基于遗传算法的串联混合动力汽车参数优化

控制策略参数优化是提高混合动力汽车燃油经济性和降低排放的关键,这类优化问题涉及多个相互冲突目标,而且属于非线性约束问题。文中采用遗传算法,基于MATLAB编程,调用ADVISOR对混合动力汽车参数进行优化,结果表明,该方法可找到多组可行解,在保证车辆动力性前提下提高燃油经济性和降低排放。     

混合动力客车与充电式混合动力客车仿真对比研究

为了降低客车排放,提高其燃油经济性,研究了混合动力客车的燃油消耗率。开发了柴油机模型和公交道路循环模型。以燃油消耗率和排放为主要评估指标,在ADVISOR软件中利用新开发的模型分别对混合动力客车和充电式混合动力客车进行了仿真。仿真分析的结果表明：在公交路况下,充电式混合动力客车的燃油经济性优于混合动力客车,油耗降低62％。     

低烯烃汽油在汽车发动机中的应用研究

选择两种不同烯烃含量的汽油分别进行了发动机台架试验、整车性能与排放试验,以考核燃油中烯烃含量对发动机动力性、经济性和排放性能的影响。研究结果表明,使用低烯烃汽油能改善发动机的动力性和燃油经济性,降低NOx排放。     

遗传算法在混合动力汽车参数优化中的应用

混合动力汽车的动力部件参数和控制器参数对整车燃油经济性和排放有重要的影响。文章分别以基于遗传算法的3种算法：权重系数法、并列选择法和共享函数法对一辆样车的参数进行离线仿真。结果表明,应用这些方法获得的优化参数,在满足车辆特定性能的前提下能有效地减少油耗和降低排放。对比分析优化结果,找出最适合HEV参数优化的算法,并给出参数优化的多组Pareto最优解。     

基于最小瞬时等效燃油消耗的液压混合动力车辆能量管理策略

为提高混合动力车辆的燃油经济性和降低尾气排放,根据混合动力车辆2个或2个以上能量流之间的功率分流分配和能量利用情况,提出了最小瞬时等效燃油消耗量策略.通过分析串联式液压混合动力传动能量流关系,以储能元件蓄能器的虚拟等效燃油消耗为准则,建立了液压混合动力车辆最小瞬时等效燃油消耗模型.对液压混合动力车辆能量管理进行了研究,并以某型公共汽车参数为例,运用计算机软件通过城市循环工况第1部分和公路循环工况对使用该策略的液压混合动力车辆燃油经济性进行了仿真计算.仿真结果表明:采用最小瞬时等效燃油消耗策略的液压混合动力车辆的燃油经济性改善率接近30％;采用最小瞬时等效燃油消耗策略在提高车辆节能效果上具有较明显的优势.     

再生制动回收能量增大对混合动力卡车燃油耗及排放特性的影响

为了证明增加回收再生制动能量与混合动力卡车的燃油经济性和废气排放特性之间的关系进行了一系列试验。研究人员在混合动力-传动系台架试验装置的发动机上,组合排气后处理装置,改变混合动力-传动系统的结构和混合动力控制方法,以及回收减速能量控制方法,以此研究混合动力卡车的燃油经济性和排放特性。研究表明,即便在3～15km的低的制动速度下进行混合动力卡车的再生制动控制,总再生电能提高14.7%,燃油经济性提高3.1%。此外,高效率发动机驱动的混合动力卡车的废气排放温度与柴油机卡车相同,排放性能得到了改善。     

ISG柴油混合动力客车能量分配策略研究

以ISG柴油混合动力客车整车控制策略为基础,综合考虑客车燃油经济性和排放,提出一种基于模糊神经网络的能量分配策略,该策略根据模糊控制原理,结合人工神经网络自主学习功能,以电池SOC、整车需求转矩以及发动机转速为模糊输入来确定发动机和电机的最佳输出转矩分配,再以神经网络对控制的模糊规则进行记忆.仿真结果表明,该策略比普通逻辑控制更加有利于燃油经济性的提高,并在一定程度上改善了排放性能.     

