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.     

Analysis of planetary gear hybrid powertrain system part 2: Output split system

In recent studies, various types of multi-mode electric variable transmissions for hybrid electric vehicles have been proposed. A multi-mode electric variable transmission consists of two or more different types of a planetary gear hybrid powertrain system (PGHP), which can change power flow type using clutches to improve transmission efficiency. Input split systems are generally used for the single-mode powertrain because of their overall superiority, but other power split systems such as output split and compound split systems can be used in the dual-mode powertrain. In this study, we analyze the power transmission characteristics of output split systems, and evaluate their fuel economies in the FTP72 cycle, acceleration performance, and constant vehicle speeds. These results enable the selection of appropriate systems for a dual-mode powertrain.     

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.     

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.     

Model Predictive Coordinated Control for Dual-Mode Power-Split Hybrid Electric Vehicle

Power-split hybrid electric vehicles (HEVs) have great potential fuel efficiency and have attracted extensive research attention with regard to their control system. The coordinated controller in HEV plays an important role in tracking the optimal state reference generated by the energy management strategy (EMS), so as to reach the desired fuel efficiency. Meanwhile, the coordinated controller also has a significant impact on driving performance. To improve its performance, the design of a model predictive control (MPC) based coordinated controller in power-split HEV is presented. First, a non-linear, time-varying constrained control oriented transmission model of a dual-mode power-split HEV is formulated to describe this control problem. Then, to solve this problem, the non-linear part in the transmission model is linearised, and a linear MPC is used to obtain the control signals for the motors and engine at each time step. To meet the requirements of real-time computation, a fast MPC method is also applied to reduce the online computation effort. Simulations and experiments demonstrate the effectiveness of the proposed MPC-based coordinated controller.     

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.     

并联式混合动力汽车传动系参数优化

为了充分发挥混合动力汽车的优越性,文章以整车燃油经济性的评价为基础,通过分析混合动力汽车动力系统的组成,建立了燃油经济性最佳的数学模型;依据考虑汽车的动力性和动力电池的荷电系数要求,使用复合形优化方法对目标函数进行了优化：并利用具体车型对优化方法进行了验证。结果表明,100km油耗降低21％,经济性得到较大提高,动力性仍然保持设计要求？指出采用逆向求解的手段来获得汽车的燃油经济性,并以其为目标函数开发的优化设计系统,能较好地改善汽车的燃油经济性,此优化方法对普通汽车的传动系统优化也具有参考作用。     

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.     

基于ADVIS0R的混合动力SUV

在我国SUV保有量迅速增加,油耗高且污染严重,而混合动力技术可以弥补这方面的缺陷。文章以国内桌SUV为例,对其改为混合动力后的驱动型式、动力总成参数的确定及性能预测等方面进行了研究并对仿真软件ADVISOR进行二次开发以便于四轮驱动的仿真分析。结果表明,与原车相比,混合动力SUV最高车速提高了32％,最大爬坡度提高了37％,油耗降低了29％,同时能在纯电动模式下以50km／h的速度行驶43．8km。指出改进后的混合动力SUV具有更好的动力性和经济性,满足了设计要求     

Fuel economy comparison of conventional drive trains series and parallel hybrid electric step vans

A hybrid electric vehicle (HEV) is a vehicle that combines a conventional propulsion system with an on-board rechargeable energy storage system to achieve better fuel economy than a conventional vehicle HEVs do not have limited ranges like battery electric vehicles, which use batteries charged by an external source. The different propulsion power systems may have common subsystems or components. The objective of this study is to compare the fuel economies of a conventional step van, a series hybrid electric step van (HESV), and a parallel HESV by calculating the fuel consumption using the ADVISOR software by NREL. We also showed the results of the vehicles in different driving cycles including the Central Business District bus cycles, the New York City Cycle, and the US EPA City and Highway cycles.     

Torque control of engine clutch to improve the driving quality of hybrid electric vehicles

As a powertrain for hybrid electric vehicles (HEVs), the automatic transmission (AT) is not only convenient for the driver but also reduces hybridization costs because the existing production line is used to produce the AT. However, it has low fuel economy due to the torque converter. To overcome this disadvantage, this paper studies HEVs equipped an AT without a torque converter. In this case, additional torque control is needed to prevent the driving quality from deteriorating. This paper suggests three different torque control methods and develops a simulator for an HEV that can simulate the dynamic behaviors of the HEV when the engine clutch is engaged. The HEV drive train is modeled with AMESim, and a controller model is developed with MATLAB/Simulink. A co-simulation environment is established. By using the developed HEV simulator, simulations are conducted to analyze the dynamic behaviors of the HEV according to the control methods.     

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.     

Development of test system for motor of hybrid electrical vehicle

The motor units of hybrid electric vehicles (HEVs) have been developed with the aim of achieving good fuel economy and low emissions. We have developed a system for evaluating the performance of an HEV motor unit under various driving patterns. We review the function and performance of this system.     

基于小波变换的燃料电池混合动力系统多能源管理策略研究

设计了一种由燃料电池、超级电容和锂离子电池组成的新型混合动力系统;提出了一种基于小波变换的燃料电池混合动力能量管理策略,实现了按功率需求的变化频率对燃料电池、超级电容和锂离子电池进行能量分配,从而改善了系统的性能,延长了部件寿命;进行了该系统的建模和仿真,结果表明该方法可以很好地实现功率分配,满足设计要求。     

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.     

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.     

Design methodology of component design environment for PHEV

In this study, the design methodology for PHEV component design environment is proposed, which consists of power evaluation, component evaluation, component analysis and vehicle performance evaluation environments. First, PHEV simulators were developed based on the dynamic model of the target PHEV powertrain, and a PHEV control algorithm was designed based on the general power-split type PHEV using MATLAB/Simulink. Experimental results were used to validate the constructed PHEV simulators. The power evaluation environment provides the magnitude and direction of the power between components at the vehicle level at any selected time that the user wants to evaluate. The component evaluation environment is designed to evaluate the parameter behaviors of a component using the effort-flow causality relationship. The component analysis environment is designed to investigate component performance according to the variations of component parameters. The vehicle evaluation environment is designed to evaluate equivalent fuel economy at any selected time. It is expected that the design methodology of the PHEV component design environment proposed in this study can be extended to other x-EVs for evaluating and designing vehicle components.     

基于多目标遗传算法的混合电动汽车参数优化

动力系统和控制器参数的同时优化是提高混合电动汽车(HEV)燃油经济性并降低排放的关键。这类优化问题涉及多个相互冲突的优化目标和非线性约束,是典型的多目标优化问题。文中采用多目标遗传算法求解该优化问题的Pareto最优解集,并应用ADVISOR对实际算例的优化结果进行比较分析。结果表明,应用该方法可找到多组可行解,在满足原车动力性要求的前提下能有效提高燃油经济性,降低排放。     

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。