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.     

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.     

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%。     

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.     

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.     

Chevrolet Volt on-road test programs in Canada part 1: Effects of drive cycle,ambient temperature and accessory usage on energy consumption and all-electric range

Environment Canada (EC) and Natural Resources Canada (NRCan) separately tested two 2012 Chevrolet Volts between 2013 and 2014 in Ottawa, Ontario on public roads in the summer and winter months using realistic cabin-climate control settings. More than 1300 trips were conducted over nine routes: three city, one congested, two arterial, one highway and two expressway routes. EC tests recorded cabin conditioning, traction battery and 12 V accessory power, select vehicle component temperatures, regulated emission rates and exhaust flow, and DC charge energy. Both NRCan and EC tests measured cumulative electrically driven distance (all-electric range), select CANbus signals and AC grid supply charge energy. Results from these studies were analysed to evaluate the overall performance of the Chevrolet Volt on public roads in climates representative of most of Canada (-27 °C to 37 °C) using realistic accessory settings. At 25 °C the Chevrolet Volt’s on-road all-electric EPA-method adjusted range is generally less than the U.S. EPA sticker rating (57.9 km). Cabin conditioning energy was found to be directly related to the difference between ambient and cabin temperature, except at low temperatures (< 0 °C) when the 1.4 L engine activates to assist the thermal management system. On average, heating the cabin in the winter months consumed significantly more electric energy than cooling the cabin in the summer months. Summer city and highway driving resulted in the lowest energy consumption (Wh/km), while congested and expressway driving cycles resulted in the highest. In the winter months, many differences between the drive cycles were not discernible due to the high cabin conditioning energy consumptions.     

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。     

燃油经济模式的蓄电池电压控制系统研究

铅酸蓄电池通过化学能和电能的转换,能够为车辆储存电能和释放电能。如果蓄电池电量充足,在进入燃油经济模式后,可以通过控制蓄电池工作电压,使其放电为用电器供电,减少燃油消耗。本文在分析蓄电池工作原理和燃油经济模式特点的基础上,研究了基于反馈控制的蓄电池电压控制系统,设计了最优充电电压控制算法,并通过车辆在燃油经济模式的试验进行验证,进而优化参数设计,使系统和算法更加合理和稳健。     

液冷和冷媒直冷动力电池包冷却性能数值分析

采用数值模拟的研究方法，对比分析了某纯电车型在高速超速以及驱动耐久工况下动力电池包采用液冷和冷媒直冷两种方案的冷却性能，研究结果表明，对于高速超速工况，相对于液冷方案，采用冷媒直冷电池包温度降低了约10%；对于驱动耐久工况，采用冷媒直冷方案电池包温度降低了约 16%，与此同时，电池包均温性也有所改善。在相同工况条件下，动力电池包冷媒直冷的冷却性能优于液冷。     

Modeling and control strategy development for fuel cell hybrid vehicles

Using MATLAB/Simulink, we constructed a comprehensive simulation model for the fuel cell hybrid vehicle (FCHV) power train in parallel with a power control strategy that uses a logic threshold approach implemented with a hybrid control unit (HCU). The simulation implements power flow and power distribution under different vehicle operating modes using the accelerator and decelerator pedal positions deduced from the driving schedule as primary inputs. The HCU control strategy also incorporates regenerative braking and recharging for recovery of battery capacity. Using the D-optimality method for selection of the optimal experiment values, three control threshold variables for the HCU are selected to maximize the hydrogen fuel economy under certain driving cycles. The proposed method provides the optimal configuration of the FCHV model, which has the capability of achieving the requested drive power while also meeting the vehicle driving schedule and recovery needs of the state of charge (SOC) battery, with lower fuel consumption levels.     

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。     

增程式电动车动力电池组低温行车预热策略

为了提高动力电池组低温环境下的放电效率,针对增程式电动车低温行车条件,考虑电池组预热过程中单体温度的不一致及单体排布等因素的影响,进行增程式电动车动力电池组低温行车预热策略研究。采用Chrom_17011充放电测试机及高低温恒温箱对26650磷酸铁锂电池单体进行低温试验与AMESim模型仿真对比的方法验证预热模型的精度,分析发动机怠速为电池组进行预热时,水泵转速、串行通风鼓风量、串行通道单体数量及单体与单体之间的间隙对电池包内入、出口单体温差的影响。通过整车仿真,分析行车预热策略与传统CDCS策略在不同环境温度下对等价燃油消耗量的影响。研究结果表明：在单体排布间距固定和水泵转速为800 r·min^-1的条件下,电池包串行通风风量越大,串行通道入、出口单体温差越小,单体预热时间相对较长,且在串行通风风量不小于3 g·s^-1的条件下,能满足电池包串行通道最大温差小于5℃的要求;环境温度在-20℃时,行车预热策略比CDCS策略等价燃油消耗率降低16.25%,纯电动续驶里程增加9.95 km;其影响等价燃油消耗率的因素有制动能量回收量和内阻消耗量,内阻消耗量是影响等价燃油消耗率升高的主要因素。     

