基于最优功率分配因子的插电式混合动力汽车实时能量管理策略研究
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摘要
插电式混合动力汽车兼顾传统混合动力汽车和纯电动汽车的优点,即具有较长的续驶里程又具有较好的燃油经济性,插电式混合动力汽车的实时能量管理策略是发挥节能潜力的关键技术。为解决具有手动行驶模式选择功能的P2构型插电式混合动力汽车的能量管理实时优化问题,定义发动机和电机功率分配因子,在任何SOC下从电量消耗模式切换到电量维持模式时,提出通过功率分配因子动态调整发动机最优工作曲线获得最佳的燃油经济性的实时能量管理策略。建立功率分配因子全局优化模型,利用自适应模拟退火算法离线优化功率分配因子,研究功率分配因子和SOC对整车燃油经济性的影响规律,得到在不同SOC的最优功率分配因子控制线。从而建立基于最优功率分配因子控制线的插电式混合动力汽车实时控制能量管理策略。在多个循环工况下对比仿真分析不同SOC下的燃油经济性,结果表明基于最优功率分配因子的能量管理策略使得燃油经济性改善幅度最大可达16.99%。
Plug-in hybrid electric vehicle(PHEV) has the advantages both of traditional hybrid electric vehicle(HEV) and electric vehicle(EV), which not only has long driving distance but only has good fuel economy. Energy management strategy is the key technology for achieving fuel-saving potential. In order to solve the real-time optimization problem of energy management of plug-in hybrid electric vehicle. A PHEV with driving modes manual selection function is regarded as researching object and power allocation factor(PAF) is proposed. When PHEV switches modes from charge-depleting(CD) to charge-sustaining(CS) at any point of SOC,PAF plays a role to adjust the engine best working line dynamically to get a better fuel economy. A global optimization model for PAF is built and adaptive simulated annealing(ASA) algorithm is used to get the optimal PAF offline. The effect of PAF and SOC to fuel economy is observed and the optimal PAF line for real time control is obtained. Then optimal PAF based real time control energy management strategy is proposed and simulation experiment is carried out over two driving cycles. The results indicate that fuel economy of PHEV has an improvement about 16.99 % by PAF-based control strategy.
Plug-in hybrid electric vehicle(PHEV) has the advantages both of traditional hybrid electric vehicle(HEV) and electric vehicle(EV), which not only has long driving distance but only has good fuel economy. Energy management strategy is the key technology for achieving fuel-saving potential. In order to solve the real-time optimization problem of energy management of plug-in hybrid electric vehicle. A PHEV with driving modes manual selection function is regarded as researching object and power allocation factor(PAF) is proposed. When PHEV switches modes from charge-depleting(CD) to charge-sustaining(CS) at any point of SOC,PAF plays a role to adjust the engine best working line dynamically to get a better fuel economy. A global optimization model for PAF is built and adaptive simulated annealing(ASA) algorithm is used to get the optimal PAF offline. The effect of PAF and SOC to fuel economy is observed and the optimal PAF line for real time control is obtained. Then optimal PAF based real time control energy management strategy is proposed and simulation experiment is carried out over two driving cycles. The results indicate that fuel economy of PHEV has an improvement about 16.99 % by PAF-based control strategy.
引文
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[2]韩立金,刘辉,王伟达,等.功率分流混合动力汽车参数匹配与优化研究[J].汽车工程,2014,36(8):904-910.HAN Lijin,LIU Hui,WANG Weida,et al.A study on the parameter matching and optimization of a power split HEV[J].Automotive Engineering,2014,36(8):904-910.
[3]王伟达,项昌乐,韩立金,等.基于电池SOC保持的混联式混合动力车辆能量管理策略的研究[J].汽车工程,2011,33(5):373-377.WANG Weida,XIANG Changle,HAN Lijin,et al.Aresearch on SOC retaining-based energy management strategy for PSHEV[J].Automotive Engineering,2011,33(5):373-377.
[4]张东好,韩立金,项昌乐,等.机电复合传动最优功率分配策略研究[J].汽车工程,2014,36(11):1392-1404.ZHANG Donghao,HAN Lijin,XIANG Changle,et al.A research on the optimal power distribution strategy for electro-mechanical drive[J].Automotive Engineering,2014,36(11):1392-1404.
[5]HOU Cong,XUA Liangfei,WANG Hewu,et al.Energy management of plug-in hybrid electric vehicles with unknown trip length[J].Journal of the Franklin Institute,2015,352(2):500-518.
[6]CHEN B,WU Y,TSAI H.Design and analysis of power management strategy for range extended electric vehicle using dynamic programming[J].Applied Energy,2014,113(1):1764-1774.
[7]CHEN Zheng,MI C,XIONG Rui,et al.Energy management of a power-split plug-in hybrid electric vehicle based on genetic algorithm and quadratic programming[J].Journal of Power Sources,2014,248(7):416-426.
