PHEV发动机驱动工况效率耦合分析与优化控制
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摘要
单轴并联式混合动力系统(Parallel Hybrid Electric Vehicle, PHEV)包括电池、驱动电机、发动机、自动变速器等多个关键部件。各部件效率特性存在相互耦合的关系,要实现系统整体效率最优,需要辨明影响系统效率的控制参数,并对系统整体效率最优的控制参数进行优化。以装备无级变速器(Continuously Variable Transmission, CVT)的PHEV为研究对象,首先对系统各关键部件的效率特性进行分析,建立各关键部件效率模型,明确各部件效率与控制参数、状态参数之间的关系。在此基础上,对发动机单独驱动模式下动力传递路径中不同部件的效率耦合关系进行分析,推导出系统燃油消耗量与动力系统各状态参数、控制参数之间的函数关系。根据分析结果,选取车辆需求功率及车速为状态参数,变速器速比及发动机转矩为控制参数,以系统燃油消耗量最小为目标建立优化目标函数和约束条件,对系统优化问题进行定义。根据优化问题的特点,设计基于模拟退火的优化算法对优化问题进行求解,获取系统燃油消耗率最小时变速器目标速比和发动机目标转矩随状态参数的变化关系。建立系统仿真模型对所述优化算法进行仿真分析,并搭建混合动力试验台对优化结果进行试验验证。结果表明:无级变速器效率对系统整体效率影响较大,采用优化控制规律使发动机效率有所降低,但无级变速器效率升高更大,系统整体效率升高;在功率需求一定的循环工况下,优化控制算法比传统上仅以发动机效率最高为目标的控制算法节油1%～2%。
Powertrain of parallel hybrid electric vehicle(PHEV) is composed of a battery, a drive motor, an engine, an automatic transmission, and several other key components. The efficiency characteristics of these components are coupled with each other. To achieve optimal overall efficiency of the system, the coupling relationships between the efficiency of different components need to be analyzed. The control parameters that determine the overall efficiency under different working modes need to be identified and should be optimized to achieve maximum system efficiency. In this paper, PHEV equipped with continuously variable transmission is studied. First, the efficiency characteristics of key components in the system were analyzed; efficiency models of these key components were established; and relationships between efficiency, control parameters, and state parameters were revealed. Furthermore, the coupling relationships between the efficiency of different components in the power transfer path were analyzed under the engine-only mode. The relationships between fuel consumption, state parameters, and control parameters of the system were deduced. According to the analysis results, power requirement and vehicle speed were selected as state parameters; and CVT ratio and engine torque were selected as control parameters. An objective function and constraints were established to achieve minimize fuel consumption, and the system optimization issues were defined. According to the characteristics of the optimal equation, an algorithm based on simulated annealing was proposed to solve the optimization equation. The relationships between CVT ratio, engine torque, and state parameters of the system were obtained to achieve minimum fuel consumption. Simulations and tests were carried out under a standard driving cycle and fixed speeds. Results indicate that the efficiency of CVT has a great influence on the overall efficiency of the system. The engine efficiency is reduced by using the optimal control law, but the efficiency of CVT increased more and the overall efficiency of the system is increased. Under driving cycle where the power requirement is fixed, fuel consumption under the proposed control algorithm reduced by about 1%-2% compared with the traditional control algorithm, which only consider reaching the highest engine efficiency.
Powertrain of parallel hybrid electric vehicle(PHEV) is composed of a battery, a drive motor, an engine, an automatic transmission, and several other key components. The efficiency characteristics of these components are coupled with each other. To achieve optimal overall efficiency of the system, the coupling relationships between the efficiency of different components need to be analyzed. The control parameters that determine the overall efficiency under different working modes need to be identified and should be optimized to achieve maximum system efficiency. In this paper, PHEV equipped with continuously variable transmission is studied. First, the efficiency characteristics of key components in the system were analyzed; efficiency models of these key components were established; and relationships between efficiency, control parameters, and state parameters were revealed. Furthermore, the coupling relationships between the efficiency of different components in the power transfer path were analyzed under the engine-only mode. The relationships between fuel consumption, state parameters, and control parameters of the system were deduced. According to the analysis results, power requirement and vehicle speed were selected as state parameters; and CVT ratio and engine torque were selected as control parameters. An objective function and constraints were established to achieve minimize fuel consumption, and the system optimization issues were defined. According to the characteristics of the optimal equation, an algorithm based on simulated annealing was proposed to solve the optimization equation. The relationships between CVT ratio, engine torque, and state parameters of the system were obtained to achieve minimum fuel consumption. Simulations and tests were carried out under a standard driving cycle and fixed speeds. Results indicate that the efficiency of CVT has a great influence on the overall efficiency of the system. The engine efficiency is reduced by using the optimal control law, but the efficiency of CVT increased more and the overall efficiency of the system is increased. Under driving cycle where the power requirement is fixed, fuel consumption under the proposed control algorithm reduced by about 1%-2% compared with the traditional control algorithm, which only consider reaching the highest engine efficiency.
