混合动力汽车能量控制策略

针对串联、并联和混联3种类型的混合动力汽车驱动系统的不同结构特点,文章对3种类型混合动力汽车的能量控制策略分别进行了详细阐述,指出了未来混合动力汽车能量控制策略研究的发展方向。能量控制策略不仅要实现整车最佳的燃油经济性,而且还要兼顾发动机排放、蓄电池寿命及驾驶性能等多方面要求,并针对混合动力汽车各部件的特性和汽车的运行工况,使发动机、电动机、蓄电池和传动系统实现最佳匹配,兼顾上述各方面要求的优化控制策略的研究应是今后的研究重点。     

混合动力汽车控制策略的优化

混合动力汽车既采用了发动机控制系统,同时采用了电动机控制系统,由此组成混合控制系统驱动车辆行驶。控制策略是混合动力汽车的核心,混合动力汽车有两个能量源,两者之间相互协调的程度对混合动力汽车燃油经济性和动力性等性能的改善具有关键作用,两者之间只有协调工作,才能很好的达到节能减排的目的,而这需要良好的控制策略来实现。因此,为了提高能源利用率,减少环境污染,需要对混合汽车的控制策略进行优化分析。然而,目前国内混合动力汽车的控制策略不够完善,本文对混合动力汽车的结构原理和控制优化问题进行了研究。     

浅析混合动力汽车控制策略

混合动力汽车驱动系统有串联、并联和混联三种布置形式,本文简要陈述了三种类型混合动力汽车的结构,针对三种动力系统的能量控制,阐述了各自的主要控制策略以及各控制策略的特点与优势,并指出了近来混合动力汽车能量控制策略研究的发展趋势。     

并联式混合动力电动汽车动力总成控制策略的研究

在混合动力电动汽车中,制定合适的控制策略和控制逻辑是优化能量流动、提高动力总成协调程度的核心,是并联式混合动力汽车具有优良的经济性与排放性能的保证。本文综合分析了并联式混合动力汽车动力总成控制的几种典型控制策略,介绍了基本思想、实现方法以及各自特点,并对各种控制策略的控制效果进行了评价和分析。     

混合动力汽车能量控制策略研究现状

随着环境污染问题的日益凸显和石油资源的逐渐匮乏,混合动力汽车研究的意义和价值也得到了广泛认可。混合动力汽车由两种或两种以上的能源提供动力,具有纯电动汽车高效率低排放的优点,又能够显著增加电动汽车的行驶里程,具有传统燃料车高比能量、高比功率的长处,又可获得传统车无法达到的优化控制目标。如何对多能量源与其他部件协调配合,进行优化组合,以减少燃油消耗、降低排放,是混合动力汽车研究中面临的一个关键问题。文章重点阐述了混合动力汽车能量控制策略的三种分类方式,并对几种常见能量控制策略进行介绍和比较,得出这些算法的优缺点及适用场合。     

混合动力汽车控制策略优化研究综述

目前在混合动力汽车上普遍采用的是简单可行的逻辑门控制策略,由于该控制策略主要依靠经验而无法保证整车性能最优,为此很多研究人员开展了对混合动力汽车控制策略的优化研究。该文阐述了混合动力汽车控制策略参数优化及整车动力系统部件效率优化的相关研究成果,并指出了其研究方向。     

燃料电池汽车能量管理控制策略研究

针对燃料电池混合动力汽车(FCHEV)能量管理策略进行了研究,对燃料电池汽车的能量管理控制策略进行了梳理和分类。从基于规则和基于优化这两个角度将控制策略进行了横向分类,再将规则型和优化型控制策略做了纵向梳理。具体介绍了模糊控制、神经网络、动态规划、庞特里亚金极值原理与等效消耗最小原理等的具体应用。分析比较了不同优化算法的优劣势,并对之后控制策略的研究方向提出了建议。     

混合动力汽车能效优化与控制策略研究

随着环境问题和能源危机的日益严重,混合动力汽车作为一种节能环保的交通工具,得到了广泛关注。能效优化和控制策略是混合动力汽车研究的重要方向,对于提高汽车性能、降低能耗、减少排放具有重要意义。本文旨在探讨混合动力汽车的能效优化和控制策略,以提高汽车的整体性能和燃油经济性。     