BSG混合动力轿车动力系统参数设计及试验研究

介绍了BSG混合动力轿车动力系统的结构及工作原理,对发动机、BSG电机、蓄电池以及传动系传动比进行了参数设计,并对BSG电机不参与工作和参与工作两种状态下轿车的动力性、燃油经济性和排放性能进行了对比试验.试验结果表明,BSG电机参与工作时BSG混合动力轿车的动力性、燃油经济性和排放性能均有显著改善.     

共轨柴油机燃烧纯生物柴油的试验研究

对一台国产涡轮增压直喷柴油机燃烧0#柴油和纯生物柴油的动力性、燃油经济性和排放性能进行对比试验研究。试验结果表明,在柴油机不进行任何调整的情况下,燃烧纯生物柴油会降低其动力性和燃油经济性,但可大幅度改善CO、HC和PM的排放性能。     

“透过上海车展,看汽车新技术”系列报道之四 汽油发动机技术的发展趋势

在本世纪头10年间,车用汽油发动机的动力性能、燃油经济性及排放性能都得到了稳步提高,尤其是燃油经济性每年降低的幅度超过2%,这为降低二氧化碳排放做出了极大的贡献。实现这些进步的关键技术是缸内直接喷射技术及其燃油喷射系统、可变气门配气机构、涡轮增压以及高效率的排气后处理装置。     

基于遗传算法的混合动力汽车参数多目标优化

针对混合动力汽车设计参数众多的状况,提出了一种对混合动力汽车传动系统参数和控制参数同时进行优化的多目标优化新方法--自适应遗传算法.在ADVISOR平台上,以一辆使用逻辑门限控制策略的并联混合动力汽车为例,分析并建立了以动力性能指标为约束的混合动力汽车参数优化的非线性规划模型,其目标函数包含最小油耗和最佳排放性能.针对遗传算法容易早熟等不足,采用带自适应交叉和变异算子的遗传算法和模拟退火技术相结合进行求解.仿真结果表明了所提出方法的有效性.     

Optimization of power management among an engine,battery and ultra-capacitor for a series HEV: A dynamic programming application

In a hybrid electric vehicle (HEV) system, it is an important issue on how to distribute the output power from multiple power generating components to operate a vehicle more efficiently. Many studies have been conducted on how to manage multiple power sources of a vehicle based on various optimization theories. In this study, an algorithm to calculate the optimization of a series HEV that has three power generating components, engine, battery and ultra-capacitor, is developed based on dynamic programming. Normally dynamic programming is applied to the optimization of power management and components sizing by estimating potential fuel economy for electrified vehicle such as HEV, Plug-in HEV or Fuelcell HEV. In contrast with most objective systems that have only two power generating components, the system in this study has three power sources. Since the system has three power sources, the number of state and control variables of optimization problem increases. Therefore the number of calculations increases unreasonably. To decrease the number and time of calculations, a new electric model that contains the both characteristics of battery and ultra-capacitor is developed with some assumptions. In comparison with the optimization algorithm which follows the theory of DP with no assumptions, the results from the newly developed algorithm has 1.04 % discrepancy in terms of fuel economy, even though the calculation time decreases to 4400 times less.     

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。     

混合动力系统的匹配设计与优化算法

混合动力电动汽车是解决当前能源短缺与环境污染问题的最切实有效的技术之一,它充分利用2种动力源之间的动力优化分配,提高整个混合动力系统的效率。文章介绍了混合动力系统的参数优化和应用的优化算法,得出通过采用合理优化算法对混合动力系统进行优化将极大地改善整车的动力性、经济性和排放性能,指出混合动力系统的匹配与优化是混合动力汽车研究和开发的重点,混合动力系统优化是一个值得深入研究的课题。     