[8]王伟达,杨新征,张为,等.基于动态单纯形算法的车辆状态最优观测器[J].中国公路学报,2015,28(6):112-119.WANG Weida,YANG Xinzheng,ZHANG Wei,et al.Dynamic simplex algorithm-based optimal observer for vehicle state[J].Chinese Journal of Highway and Transport,2015,28(6):112-119.
[9]SUN Hui.Multi-objective optimization for hydraulic hybrid vehicle based on adaptive simulated annealing genetic algorithm[J].Engineering Applications of Artificial Intelligence,2010,23(1):27-33.
[10]SIGIT Y M,AGUNG K.Optimization and simulation of plastic injection process using genetic algorithm and moldflow[J].Chinese Journal of Mechanical Engineering,2017,30(2):398-406.
[11]LI Liang,ZHANG Yahui,YANG Chao,et al.Hybrid genetic algorithm-based optimization of powertrain and control parameters of plug-in hybrid electric bus[J].Journal of the Franklin Institute,2015,352(3):776-801.
[12]CHEN Zheng,MI C,XU Jun,et al.Energy management for a power-split plug-in hybrid electric vehicle based on dynamic programming and neural networks[J].IEEETransactions on Vehicular Technology,2014,63(4):1567-1580.
[13]BORHAN H,VAHIDI A,PHILLIPS A,et al.MPC-based energy management of a power-split hybrid electric vehicle[J].IEEE Transactions on Control Systems Technology,2012,20(3):593-603.
[14]MA Biao,LIU Yahui,GAO Yefeng,et al.Estimation of vehicle sideslip angle based on steering torque[J].International Journal of Advanced Manufacturing Technology,2018,94(9-12):3229-3237.
[15]ZOU Yuan,LIU Teng,SUN Fengchun,et al.Comparative study of dynamic programming and Pontryagin’s minimum principle on energy management for a parallel hybrid electric vehicle[J].Energies,2013,6(4):2305-2318.
[16]EBBESEN S,ELBERT P,GUZZELLA L.Battery state-of-health perceptive energy management for hybrid electric vehicles[J].IEEE Transactions on Vehicular Technology,2012,61(7):2893-2900.
[17]GENG Bo,MILLS J,SUN Dong.Energy management control of micro turbine-powered plug-in hybrid electric vehicles using the telemetry equivalent consumption minimization strategy[J].IEEE Transactions on Vehicular Technology,2011,60(9):4238-4248.
[18]HE Hongwen,XIONG Rui,ZHAO Kai,et al.Energy management strategy research on a hybrid power system by hardware-in-loop experiments[J].Applied Energy,2013,112(16):1311-1317.
[19]王钦普,杜思宇,李亮,等.基于粒子群算法的插电式混合动力客车实时策略[J].机械工程学报,2017,53(4):77-84.WANG Qinpu,DU Siyu,LI Liang,et al.Real-time energy management strategy for plug-in hybrid electric bus on particle swarm optimization algorithm[J].Journal of Mechanical Engineering,2017,53(4):77-84.
[20]黄硕,李亮,杨超,等.基于规则修正的同轴并联混合动力客车瞬时优化能量分配策略[J].机械工程学报,2014,50(20):113-121.HUANG Shuo,LI Liang,YANG Chao,et al.Rule correction-based instantaneous optimal energy management strategy for single-shaft parallel hybrid electric bus[J].Journal of Mechanical Engineering,2014,50(20):113-121.
[21]杨超,焦晓红,李亮,等.面向公交客车应用的插电式混合动力实时优化策略研究[J].机械工程学报,2015,51(22):111-119.YANG Chao,JIAO Xiaohong,LI Liang,et al.Research on city-bus application-oriented real-time optimal energy management strategy for plug-in hybrid electric bus[J].Journal of Mechanical Engineering,2015,51(22):111-119.
[22]林歆悠,冯其高,张少博.等效因子离散全局优化的等效燃油瞬时消耗最小策略能量管理策略[J].机械工程学报,2016,52(20):102-110.LIN Xinyou,FENG Qigao,ZHANG Shaobo.Global optimal discrete equivalent factor of equivalent fuel consumption minimization strategy based energy management strategy for a series-parallel plug-in hybrid electric vehicle[J].Journal of Mechanical Engineering,2016,52(20):102-110.
[23]SUN Yong,MA Zilin,TANG Gongyou,et al.Estimation method of state-of-charge for lithium-ion battery used in hybrid electric vehicles based on variable structure extended kalman filter[J].Chinese Journal of Mechanical Engineering,2016,29(4):717-726.
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[26]INGBER L.Adaptive simulated annealing(ASA):Lessons learned[J].Control&Cybernetics,2000,25(1):33-54.