发动机热管理系统对整车节油性能的评估

优化车辆发动机热管理的结构形式与控制模式是提高车辆节油性能的重要途径,本文在公交客车平台基础上,比较了基于电动风扇冷却的新型发动机热管理系统与由皮带直驱的风扇冷却系统,阐述基于电动风扇冷却的发动机热管理系统对整车节油性能的贡献。     

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.     

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。     

车载动力电池液体冷却非线性优化方法研究

电动汽车动力电池散热需求会受到外部环境温度、风速和负载电流变化等因素的影响,如果不及时散热,动力电池的温度会迅速攀升,进而影响电动汽车的驾驶性和安全性。基于此提出一种锂离子电池非线性冷却优化方法。首先,通过对锂离子电池生热、散热机理分析,建立考虑传热系数随冷却液流速变化的锂离子电池集中热模型,通过电池特性测试试验确定电池内阻和熵热系数等热物性参数,并与AMESim模型对比,验证模型的有效性。然后,基于电池冷却系统非线性和易受负载电流变化影响的特征,提出一种考虑电池冷却系统的稳态特性以及参考变量前馈功能和闭环反馈消除静态误差机制的非线性冷却优化方法,并对其稳定性和鲁棒性进行研究。仿真结果表明:在NEDC-HWFET-US06组合工况下,非线性冷却优化方法调节下的电池温度与目标温度的最大偏差较PID方法减小了0.8 K,并且冷却过程的能耗降低了6.3%,具有更好的调节效果。     

Effect of UWS injection at low exhaust gas temperature on NO<Subscript>x</Subscript> removal efficiency of diesel engine

Urea-SCR systems have been widely used in diesel vehicles according to the strengthened NO_x (Nitrogen Oxides) emission standard. The NO_x removal efficiencies of the latest well optimized urea-SCR system are above 90 % at moderate exhaust gas temperature of 250 ~ 450 °C. However, a large amount of NO_x is emitted from diesel vehicles at cold start or urban driving conditions, when the exhaust gas temperature is not high enough for SCR catalyst activation. Although many researchs have been stuied to improve NO_x conversion efficiency at these low temperature conditions, it is still one of important technical issues. In this study, the effect of UWS injection at low exhaust gas temperature conditions is studied. This study uses a 3.4 L diesel engine equipped with a commertial urea SCR system. As a result, it is found that about 5 % of NO_x removal efficiency is improved in the NRTC test when UWS injection starts at the SCR inlet temperature of 150 °C compared to 200 °C. It is also found that urea deposits can be formed on the wall of exhaust pipe, when the local wall temperature is lower than temperature of urea decomposition.     

功率分流混合动力全速域工作模式切换规则优化

针对某功率分流混合动力汽车，探讨了既定模式转矩分配策略未知情况下全速域工作模式切换规则的优化问题。先在既定模式转矩分配策略未知的前提下，将等效燃油消耗与样本数字特征相结合，计算了不同荷电状态（SOC）值下各工作模式在所有可行工作点的基准综合燃油消耗率。以整车燃油经济性为优化目标，确定不同SOC值下所有可行工作点的最佳工作模式，进而得出基于车速、车轮端需求转矩、SOC值的优化后全速域工作模式切换规则，以满足不同工况下的工作模式选择需求。之后，不考虑模式切换过程对整车驾驶平顺性的影响，搭建了模式切换实施模型。再以4个新欧洲驾驶循环（NEDC）工况所构成的组合工况为目标行驶工况，将优化后全速域工作模式切换规则和传统基于逻辑门限的全速域工作模式切换规则分别应用于基于规则的能量管理策略，进行了整车燃油经济性仿真与台架试验验证。仿真结果表明：在不改变既定模式转矩分配策略的条件下，与基于逻辑门限的全速域工作模式切换规则情况相比，所提出的既定模式转矩分配策略未知情况下全速域工作模式切换规则优化方法至少可使整车燃油经济性提高7.33%。台架试验结果进一步表明，该优化方法至少可使整车燃油经济性提高6.17%。由此可见，所提出的既定模式转矩分配策略未知情况下全速域工作模式切换规则优化方法对整车燃油经济性具有较好的改善效果。