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.     

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.     

多模式混合动力汽车控制策略研究

针对目前混合动力汽车结构的优缺点及发展现状,提出一种双电机双离合器混合动力结构,在该结构下可实现多种驱动形式,综合各模式优势,可充分利用发动机、电机及电池特性,尽可能地节省能耗.在该混动结构下搭建了基于逻辑门限值和基于ECMS的瞬时优化能量管理策略,仿真及试验分析表明,基于ECMS的瞬时优化能量管理策略与基于规则的策略...     

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.     

混合动力重型货车参数局部与集成优化仿真研究

动力耦合系统的动力源参数匹配和能量管理策略两者相互关联，为提高混合动力重型货车的综合性能，两者应集成设计。针对混合动力重型货车参数匹配需反复计算、验证的特点，在Matlab/Simulink中建立了可缩放、自动寻优的参数匹配模型。以经济性为目标函数，基于粒子群算法进行动力源参数匹配，得到局部最优动力源参数结果。针对混合动力重型货车中广泛采用的基于规则的能量管理策略，其规则控制中一些阈值参数不确定的问题，应用粒子群算法对其关键控制参数进行优化，得到局部最优控制参数。为了实现全局最优的匹配结果，将动力源部件参数和控制策略参数进行集成优化，以动力性为约束条件，经济性最优为优化目标，得到全局最优的参数匹配结果。对比显示，全局优化匹配效果相较于动力源参数局部优化提升11.4%、相较于控制策略参数局部优化提升12.4%。     

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.     

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).     

基于粒子群算法的Plug-in混合动力汽车能量管理策略优化研究

基于对混合动力汽车能量管理策略优化的目的,建立了丰田Prius Plug-in混合动力汽车的MATLAB/Simulink数学模型,用数学公式描述了系统优化控制问题,采用粒子群优化算法对该包含众多约束条件的非线性优化问题进行了求解,利用PSAT专业软件对比分析了基本型优化控制算法、改进型优化控制算法和规则控制算法等的控制效果及燃油经济性。结果表明,经过优化后的Plug-in混合动力汽车在不牺牲汽车各项性能的前提下能提高动力系统工作效率。     

基于系统效率最优的CVT混合动力轿车转矩优化分配方法

无级变速器CVT消除了挡位概念,其速比在一定范围内连续可调。配备CVT的混合动力汽车能够实现动力源转矩和传动系统的优化匹配。针对此问题,提出了基于系统效率最优的CVT中度混合动力轿车动力源转矩优化分配方法:。该方法:综合考虑了各个关键部件的效率,以混合动力系统的总体效率为优化目标,以车速、车辆加速度、电池SOC为状态变量,优化分配了驱动工况下各动力源输出转矩,为整车能量管理策略的制定奠定了基础。     

基于深度学习的混合动力汽车预测能量管理

为了优化混合动力汽车的能量动态分配过程,提升混合动力汽车的燃油经济性和动力电池荷电状态（SOC）平衡性,提高混合动力汽车能量管理策略的鲁棒性,以等效燃油消耗最小化策略为基础,结合对车辆未来行驶工况的预测研究,分析车辆未来行驶需求能量的变化,制定相应的动态调整策略。基于车联网通信技术,实时采集车辆的运行状态信息和交通信息,作为车辆未来工况预测模型的输入变量。以数据驱动为特征,基于混合深度学习建立工况预测模型。利用STL分解算法对各输入变量进行周期性、趋势性等特征分解,并对各输入变量的特征分量,使用混合深度学习网络从数据局部特征及时间维度依赖特征来深度挖掘目标车辆车速与外部信息及历史数据的关系,进而对车辆未来的行驶工况进行预测。利用预测的工况信息,分析车辆未来行驶需求能量的变化,应用于自适应等效消耗最小化策略等效因子的实时动态调整,从而实现对车辆的优化控制,并通过与传统自适应等效消耗最小化策略进行对比,验证该方法的有效性。研究结果表明：基于混合深度学习的工况预测模型预测精度比BP网络预测模型高44.72%;利用精确的预测工况信息预测能量管理,可以实时动态调整发动机和电机的功率输出,降低油耗并维持电池SOC平衡。     

基于提取PMP控制规则的FCHEV能量管理策略

针对FCHEV的能量管理问题,提出一种基于提取PMP控制规则的FCHEV能量管理策略.利用PMP优化算法解出的车辆在CHTC_C工况下离线最优控制序列,从最优控制序列中提取控制规则,实现能量管理策略的在线化.在MATLAB/Simulink上建立车辆模型,对所提能量管理策略进行仿真验证.仿真结果表明:所提能量管理策略能...     