并联混合动力汽车控制策略的综合分析

混合动力汽车解决了纯电动汽车续驶里程短和初始成本高的难题。文章简要介绍了混合动力汽车的驱动系统和工作模式及能量流动。将目前已提出的基于转矩或功率的并联混合动力汽车控制策略进行了分类,并介绍了其主要思想及优缺点,指明了控制策略的发展方向。     

基于行驶路况的混合动力汽车能量管理分析（英文）

混合动力汽车的能量管理是实现节能减排的关键技术之一,随着智能网联技术的发展,基于路况预测的能量管理及控制策略已受到了广泛关注。阐述了4种车辆行驶路况的获取方式,通过对路况特征参数进行选取和数据处理,实现了对未来行驶路况的识别和预测。基于行驶路况信息,对混合动力汽车不同的控制策略进行了分析,包括电能消耗和能量分配控制策略,并阐述了基于局部工况和全局工况的预测能量管理方法。通过对混合动力能量管理和控制策略的分析,为相关工程开发人员提供借鉴和参考。     

Plug-in HEV with CVT: configuration,control, and its concurrent multi-objective optimization by evolutionary algorithm

Plug-in Hybrid Electric Vehicle (Plug-in HEV) has dramatic improvements in fuel economy and emission reduction. It is most important to decide its optimal configuration, energy management strategy, powertrain sizes, and control logic parameters. For multi-objective optimization, we present a concurrent optimization methodology based on an optimal Plug-in HEV powertrain configuration with continuous variable transmission (CVT). The novelty is using evolutionary algorithm in conjunction with an instantaneous optimal energy management strategy. Simulation results indicate the proposed method can significantly reduce fuel consumption and emissions by simultaneously optimizing the propulsion system parameters as well as the energy control parameters.     

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。     

Advanced hybrid energy storage system for mild hybrid electric vehicles

Hybrid electric vehicles (HEV) utilize electric power and a mechanical engine for propulsion; therefore, the performance of HEVs is directly influenced by the characteristics of the energy storage system (ESS). The ESS for an HEV generally requires high power performance, long cycle life, reliability and cost effectiveness; thus, a hybrid energy storage system (HESS) that combines different types of storage devices has been considered to fulfill both performance and cost requirements. To improve the operating efficiency and cycle life of a HESS, an advanced dynamic control regime in which pertinent storage devices in the HESS can be selectively operated based on their status is presented. Verification tests were performed to confirm the degree of improvement in energy efficiency. In this paper, an advanced HESS with a battery management system (BMS) that includes an optimal switching control function based on the estimated state of charge (SOC) is presented and verified.     

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.     

轻度混合控制策略下混合动力电动汽车能量优化与仿真

为了优化轻度混合控制策略下的CFA6470混合动力电动汽车能量总成控制系统,设计了能量总成控制器,并将其分成5个模块;分析了节气门开启角与车辆行驶挡位的优化方法,轻度混合时的能量分配策略;提出了基于能量守恒原理的电池组荷电状态估计方法,并根据ECE-EUDC工况,在2种不同的期望车速下对设计的控制系统进行了仿真。仿真结果表明:在发动机的期望工况下,所设计的能量总成控制系统能够实现能量在发动机、驱动电机以及电池组之间的合理分配,电池组的荷电状态变化规律与车辆行驶状态相符合。     

基于捕食搜索策略的混合动力汽车参数优化

混合动力汽车模型是一个较复杂的非线性系统,且设计参数较多,为一种处理燃油经济性和排放的多目标问题。文章以一辆实例样车的动力系统和逻辑门限值控制策略为例,分析并建立了以动力性能为控制约束,以最小化油耗和排放为控制目标的非线性规划模型。采用捕食搜索遗传算法,对模型进行了仿真。结果表明,该方法相对于简单遗传算法更能有效地改善车辆燃油经济性和排放。     

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).     

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。     

混合动力电动汽车制动系统回馈特性仿真

为了研究混合动力电动汽车(HEV)回馈制动特性,建立了用于城市公交的混合动力电动汽车复合制动系统的仿真模型,提出了回馈制动控制策略,分析了复合制动系统的工作过程,并探讨影响电动汽车制动系统可靠、安全和高效的主要因素,研究电动汽车复合制动系统优化途径。研究结果表明:回馈制动最低车速限值越小,制动能量回收率越大;从回收电动汽车能量角度分析,回馈制动比例应有一个有效范围值;在各种循环工况下,具有回馈制动功能时混合动力电动汽车城市客车单位里程的能量消耗可降低10%~25%。