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.     

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).     

插电式并联混合动力客车建模及仿真

基于Advisor软件中并联混合动力客车仿真模型,建立插电式并联双离合器混合动力客车仿真模型,并对发动机、电机、传动系和电池等进行参数匹配;分析电力辅助控制策略,利用正交设计对其控制参数进行优选研究。仿真结果表明,动力系统主要参数及整车控制策略设计合理,满足整车性能要求。     

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.     

Integrated modeling and optimization of a parallel hydraulic hybrid bus

Hydraulic hybrid powertrains are a critical technology used in buses to improve fuel economy and emission performance. New exploration in configuring a parallel hydraulic hybrid bus (PHHB) is developed in this paper with no changes made to the conventional base bus driveline. An integrated model and simulation of the parallel hydraulic hybrid bus is built based on AMESim, which is used to model the hydraulic powertrain and conventional bus driveline, and interlinked with a Matlab/Simulink/Stateflow model of the control unit. Compared to conventional buses, the fuel economy of the PHHB improved by 28% in real road tests at the SMVIC (National Center of Supervision and Inspection on Motor Products Quality (Shanghai)); the approximate improvement of fuel economy was 30% in simulated runs, which validates our model. Then a Non-linear Programming by Quadratic Lagrangian algorithm (NLPQL), is applied to optimize control strategies for improving fuel economy and emissions. Simulations also demonstrate that fuel economy and emission performance can be significantly improved. However, optimum parameters for maximum fuel economy and minimum emissions are not consistent. Simulation results show tradeoffs between fuel economy and emissions in PHHB, and optimal parameters can be selected by balancing design objectives.     

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.     

基于烟花算法的PHEV能量管理策略参数优化

为改善插电式混合动力汽车(PHEV)的燃油经济性,提出一种基于规则的能量管理策略。结合智能网联汽车技术,利用烟花算法(FWA)结合系统约束条件,对能量管理策略参数进行优化,以求使车辆在变化的路况下能耗最低。为减轻沉重运算负荷,设计了一种事件触发机制来控制优化操作的启停。当车辆油耗超过预设上限则开始优化,一旦油耗满足预设下限则优化结束。在中国典型城市工况下,验证了该策略的有效性及优化性能。结果显示:较优化前的能量管理策略,该方案可使PHEV燃料消耗降低10%。从而,使燃油经济性明显提升。     

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.     

基于能耗计算的并联式混合动力汽车控制策略

以某款并联式混合动力汽车为例,根据对工况点进行能耗计算的结果,将其动力总成工作区域划分为4个区域,分别对应于动力总成4个不同的工作模式.在此基础上制定了相应的控制策略,建立了动力总成Matlab模型并进行仿真.结果表明,整车的燃油经济性得到了明显提高.     

液压混合动力公交车动力性能仿真与试验研究

将EQ6110公交车改造为并联式液压混合动力公交车,基础车的动力系统不作改变,建立了液压混合动力公交车模型,对液压系统独立工作时的驱动和制动性能进行了仿真及实车试验,为系统的参数匹配提供依据.采用简化公交循环工况的实车试验表明,动力性能满足起步和制动要求,燃油经济性改善达25%以上;另外,仿真结果也表明,动力性能可以满足国家典型公交行驶循环下的起步和制动性要求,制动再生效率达70%,燃油经济性改善达30%.     

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。     

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。     

Emissions simulation in a 7000 kg-grade diesel hybrid electric vehicle

Hybrids combine a combustion engine with an electric motor and battery. The two technologies can be combined to reduce fuel consumption and exhaust emissions. This paper presents the concept of hybrid electric vehicles (HEVs) applied to truck or van vehicles with diesel engines. The simulation results from the advanced vehicle simulator (ADVISOR) demonstrate that the required power may be properly shared between the internal combustion engine and electric motor. The simulation can also be used to prove that the technique is useful for improvements in driving performance; additionally, the technique is suitable for hybrid electric vehicles, allowing for good fuel economy and low emissions performance.     

燃料电池混合动力汽车动力系统匹配与优化研究

首先,基于中国客车典型循环工况对燃料电池混合动力系统进行匹配计算,确定了电动机、燃料电池发动机和蓄电池的基本参数;然后基于中国客车典型循环工况,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进行优化,分析了各种参数对整车燃料经济性的影响,包括燃料电池发动机与动力蓄电池之间的功率分配比、SOC的初始值与目标值、变速器传动比及传动比间隔以及主减速比等,为燃料电池混合动力汽车的构型提供指导。     

