Comparison of PMP and DP in fuel cell hybrid vehicles

Pontryagin’s Minimum Principle (PMP) and Dynamic Programming (DP) are both from the optimal control theory and can both achieve optimal trajectories when they are applied to power management strategies of hybrid vehicles. However they have totally different control concepts. In order to select the superior one, the PMP-based and the DP-based power management strategies are introduced and compared for a fuel cell hybrid vehicle (FCHV) in this paper. The two power management strategies are applied to the FCHV in a computer simulation environment, and the simulation results from the two strategies are compared when the control variable for the PMP is fuel cell system (FCS) net power and for the DP is battery power. As a result, the superiority of the PMP-based power management strategy is proved.     

Fuel economy evaluation of fuel cell hybrid vehicles based on optimal control

The fuel economy of a fuel cell hybrid vehicle (FCHV) depends on its power management strategy because the strategy determines the power split between the power sources. Several types of power management strategies have been developed to improve the fuel economy of FCHVs. This paper proposes an optimal control scheme based on the Minimum Principle. This optimal control provides the necessary optimality conditions that minimize the fuel consumption and optimize the power distribution between the fuel cell system (FCS) and the battery during driving. In this optimal control, the final battery state of charge (SOC) and the fuel consumption have an approximately proportional relationship. This relationship is expressed by a linear line, and this line is defined as the optimal line in this research. The optimal lines for different vehicle masses and different driving cycles are obtained and compared. This research presents a new method of fuel economy evaluation. The fuel economy of other power management strategies can be evaluated based on the optimal lines. A rule-based power management strategy is introduced, and its fuel economy is evaluated by the optimal line.     

氢燃料电池混合动力汽车能量管理系统建模与仿真分析

为了合理分配燃料电池/动力电池混合动力汽车(FCHV)行驶过程中双电源的能量投入比例,更好地保护电池,本文讨论了“FC+B”汽车混合动力系统,设计了一种能量管理控制方法,利用Matlab/Simulink建立了能量管理系统模型,并对该能量管理系统进行了仿真研究。研究结果表明,制定的能量管理控制方法,可有效判断并计算需求功率,准确分配燃料电池和动力电池的功率,使FCHV具有良好经济性和安全性。     

Fuel consumption of fuel cell hybrid vehicles considering battery SOC differences

Fuel cell hybrid vehicles (FCHVs) have become one of the most promising candidates for future transportation due to current energy supply problem and environmental problem. Fuel economy is an important factor in FCHVs. In order to properly evaluate the fuel economy of an FCHV, the initial battery state of charge (SOC) and the final battery SOC have to be identical so that the effect of the battery energy usage on the fuel economy is neglected. In the simulation or in the real driving, however, the final battery SOC is usually different from the initial battery SOC, and the final battery SOC often depends on the power management strategy. To consider the difference between the two battery SOC values, the concept of equivalent fuel consumption is presented by two methods. One is based on the relationship between delta SOC and delta fuel consumption, and the other is based on the optimal control theory. Two rule-based power management strategies for an FCHV are presented, and for each strategy, the fuel economy is evaluated based on the two methods. The characteristics of the two methods are discussed and compared, and the superior one is selected based on the comparison.     

考虑燃料电池衰退的FCHEV反馈优化控制策略

为了提高插电式燃料电池混合动力汽车的经济性和燃料电池耐久性，在构建燃料电池衰退模型的基础上，制定等效氢气消耗最小（ECMS）的反馈优化控制策略。ECMS反馈优化控制策略中目标价值函数的等效氢气消耗除包括燃料电池氢气消耗和动力电池等效氢气消耗外，还将燃料电池开路电压衰退转化成等效的氢气消耗加入到目标价值函数之中，以电机需求功率P_m、动力电池SOC值为状态变量，动力电池目标功率为控制变量，取使目标价值函数最小的动力电池目标功率作为参考动力电池目标功率输出，并根据反馈的燃料电池电压衰退速率对燃料电池系统输出功率限制变化值ΔP_f进行动态调整，最终得到燃料电池目标功率。通过MATLAB/Simulink建立插电式燃料电池汽车前向仿真模型，采用城市道路循环（UDDS）工况进行验证。研究结果表明：相比基于规则的能量管理策略，电量保持（CS）阶段采用ECMS反馈优化控制策略，氢气消耗量降低2.6%，同时燃料电池的开路电压衰退降低4.1%，基于ECMS的反馈优化控制策略相比基于规则的能量管理策略在高效区间的工作点占比更高；与ΔP_f分别为1，2，3 kW时相比，采用燃料电池系统电压衰退速率反馈调节ΔP_f策略的氢气消耗量为0.105 3 kg，相比ΔP_f为1，2 kW的氢气消耗量（0.121 3，0.110 2 kg）有明显优化，接近ΔP_f为3 kW的氢气消耗量（0.102 9 kg），同时燃料电池电压衰退速率有明显的减小，整车经济性与燃料电池耐久性都得到了改善。     

