CS模式控制策略和忽略发动机冷热效应的最优控制策略进行了比较.研究结果表明:计及发动机冷热效应的最优控制策略与CD-CS模式控制策略相比可使整车百公里油耗降低9.64％;与忽略发动机冷热效应的最优控制策略相比,可使整车百公里油耗降低2.34％,使三元催化器的起燃时间缩短21.3％;该策略可使插电式混合动力汽车具有更好的燃油经济性和排放性.     

基于增益功率燃油系数的HEV能量管理策略

为了优化等效燃油最小能量管理策略的节油效果，以适用于工程批量应用为导向，制定基于增益功率燃油系数的混合动力汽车(HEV)能量管理策略。基于瞬时优化原理，提出基于增益功率燃油系数的工作模式决策机制，根据电机发电或电动引起的发动机功率与燃油消耗率的变化关系，分别给出电机充电和放电模式下增益功率燃油系数的计算方法。考虑发动机扭矩瞬态快速变化对油耗的影响和电机及电池包充放电效率特性，提出发动机高效区域扭矩滞回控制方法，建立基于增益功率燃油系数的能量管理策略算法架构。基于MATLAB/Simulink搭建控制策略软件模型，通过转鼓试验台进行实车试验验证。研究结果表明：相对于等效燃油最小能量管理策略，基于增益功率燃油系数的能量管理策略提升了节油率和舒适性，在全球轻型汽车测试循环(WLTC)工况下的百公里油耗降低了约4.8%，发动机的启停次数降低了约53%；相对于有效燃油消耗率(BSFC)最优工作点控制方法，发动机高效区域滞回控制方法降低百公里油耗约1.8%；与采用基于动态规划的全局优化能量管理策略的仿真结果对比，在不能提前预知工况的条件下，制定的能量管理策略在WLTC工况与新标欧洲测试循环(NEDC)工况下的油耗与理论最优值差距均较小。     

Economic value and utility of a powertrain system for a plug-in parallel diesel hybrid electric bus

This research is the first to develop a design for a powertain system of a plug-in parallel diesel hybrid electric bus equipped with a continuously variable transmission (CVT) and presents a new design paradigm of the plug-in hybrid electric bus (HEB). The criteria and method for selecting and sizing powertrain components equipped in the plug-in HEB are presented. The plug-in HEB is designed to overcome the vulnerable limitations of driving range and performance of a purely electric vehicle (EV) and to improve fuel economy and exhaust emissions of conventional bus and conventional HEBs. The control strategy of the complicated connected propulsion system in the plug-in parallel HEB is one of the most significant factors in achieving higher fuel economy and lower exhaust emissions of the HEV. In this research, a new optimal control strategy concept is proposed against existing rule-based control strategies. The optimal powertrain control strategy is obtained through two steps of optimizations: tradeoff optimization for emission control and energy flow optimization based on the instantaneous optimization technique. The proposed powertrain control strategy has the flexibility to adapt to battery SOC, exhaust emission amount, classified driving pattern, driving condition, and engine temperature. The objective of the optimal control strategy is to optimize the fuel consumption, electricity use, and exhaust emissions proper to the performance targets. The proposed control strategy was simulated to prove its validity by using analysis simulation tool ADVISOR (advanced vehicle simulator).     

基于线性规划的混合动力汽车智能充电策略

以油电混合动力汽车整车控制策略为基础,提出一种基于线性规划的智能充电能量分配策略,改善了混合动力汽车燃油经济性。该策略在维持高压电池SOC平衡的前提下,根据整车需求功率,发动机和中混电机转速,结合各动力总成部件能量传递的效率,以系统等效燃油消耗最小为原则进行扭矩分配优化。通过仿真结果表明,该策略比普通瞬时优化策略提高了整车燃油经济性。     

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.     

PSO algorithm-based parameter optimization for HEV powertrain and its control strategy

The coordination between the powertrain and control strategy has significant impacts on the operating performance of hybrid electric vehicles (HEVs). A comprehensive methodology based on Particle Swarm Optimization (PSO) is presented in this paper to achieve parameter optimization for both the powertrain and the control strategy, with the aim of reducing fuel consumption, exhaust emissions, and manufacturing costs of the HEV. The original multi-objective optimization problem is converted into a single-objective problem with a goal-attainment method, and the principal parameters of powertrain and control strategy are set as the optimized variables by PSO, with the dynamic performance index of HEVs being defined as the constraint condition. Computer simulations were carried out, which showed that the PSO scheme gives preferable results in comparison to the ADVISOR method. Therefore, fuel consumption and exhaust emissions of HEVs can be effectively reduced without sacrificing dynamic performance of HEVs.     

Powertrain system optimization for a heavy-duty hybrid electric bus

This research concerns the design of a powertrain system for a plug-in parallel diesel hybrid electric bus equipped with a continuously variable transmission (CVT) and presents a new design paradigm for the plug-in hybrid electric bus (HEB). The criteria and method for selecting and sizing powertrain components equipped in the plug-in HEB are presented. The plug-in HEB is designed to overcome the vulnerable limitations of driving range and performance of a purely electric vehicle (EV), and it is also designed to improve the fuel economy and exhaust emissions of conventional buses and conventional HEBs. Optimization of the control strategy for the complicated and interconnected propulsion system in the plug-in parallel HEB is one of the most significant factors for achieving higher fuel economy and lower exhaust emissions in the hybrid electric vehicle (HEV). In this research, the proposed control strategy was simulated to prove its validity using the ADVISOR (advanced vehicle simulator) analysis simulation tool.     

并联式混合动力汽车模式切换控制策略研究

并联式混合动力汽车模式切换时离合器会介入传动系统,容易引起较明显的冲击感,是影响整车驾驶舒适性的主要因素。为此,提出了基于离合器双模糊和电机转矩协调的模式切换控制策略。首先建立混合动力汽车模式切换过程的动力学模型,以减小离合器滑磨功为目标,对模式切换时的离合器接合过程进行划分;其次,结合混合动力汽车模式切换的基本要求和驾驶意图,制定离合器双模糊控制策略,分别对滑摩阶段的接合时长和转矩同步阶段的压力变化率进行控制;然后以离合器滑磨功和整车冲击度为优化目标,采用二次型最优控制算法对滑摩阶段的接合压力进行优化,从而获取模式切换过程中离合器的最优接合压力轨迹;在此基础上,通过实时计算离合器传递转矩,根据电机转矩响应快的特点,制定电机转矩协调控制策略;最后,基于某混合动力试验样车,在底盘测功机上分别进行缓加速、中等加速和急加速下的模式切换试验,对所提出的控制策略进行验证。试验结果表明：该策略能较好地反映驾驶人驾驶意图,保证离合器的使用寿命,所产生的整车冲击度均处于合理范围之内,改善了整车模式切换过程中的驾驶舒适性。     

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.     

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。