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。     

基于混合系统理论的混合动力城市客车控制策略研究

在分析了串联式混合动力城市客车(SHEB)动力系统的结构和运行模式的基础上,应用混合系统理论描述了SHEB动力系统,并设计了一种基本规则型多能源动力系统控制策略.采用基于Simulink Stateflow的混合建模方法,建立了SHEB基本规则型多能源控制策略仿真模型,并嵌入到Advisor模型中进行仿真.最后对一辆实际SHEB进行了性能试验,验证了该控制策略的可行性和有效性.     

Energy management and design optimization for a series-parallel PHEV city bus

Series-parallel PHEV city buses combine the advantages of series and parallel configurations and have been used in China. However, the design and energy management of series-parallel PHEV city buses based on Chinese driving conditions still need to be investigated. In this paper, an equivalent consumption minimization strategy is provided to optimize energy management for series-parallel PHEV city buses, and the process of the equivalent consumption minimization strategy for series-parallel is presented in this paper. Compared with the validated rule-based energy control strategy, ECMS shows a fuel economy improvement of 8.2 % in the CBCD (Chinese Bus Driving Cycle). Based on the optimal energy management, a design for a generator motor in the series-parallel configuration has been processed. The fuel consumption has been shown to decrease, with an increase in generator power, because the system with the higher generator power can work at a higher efficiency in the series mode and operate the engine in the high efficiency area in the parallel mode. Besides, in terms of costof- ownership for a PHEV bus for lifetime of 8 years, although the high generator power will lead to high purchase cost for series-parallel PHEV bus, a series-parallel PHEV city bus with a generator of 100 kW maximum power will still show small advantage in cost-of-ownership, based on current motor price and natural gas price.     

Calibration efficiency improvement of rule-based energy management system for a plug-in hybrid electric vehicle

This paper presents a calibration method of a rule-based energy management strategy designed for a plug-in hybrid electric vehicle, which aims to find the optimal set of control parameters to compromise within the conflicting calibration requirements (e.g. emissions and economy). A comprehensive evaluating indicator covering emissions and economy performance is constructed by the method of radar chart. Moreover, a radial basis functions (RBFs) neural network model is proposed to establish a precise model within the control parameters and the comprehensive evaluation indicator. The best set of control parameters under offline calibration is gained by the multi-island genetic algorithm. Finally, the offline calibration results are compared with the experimental results using a chassis dynamometer. The comparison results validate the effectiveness of the proposed offline calibrating approach, which is based on the radar chart method and the RBF neural network model on vehicle performance improvement and calibrating efficiency.     

Optimized energy management control for the Toyota Hybrid System using dynamic programming on a predicted route with short computation time

Among the general problematic of the HEV power trains, the most critical point is the determination of the power-split ratio between the mechanical and the electrical paths, known as the energy management strategy (EMS). Many EMS are proposed in the literature, and can be grouped in two categories: the local optimization EMS and the global optimization EMS. The local optimization category corresponds to the EMS based on human expertise and the knowledge of the power train components efficiency maps. Thus, the local optimization EMS manages the power train operations by referring to predefined rules. The drawback of such strategies is that it brings an instantaneous fuel consumption optimization, and does not fully optimize the fuel consumption over the whole trip. Therefore, additional fuel savings are still possible. This paper presents an overall optimized predictive EMS for the Toyota Hybrid System (THS-II) power train of the Prius. The proposed EMS is based on Dynamic Programming (DP), where the prior knowledge of the route is required in order to predetermine the power-split ratio and optimize the fuel consumption for the whole predicted route. The DP EMS proposed for the THS-II power train is designed with a very short computation time, intended to be implemented in real-time applications. The potential of this DP-controller in reducing fuel consumption on regulatory cycles are computed and compared to a rule-based controller and to the Prius published fuel consumption results. Finally, the fuel reduction enhancements of the DP-controller are computed for real road tests achieved on a MY06 Prius in Ile-de-France, by comparing to the associated observed consumption measurements.     

系统综合效率优化的插电式混合动力车辆的能量管理策略

为了提升插电式混合动力汽车(PHEV)的动力系统的真实能效,从综合能效最优的角度,研究了插电式混合动力系统能量管理策略.针对系统综合效率的时变性和耦合性,建立了系统效率评价模型,对电池储存电能的效率进行评价和动态修正,以系统综合效率最优为目标,结合粒子群优化算法,构建了能量管理策略.基于GT-Suite和Simulin...     

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 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.     

混合动力汽车控制策略研究现状及发展趋势

混合动力汽车作为解决汽车工业节能和环保的一项新技术,目前已成为汽车研究和发展的焦点。文章对混合动力汽车研究中基于规则的稳态能量管理策略、模糊优化控制策略、瞬时优化控制策略和全局优化控制策略进行了分析和比较,指出了未来混合动力汽车控制策略研究的发展方向。混合动力能量管理控制策略是混合动力汽车的基础和核心,当前的混合动力控制策略还不是很理想和成熟,需要进一步的优化。