Development of equivalent fuel consumption minimization strategy for hybrid electric vehicles

Power distribution between an internal combustion engine and electric motors is one of main features of hybrid electric vehicles that improves their fuel economy. An equivalent fuel consumption minimization strategy can instantaneously identify the optimal power distribution by converting the battery power into the equivalent fuel power and minimizing the overall fuel consumption. To guarantee the effectiveness of the strategy, it is essential to find the proper value of the conversion factor used to obtain the equivalent fuel power. However, finding the proper value is not a straightforward process because it is necessary to consider the overall power conversion efficiencies and battery charge sustaining strategy for the target driving cycle in advance. In this study, a model-based parameter optimization method is introduced to find the optimal conversion factor. A hybrid electric vehicle simulation model capable of estimating fuel consumption was developed, and the optimal conversion factor was discovered using a genetic algorithm that evaluates its population members using the simulation model. A series of simulations and vehicle tests was conducted to verify the effectiveness of the optimized strategy, and the results show a distinct improvement in fuel economy.     

New Optimal Power Management Strategy for Series Plug-In Hybrid Electric Vehicles

Recently Plug-in hybrid electric vehicles (PHEVs) have gained increasing attention due to their ability to reduce the fuel consumption and emissions. In this paper a new efficient power management strategy is proposed for a series PHEV. According to the battery state of charge (SOC) and vehicle power requirement, a new rule-based optimal power controller with four different operating modes is designed to improve the fuel economy of the vehicle. Furthermore, the teaching-learning based optimization (TLBO) method is employed to find the optimal engine power and battery power under the specified driving cycle while the fuel consumption is considered as the fitness function. In order to demonstrate the effectiveness of the proposed method, four different driving cycles with various numbers of driving distances for each driving cycle are selected for the simulation study. The performance of the proposed optimal power management strategy is compared with the rule-based power management method. The results verify that the proposed power management method could significantly improve the fuel economy of the series PHEV for different driving conditions.     

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。     

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.     

基于遗传算法系统效率优化的PHEV电量保持模式控制策略

为了提高插电式混合动力汽车（PHEV）在电量保持下的燃油经济性,并解决插电式混合动力汽车在运行过程中动力元件效率对系统能量利用率影响的问题,制定了系统效率最优的控制策略。以PHEV关键动力部件的测试数据为基础,建立发动机、驱动电机、无级变速器（CVT）以及动力电池等关键部件的效率数值模型,并考虑了温度及荷电状态（SOC）对动力电池充放电功率的影响。设计以混合动力系统效率最优为适应度评价函数,将CVT速比、发动机转矩作为优化变量,以车速、加速度和SOC为状态变量,在动力性指标的约束下,运用遗传算法进行迭代寻优,PHEV的系统效率在第20代左右收敛于全局最优值。同时发动机转矩和CVT速比通过多代遗传进化,较快收敛于最佳值。将相关优化结果与车速、加速度拟合成相应的三维控制数表,综合数值建模和试验测试数据建模的方法,基于MATLAB/Simulink搭建插电式混合动力汽车整车控制策略仿真模型,采用新欧洲行驶循环工况进行仿真验证。结果表明：插电式混合动力汽车在电量保持模式下,利用遗传算法优化的系统效率最优控制策略相比优化前,动力电池SOC运行更为平稳,CVT效率有所提升,驱动电机及发动机转矩分配更为合理;百公里燃油消耗量从优化前的5.2 L降至4.5 L,燃油经济性提升了13.5%。     

基于小波变换-模糊控制的复合电源能量管理

以锂电池-超级电容构成的复合电源电动汽车为研究对象,在满足动力性能的前提下,为实现超级电容在合理的荷电状态（SOC）下承担高频率信号,且锂电池承担低频率信号的目标,建立了实时小波变换-模糊控制的能量管理控制策略。基于Matlab/Simulink和ADVISOR软件搭建整车模型,并在NEDC循环工况下进行仿真测试。仿真结果表明,与单一锂电池相比,在小波变换-模糊控制策略下,复合电源锂电池的驱动峰值电流降低了20.68%,寿命提高了16.74%。搭建了按一定比例缩小的复合电源系统试验平台,并在NEDC工况下进行试验验证。结果表明,小波变换-模糊控制策略对复合电源电动汽车的能量管理具有良好的控制效果。     

