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设计了一种具有实时控制能力的增程式电动汽车混合型能量管理策略。首先建立了面向能量管理策略优化的增程式电动汽车整车模型。根据能量管理策略特点,将优化目标设置为增程器系统燃油消耗及动力电池当前SOC值与目标值之间差值的总和。再采用动态规划算法求解增程式电动汽车在给定行驶工况下的能量管理优化问题,从而获得了增程器开启时刻与输出功率优化结果。但由于动态规划算法需要已知详细的工况信息,很难应用于实车实时控制,而且从动态规划优化结果中不易提取控制规则,因此利用BP神经网络算法对优化结果进行离线训练,建立了增程器输出功率与车辆行驶状态参数间的非线性映射关系,得到了具有实时控制能力的神经网络控制模型。在采用BP神经网络训练时,根据车辆各个状态参数在CAN总线中的传输精度,对神经网络输入层、输出层参数的精度进行了修正。仿真结果表明:神经网络模型能够获得类似动态规划的最优控制效果,能够控制动力电池SOC在目标值的3%误差带以内。采用NEDC工况对混合型能量管理策略进行了硬件在环仿真试验,试验结果表明:与实车采用的电能消耗-电能维持型控制策略相比,所提出的混合型能量管理策略使汽车的燃油经济性提高了9.5%。 相似文献
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为提高插电式混合动力汽车燃油经济性,设计了一种基于动态规划和径向基函数(RBF)神经网络的插电式混合动力汽车能量管理策略。首先,建立了插电式混合汽车数学模型;其次,以发动机油耗最小为目标函数,采用动态规划求解全局最优的离线优化结果;最后,采用RBF神经网络对离线最优控制结果进行学习,建立了发动机输出转矩与车辆状态参数之间的非线性映射关系,得到了基于动态规划和RBF神经网络的能量管理策略。仿真结果表明,文章所提策略油耗较之于电量消耗-维持策略降低了2.92%,验证了该策略的有效性。 相似文献
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《汽车工程》2014,(8)
鉴于采用通常在特定工况下开发的控制策略的混合动力汽车在实际路况下的性能未必能达到最优的问题,将实际道路下的混合动力汽车能量管理策略问题转化为标准路况下的随机线性最优控制问题。建立了包含三效催化转化器热状态的混合动力汽车二次型状态空间方程,以发动机燃油消耗和三效催化转化器出口处的排放最小为优化目标,对蓄电池SOC、车速、三效催化转化器温度和出口排放等实际状态进行卡尔曼滤波估计,以对电机功率和发动机功率等输出变量进行最优反馈。仿真结果表明,与规则控制相比,所建立的随机最优控制策略能在满足车辆动力性要求的前提下,三效催化转化器的起燃时间约缩短160s,HC和CO的转化率明显提高。 相似文献
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针对THS-Ⅲ平台的插电式混合动力汽车提出一种基于深度强化学习的能量管理策略。首先,使用MATLAB/Simulink搭建车辆前向仿真模型;其次,建立车辆能量管理的马尔可夫过程和深度强化学习算法;最后,使用WLTC-Class3和ACC-60工况进行了仿真验证。结果表明,与基于规则的能量管理策略相比,基于深度强化学习的能量管理策略在WLTC-Class3工况下总花费节省16.51%,燃油消耗量下降15.56%,在ACC-60工况下总花费节省31.95%,燃油消耗量下降29.96%。 相似文献
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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(F WA)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... 相似文献
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Nadir Ouddah Lounis Adouane Rustem Abdrakhmanov 《International Journal of Automotive Technology》2018,19(3):571-584
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. 相似文献
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针对某新型双电机行星耦合插电式混合动力汽车(PHEV)中发动机在起停及怠速运行状态下会导致油耗增加的问题,基于等效燃油消耗最小能量管理策略,加入发动机起停优化控制模块,以进一步改善整车燃油经济性。建立了整车动力学和传动模型并加入发动机起停优化控制模块,对ECMS能量管理策略输出的发动机及电机最优目标转矩进行重新优化分配后,再输出给发动机及电机控制器以控制其工作状态。针对起停优化控制中影响起停频次的关键时间参数,采用粒子群优化算法对其进行优化。仿真结果表明,相比优化前,所提出的能量管理优化策略能够实现对发动机起停或怠速状态的有效控制,减少发动机的起停频次,减少恶化油耗,验证了本文所提出的能量管理优化策略能够进一步优化整车燃油经济性。 相似文献
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C. H. Zheng G. Q. Xu Y. I. Park W. S. Lim S. W. Cha 《International Journal of Automotive Technology》2014,15(1):117-123
Pontryagin’s Minimum Principle (PMP) and Dynamic Programming (DP) are both from the optimal control theory and can both achieve optimal trajectories when they are applied to power management strategies of hybrid vehicles. However they have totally different control concepts. In order to select the superior one, the PMP-based and the DP-based power management strategies are introduced and compared for a fuel cell hybrid vehicle (FCHV) in this paper. The two power management strategies are applied to the FCHV in a computer simulation environment, and the simulation results from the two strategies are compared when the control variable for the PMP is fuel cell system (FCS) net power and for the DP is battery power. As a result, the superiority of the PMP-based power management strategy is proved. 相似文献
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基于对混合动力汽车能量管理策略优化的目的,建立了丰田Prius Plug-in混合动力汽车的MATLAB/Simulink数学模型,用数学公式描述了系统优化控制问题,采用粒子群优化算法对该包含众多约束条件的非线性优化问题进行了求解,利用PSAT专业软件对比分析了基本型优化控制算法、改进型优化控制算法和规则控制算法等的控制效果及燃油经济性。结果表明,经过优化后的Plug-in混合动力汽车在不牺牲汽车各项性能的前提下能提高动力系统工作效率。 相似文献
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基于对混合动力汽车能量管理策略优化的目的,建立了丰田PnusPlug-in混合动力汽车的MATLAB/Simulink数学模型,用数学公式描述了系统优化控制问题,采用粒子群优化算法对该包含众多约束条件的非线性优化问题进行了求解,利用PSAT专业软件对比分析了基本型优化控制算法、改进型优化控制算法和规则控制算法等的控制效果及燃油经济性。结果表明,经过优化后的Plug-in混合动力汽车在不牺牲汽车各项性能的前提下能提高动力系统工作效率。 相似文献
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In this paper, a new methodology is presented for computing time-optimal obstacle avoidance maneuvers for ground vehicles. Usually, the problem of obstacle avoidance is addressed in two parts. In the first part a path is planned. In the second an appropriately designed vehicle controller tracks the desired path. In view of the fact that the main problem concerning emergency maneuvers remains the development of an optimal control for minimum time and maximum maneuverability — with respect to the slip risk due to saturation of the tire forces — the authors propose an alternative approach. Considering that the time optimal control according to Pontryagin’s Maximum Principle (PMP) is of bang-bang type the investigations concern the minimum order and magnitude bang-bang control for “feedforward” steering maneuvers with the target of minimizing the computation time and simplifying the algorithm. This is accomplished by keeping the basic PMP logic but transforming the computational algorithm from an exact to a least squares control problem. Furthermore, the paper addresses how to solve the problem of guiding the vehicle from a non rest to a rest position. Simulations of obstacle avoidance maneuvers illustrate the performance of the controller. 相似文献