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。     

Impedance-based and circuit-parameter-based battery models for HEV power systems

The relationship between voltage and current inside a battery, or the impedance, plays an important role in the simulation and design of hybrid electric vehicle (HEV) power systems. This paper proposes a new approach employing the Bode plot for evaluation of equivalent circuit parameters for a lithium polymer battery (LiPB) for HEV application. The main concept of the proposed circuit-parameter-based model approach is the application of a transfer function used to process the frequency response of the battery for calculation of accurate circuit parameters. Additionally, the Bode plot is also applied to derive the impedance-based model directly from frequency response measurements for short time simulations and practical use in the HEV. Two methods for battery modeling are proposed and verified experimentally with the voltage-current profile of a conventional HEV using the battery measured in this paper. The results show that the proposed circuit-parameter-based technique provides a satisfactory battery equivalent circuit model.     

Bees-algorithm-based optimization of component size and control strategy parameters for parallel hybrid electric vehicles

This paper presents the optimization of key component sizes and control strategy for parallel hybrid electric vehicles (parallel HEVs) using the bees algorithm (BA). The BA is an intelligent optimization tool that mimics the food foraging behavior of honey bees. Parallel HEV configuration and electric assist control strategy were used to conduct the research. The values of the key component size and the control strategy parameters were adjusted according to the BA to minimize the weighted sum of fuel consumption (FC) and emissions, while the vehicle performance satisfies the PNGV constraints. In this research, the software ADVISOR was used as the simulation tool, and the driving cycles FTP, ECE-EUDC and UDDS were employed to evaluate FC, emission and dynamic performance. The results demonstrate that the BA is a powerful tool in parallel HEV optimization to determine the optimal parameters of component sizes and control strategy, resulting in the improvement of FC and emissions without sacrificing vehicle performance. In addition, the BA is able to define a global solution with a high rate of convergence.     

混合动力电动汽车结构分析

混合动力电动汽车（HEV）是指以蓄电池与辅助动力单元（APU）共同作为动力源的汽车。由于混合动力电动汽车在节能和降低排放污染方面的明显优势，因而受到很大的重视，研制开发和产业化的进程相当快，目前混合动力电动汽车主要有两种混合驱动结构，串联式和并联式，对这两种混合动力系统结构和特点进行了分析，并重点对并联式结构中的不同结构进行了分析介绍。     

Vehicle dynamics control of an electric-all-wheel-drive hybrid electric vehicle using tyre force optimisation and allocation

ABSTRACT

Hybrid Electric Vehicles (HEV) offer improved fuel efficiency compared to conventional vehicles at the expense of adding complexity and at times, reduced total power. As a result, HEV generally lack the dynamic performance that customers enjoy. To address this issue, the paper presents a HEV with electric All-Wheel-Drive capabilities via the use of torque vectoring electric rear axle drive (TVeRAD) to power the rear axle. The addition of TVeRAD to a front wheel drive HEV improves the total power output. To improve the handling characteristics of the vehicle, the TVeRAD provides torque vectoring at the rear axle. A bond graph model of the drivetrain is developed and used in co-simulation with CarSim. The paper proposes a control system which utilises control allocation to optimise tyre forces. The proposed control system is tested in the simulation environment with a high fidelity CarSim vehicle model. Simulation results show the control system is able to maximise vehicle longitudinal performance while avoiding tyre saturation on low mu surfaces. More importantly, the control system is able to track the desired yaw moment request on a high speed double lane change manoeuvre through the use of the TVeRAD to improve the handling characteristic of the vehicle.     

混合动力电动汽车关键技术

混合动力电动汽车（HEV）的核心是混合动力驱动系统，HEV系统具有高度的复杂性，混合动力系统设计的关键是系统结构的选择，整车能量管理策略的开发和系统参数的确定。功率分别是系统能量管理策略研究的关键，随着研究的深入，自适应控制，模糊逻辑控制，神经元网络控制等方法也得到了有效的运用。文中对子系统的关键技术及整车试验方法一评价体系的建立等方面进行了讨论。