燃料电池汽车混合动力系统参数匹配与优化

首先分析燃料电池的特性得出了动力总成结构配置的优化解决方案,并且根据设计性能要求进行动力总成主要部件基本参数设计;最后基于典型的客车循环工况,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对混合动力系统的两种能量管理策略进行优化仿真,其结果符合设计要求。     

燃料电池混合动力客车等效氢耗优化策略

为了改进燃料电池混合动力客车的燃油经济性,基于等效氢耗理论,对燃料电池混合动力系统能量管理算法进行了优化.首先建立了系统瞬时氢耗模型,在该模型中,系统瞬时氢耗分为燃料电池瞬时氢耗和蓄电池等效瞬时氢耗2个部分;而后采用最小二乘算法辨识了蓄电池模型待定系数,求解了系统瞬时氢耗最小化问题,探讨了瞬时优化问题的本质;最后以解析解为基础建立了能量管理优化算法,并在中国城市公交典型工况中进行实车试验.结果表明:该工况下所研究的燃料电池城市客车百公里氢耗为9.3 kg,比采用基于规则的能量管理算法降低2.1%;通过提高燃料电池系统效率、降低整车辅助功率和采用制动能量回收策略可进一步提高系统经济性.     

电-气串联混合动力客车动力系统方案设计

基于对电-气串联混合动力客车运行目标驾驶循环的分析,对动力系统进行了方案设计。对混合动力系统的构型进行了设计,并基于城市公交驾驶循环对动力系统的主要零部件(发动机、发电机、电动机、蓄电池)进行选型计算。建立了整车仿真模型,对整车零部件的选型结果进行了仿真验证。仿真结果表明,所设计的动力系统方案可以满足整车动力性和经济性要求。     

基于运行数据的公交客车动力系统参数优化

为使公交客车在载客量和工况多变的情况下发挥混合动力系统的节能潜力，提出了基于运行数据的混合动力客车动力系统参数优化方法。基于车联网数据，利用核主成分分析（KPCA）和粒子群优化（PSO）K均值聚类分析构建了具有代表性的某市公交客车行驶工况；针对公交客车运营中乘客人数随机变化的特点，建立基于最优拉丁超立方设计（OptLHD）的混合动力客车动力系统参数双层优化模型，内层采用Opt-LHD产生乘客人数，采用发动机最优控制策略将系统响应传递至外层优化算法。仿真结果表明，优化后的动力系统参数对不确定因素有更强的适应性，燃油消耗量较优化前平均减少9.97%。     

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。     

混合动力客车用发动机ISG电机总成的台架测试系统

为满足混合动力客车动力系统的需要,开发一套基于CAN总线测控的台架测试系统,在台架上可实现混合动力客车用"发动机ISG"总成的工况测试。     

大功率型氢燃料电池重卡动力系统匹配设计

针对大功率型氢燃料电池重卡动力系统设计尚无成熟控制策略问题,提出了动力系统匹配设计中大功率型氢燃料电池保护优先的控制策略。根据该策略确定设计流程、零部件选型、参数匹配和计算。在此基础上,进行了动力系统构型优化,并基于稳态工况进行了燃料电池选型,同时综合考虑重卡实际工况特性和效率特性对氢燃料电池、动力电池和电机的功率以及传动比等参数进行匹配设计和零部件参数确定。基于设计结果,在Cruise中建立大功率型氢燃料电池重卡整车模型进行分析和优化,根据设计和优化结果完成了原型车的设计和制造,并初步进行了总体性能参数的验证。本研究为大功率型氢燃料电池重卡动力系统的匹配设计提供了参考。     

面向低油耗的燃料电池乘用车动力系统匹配设计

在绿色省能、零污染的燃料电池汽车的基础上,为提高“电-电”混合动力汽车的协调稳定性、动力系统的效率,满足动态性能的要求,开展对燃料电池/蓄电池的电-电混合动力汽车的动力系统匹配设计。文章以燃料电池汽车为研究对象,依据整车动力性能经济性指标开展了驱动电机、燃料电池系统、动力蓄电池系统的选型与参数匹配,引用混合度定义,考虑燃料电池和蓄电池混合动力系统间的功率配合,使用Advisor车辆仿真软件对常见工况下的各种匹配方案进行仿真计算。结果表明,从动力性以及燃油经济性方面,所确定的动力系统匹配设计方案具有一定的可行性,且符合车辆设计指标,即燃料电池（34 kW）与锂离子蓄电池（46 kW）的最佳匹配。两动力源之间合理的功率配合能够有效提高整车动力性,确保经济性,从而降低车辆的平均运行成本。     

并联混合动力轿车系统开发与试验匹配研究

采用基于超级电容的设计方案开发了单轴并联式混合动力轿车,对发动机、ISG电机、超级电容等零部件进行选型.研究了并联混合动力轿车动力系统的控制策略,优化匹配了发动机和电机的转矩分配,实现了混合动力节能并降低了排放.进行了混合动力系统的启动和怠速优化试验,实现了混合动力各个工况的控制参数的优化匹配,降低了启动污染物的排放,提高了燃油经济性.     