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。     

Development of route information based driving control algorithm for a range-extended electric vehicle

A route information based driving control algorithm was developed for an RE-EV which consists of two motorgenerators, MG1 and MG2. A threshold power which controls the engine on/off to charge the battery was obtained by an optimization process using route information, such as the vehicle velocity and altitude. The threshold power allows the vehicle to travel to the final destination while making the final battery SOC close to SOC _low. Using the threshold power, route based control (RBC) was proposed by considering the driver’s characteristics and traffic conditions using the driving data base. In addition, a relationship between the threshold power and various initial battery SOC was obtained by off-line optimization. The performance of the RBC was evaluated by simulation and human-in-the-loop simulation (HILS) for city driving. It was found from the simulation and HILS results that the RBC achieved approximately 4 % to 12 % reduction in fuel consumption compared to the existing charge depleting/charge sustaining (CD/CS) driving control.     

混合动力电动汽车模糊逻辑控制策略的研究与仿真

以四川汽车工业集团野马混合动力电动汽车设计要求为基础,提出了一种混合动力电动汽车模糊逻辑控制策略。这种策略通过对油耗和各排放参数动态地分配权重值确定出发动机的最佳转矩,然后再根据模糊控制原理,以电池SOC值、汽车驱动需求的输出转矩和电动机转速为模糊输入确定出发动机的实际输出转矩,最终实现整车油耗和排放的综合优化。通过在S imu link软件中搭建该控制策略的仿真模型并与基础的电力辅助控制策略相比较,证明了这种控制策略有利于整车运行经济性和环保性的提高。     

HEV实时等效能量消耗最小控制策略

以变速器前置式并联结构为例,介绍了一种实时等效能量消耗最小控制策略。在研究车辆行驶于循环工况中消耗燃油热能和电能之间关系的基础上,针对该策略的关键问题———蓄电池组的电能和发动机的燃油热能消耗量的等效方法进行了详细阐述。最后在车辆仿真模型的基础上对该种策略进行仿真试验,并与其他类型的控制策略进行了比较。     

Modeling and simulation of fuel cell hybrid vehicles

A comprehensive procedure for mathematical modeling and validation of a fuel cell hybrid vehicle (FCHV) is presented in this paper. The subsystems are modeled based on lab testing and in-field vehicle testing results from the Tongji University Start prototype vehicle. An FCHV-SIM (fuel cell hybrid vehicle simulation) model is then developed based on the experimental data. Model validation results confirm that the FCHV-SIM model is reasonably accurate and suitable for model-based control development.     

PHEV复合储能系统设计及基于MODA的参数优化

为了提高插电式混合动力汽车的燃油经济性、降低污染物的排放,并解决插电式混合动力汽车单一动力电池低比功率、无法响应暂态功率需求的问题,设计蓄电池和超级电容并联的复合储能系统,采用带有滑动窗口的实时小波功率分配策略,并对滑动窗口长度进行选择。该功率分配策略将复合储能系统的需求功率分解成高频和低频两部分,超级电容接收高频分量,蓄电池接收低频分量,避免了高频分量对于蓄电池的冲击,提高了蓄电池的耐久性和可靠性。制定基于规则的控制策略,以整车燃油消耗量和污染物排放量为优化目标,利用多目标蜻蜓算法对相关控制参数进行优化。基于ADVISOR搭建含有复合储能系统的插电式混合动力汽车整车仿真模型,采用新欧洲行驶循环工况进行测试,并通过与带精英策略的非支配排序遗传算法进行对比,验证算法的有效性。研究结果表明：利用多目标蜻蜓算法优化后的车辆百公里燃油消耗平均降低了12.71%,污染物综合排放性能平均下降了10.05%;相对于优化前,发动机输出功率减少,电机输出功率增加,发动机和电机的工作效率均得到了显著提升;Pareto最优解的收敛性和覆盖范围优于带精英策略的非支配排序遗传算法,同时得到的多组Pareto最优解为整车设计和优化提供了更多选择。     

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).     

新型双能源电动汽车动力控制系统的仿真研究

从理论上分析了燃料电池／蓄电池双能源电动汽车的功率分配方法,并用SIMULINK建立了功率跟随模式控制策略的仿真模型。在ADVISOR上实现了对采用功率跟随模式控制策略虚拟样车的仿真,通过对仿真结果的分析验证了文中所述的控制策略。     

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.