Development of an auxiliary mode powertrain for hybrid electric scooter

This paper proposes a design and implementation of an auxiliary mode, hybrid electric scooter (HES) by means of more cost-effective way for improving scooter’s performance and efficiency. The HES is built in a parallel hybrid configuration with a 24V 370W auxiliary power electric motor, a 24V 20AH battery, and an electronically controlled fuel injection internal combustion engine (ICE) scooter. In contrast to hybrid electric vehicles (HEVs), the issues concerning cost, volume, and reliability are even more rigorous when developing hybrid electric scooters (HESs). Therefore, the drive topology and control strategy used in HEV cannot be applied to HES directly. In order to hasten the developing phase and achieve the parametric tune-up of the HES component, a dynamic simulation model for the HES is developed here. Because the powertrain system is complex and nonlinear in nature, the simulation model utilizes mathematical models in tandem with accumulated experimental data. The method about the mathematical model construction, analysis and simulation of the hybrid powertrain used in a scooter are fully described. The efficacy of the model was verified experimentally on a scooter chassis dynamometer and the performance of the proposed hybrid powertrain is studied using the developed model under a representative urban driving cycle. Finally, Simulation and experimental results confirm the feasibility and prosperity of the proposed hybrid HES and indicate that the designed hybrid system can improve the fuel consumption rate up to 15% compared with the original scooter.     

A comparative study on the power characteristics and control strategies for plug-in hybrid electric vehicles

A comparative study was performed on two types of plug-in hybrid electric vehicles (PHEVs): the GM Volt and the Toyota Prius Plug-in Hybrid. First, the powertrain models of the two vehicles were derived. Based on the dynamic models, a detailed component control algorithm was developed for each PHEV. Specifically, a control algorithm was proposed for motor generator 1 (MG1) and MG2 to achieve optimal engine operation. Additionally, an energy management strategy for selecting the operation mode was developed from the viewpoint of fuel economy, battery state of charge and vehicle velocity. Using the dynamic model of the control algorithm for each PHEV, simulations were performed, and the simulation results were verified by comparing them with those obtained using the Powertrain System Analysis Toolkit simulator for the plug-in Prius. Based on the simulation results, a comparative study was performed, and it was found that the role and capacity of MG1 and MG2 and the mode selection algorithm must be determined depending on the configuration of the PHEV.     

From Offline to Adaptive Online Energy Management Strategy of Hybrid Vehicle Using Pontryagin’s Minimum Principle

This paper details the development of an energy management strategy (EMS) for real-time control of a multi hybrid plug-in electric bus. The energy management problem has been formulated as an optimal control problem in order to minimize the fuel consumption of the bus drivetrain for a typical day of operation. Considering the physical characteristics of the studied hybrid electric bus and its well-known daily tour, the Pontryagin’s minimum principle (PMP) is firstly used as the mean to obtain offline optimal EMS. Afterward, in order to adapt the proposed strategy for real-time implementation, the proposed control parameters are adapted online using feedback from the battery state of energy (SOE) which allows us to accurately control the battery SOE in the presence of wide range of uncertainties. The work proposed in this paper is conducted on a dedicated high-fidelity dynamical model of the hybrid bus, that was developed on MATLAB/TruckMaker software. The performance evaluation of the proposed strategy is carried out using a normalized driving cycles to represent different driving scenarios. Obtained results show that among the investigated methods, it is reasonable to conclude that the proposed adaptive online strategy based on PMP is the most suitable to design the targeted EMS.     

Matlab-based modeling,simulation and design package for Eletric,Hydraulic and Flywheel hybrid powertrains of a city bus

In this paper a package for designing, modelling and simulation of three hybrid powertrains are presented. These powertrains are Electric hybrid, Hydraulic hybrid and Flywheel hybrid. The differences among the proposed hybrid powertrains include the energy storage system components, the secondary power converter and also the powertrain configuration. The O457 city bus is considered as the benchmark vehicle. At first, the design process for each hybrid powertrain which is based on the power requirements of the bus in any driving condition is presented. Then, the powertrains modelling using MATLAB/Simulink as a powerful simulating tool is presented. The models are feed-forward and resemble the real world driving conditions. Each model has the blocks for the main components of the corresponding propulsion system. The most important stage in the modeling process is implementing of the components efficiency in each powertrain. Moreover, there is a block in each hybrid powertrain model for the energy management. Finally, the simulation results for comparing the usefulness of the hybrid powertrains are presented. The results indicate that the electric hybrid powertrain has the most effect on reducing the bus fuel consumption. But regarding the fabrication expenses and manufacturing complexity, the hydraulic hybrid powertrain is recommended.     

基于ADVISOR仿真的混合动力客车动力系统匹配研究

分析一种单轴并联式混合动力系统的工作原理,对动力总成关键部件进行匹配计算。在Matlab/Simulink环境下,对电动汽车仿真软件ADVISOR进行二次开发,嵌入动力系统的控制策略,对整车进行动力性和经济性仿真分析,为混合动力客车动力系统的匹配设计提供参考。     

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。