基于工况分析的混合动力系统设计

通过对上海典型城市工况循环的构建与分析得到了目标车型的基本行驶参数,并分析了加减速过程中整车能量消耗、功率消耗的分布情况。对该车混合动力系统控制策略进行了优化,并在ECE+EUDC联合工况下分别以混合动力模式和传统车模式进行了仿真对比。结果表明,以混合动力模式运行时,整车能够及时跟踪期望车速,并且能按预期目标实现发动机托动、怠速停机、加速助力和制动能量回收功能;该动力系统方案下混合动力运行模式比传统运行模式燃油经济性提高12%以上。     

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).     

Fuzzy energy management strategy for a hybrid electric vehicle based on driving cycle recognition

By considering the effect of the driving cycle on the energy management strategy (EMS), a fuzzy EMS based on driving cycle recognition is proposed to improve the fuel economy of a parallel hybrid electric vehicle. The EMS is composed of driving cycle recognition and a fuzzy torque distribution controller. The current driving cycle is recognized by learning vector quantization in driving cycle recognition. The torque of the engine and the motor is controlled by a fuzzy torque distribution controller based on the required torque of the hybrid powertrain and the battery state of charge. The membership functions and rules of the fuzzy torque distribution controller are optimized simultaneously by using particle swarm optimization. Based on the identification results of driving cycle recognition, the fuzzy torque distribution controller selects the corresponding membership function and rule to control the hybrid powertrain. The simulation research based on ADVISOR demonstrates that this EMS improves fuel economy more effectively than fuzzy EMS without driving cycle recognition.     

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.     

Design methodology of hybrid electric vehicle energy sources: Application to fuel cell vehicles

This paper presents a methodology to optimize the sizing of the energy and power components in a fuel cell electric vehicle from the driving mission (which includes driving cycles, a specified acceleration and autonomy requirements). The fuel cell and the Energy Storage System associated (battery or/and ultra capacitor) design parameters are the numbers of series and parallel branches respectively Nsi and Npi. They are set so as to minimize the objective function that includes mass, cost, fulfilling the performance requirements and respect the technological constraints of each power component through a penalty function. The methodology is based on a judicious combination of Matlab-Simulink® for the global simulation and a dedicated software tool Pro@Design®. Both are well suited to treat inverse problems for the optimization. An application for a fuel cell/battery powertrain illustrates the feasibility of the proposed methodology.     

增程式电动汽车动力系统参数匹配及控制策略优化

针对增程式电动汽车动力系统参数匹配的问题,在Simulink-Cruise联合仿真平台上建立了用于匹配设计的整车初始模型,提出了基于典型工况统计分析的匹配设计方法,对增程式动力系统进行了稳态匹配。为了进一步验证设计参数的合理性,采用恒温式定点控制策略和CD-CS型最优曲线功率跟随控制策略进行了仿真对比分析,验证了匹配参数的合理性。以燃油经济性、发动机启停次数和平均充电电流为目标,基于粒子群算法对控制参数进行了多目标优化。优化结果表明,优化后的控制策略使整车在目标工况下的百公里综合油耗下降了7.2%,平均充电电流下降了3.1%,优化后的控制参数使整车性能和电池寿命都有所提升,为进一步的控制策略制定和优化奠定了基础。     

Simulation of city bus performance based on actual urban driving cycle in China

This paper establishes the simulation model of a city bus on the basis of the EQ6110 bus prototype and its experimental data. According to the actual urban driving cycle, the fuel economy and the traction performance of the EQ6110 city bus have been simulated, and factors such as the driving cycle, the loss of power to engine accessories, the gear-shifting strategy, the fuel shut-off strategy of the engine, etc., which influence on the bus’s fuel economy, are also quantitatively analyzed. Some conclusions are drawn as follows: (1) driving cycles have a great influence on the fuel economy of a city bus; (2) under the typical urban driving cycle of the public bus in China, the engine fuel shut-off strategy can save about 1 to 1.5 percent of the fuel consumption; and (3) the optimized gear-shifting rules can save 6.7 percent of the fuel consumption. Experimental results verify that the fuel economy for the EQ6110 public bus is improved by 7.2 pecent over the actual Wuhan urban driving cycle of the current public bus in China.     

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。     

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.