引文
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[13]张昕,王松涛,张欣,等.基于马尔可夫链的混合动力汽车行驶工况预测研究[J].汽车工程,2014,36(10):1217-1236.ZHANG Xin,WANG Song-tao,ZHANG Xin,et al.A Research on Driving Condition Prediction for HEVs Based on Markov Chain[J].Automotive Engineering,2014,36(10):1217-1236.
[14]龙海威.基于效率优化的AMT中度混合动力汽车能量管理策略研究[D].重庆:重庆大学,2012.LONG Hai-wei.Study on Energy Management Strategy for AMT Medium Hybrid Electric Vehicle based on Efficiency Optimized[D].Chongqing:Chongqing University,2012.
[15]彭志远,秦大同,段志辉,等.基于系统效率最优的新型混合动力汽车控制策略[J].沈阳工业大学学报,2012,34(4):412-419.PENG Zhi-yuan,QIN Da-tong,DUAN Zhi-hui,et al.Control Strategy for Novel Hybrid Electric Vehicle Based on System Efficiency Optimization[J].Journal of Shenyang University of Technology,2012,34(4):412-419.
[16]秦大同,胡明辉,杨亚联,等.CVT轻度混合动力系统电动机和发动机联合工作模式下的系统效率优化[J].机械工程学报,2008,44(9):148-153.QIN Da-tong,HU Ming-hui,YANG Ya-lian,et al.Optimization and Analysis of System Efficiency for the Mild Hybrid Electric Vehicle Under the Cruise Conditions[J].Chinese Journal of Mechanical Engineering,2008,44(9):148-153.
[17]杨阳,秦大同,胡明辉,等.基于效率优化的混合动力再生制动控制策略[J].中国机械工程,2009,20(11):1376-1380.YANG Yang,QIN Da-tong,HU Ming-hui,et al.Investigation of Control Strategy for Regenerative Braking of HEV Based on Efficiency Optimization[J].China Mechanical Engineering,2009,20(11):1376-1380.
[18]伏开飞.装有CVT的PHEV关键参数匹配与能量管理研究[D].重庆:重庆大学,2015.FU Kai-fei.Research on Key Parameters Matching and Energy Management of PHEV with CVT[D].Chongqing:Chongqing University,2015.
[19]梁金广,洪韬汶,宋传学.混合动力车用汽油机效率模型研究[J].农业机械学报,2012,43(9):1-10.LIANG Jin-guang,HONG Tao-wen,SONG Chuanxue.Efficiency Model of Gasoline Engine Used by Hybrid Electrical Vehicle[J].Transactions of the Chinese Society of Agricultural Machinery,2012,43(9):1-10.
[20]徐俊.无级自动变速器能耗损失预测方法研究[D].长春:吉林大学,2016.XU Jun.Research on Energy Loss Prediction Method of Continuously Variable Transmission[D].Changchun:Jilin University,2016.
[2]HAMMAR A.Prospects on Diffusion of Agriculture Hybrid Tractors Equipped with on Board High Voltage System[J].SAE Papers 2015-01-2827.
[3]陈雪平,张海亮,钟再敏,等.插电式混合动力汽车能耗及其影响因素分析[J].同济大学学报:自然科学版,2016,44(11):1749-1754.CHEN Xue-ping,ZHANG Hai-liang,ZHONG Zaimin,et al.Simulation and User Factors Analysis of Energy Consumption of Plug-in Hybrid Electric Vehicles[J].Journal of Tongji University:Nature Science,2016,44(11):1749-1754.
[4]王磊.增程式电动车参数匹配与综合控制研究[D].重庆:重庆大学,2014.WANG Lei.The Parameters Matching and Control Strategy Study of EREV[D].Chongqing:Chongqing University,2014.
[5]OLIVEIRA A M,BERTOTI E,ECKERT J J,et al.Evaluation of Energy Recovery Potential Through Regenerative Braking for a Hybrid Electric Vehicle in a Real Urban Drive Scenario[J].SAE Papers 2016-36-0348.
[6]MARQUEZ E D,NELSON D.Control Strategy Development for Parallel Plug-in Hybrid Electric Vehicle Using Fuzzy Control Logic[J].SAE Papers 2016-01-2222.
[7]詹森,秦大同,曾育平.基于遗传优化K均值聚类算法工况识别的混合动力汽车能量管理策略[J].中国公路学报,2016,29(4):130-152.ZHAN Sen,QIN Da-tong,ZENG Yu-ping.Energy Management Strategy of HEV Based on Driving Cycle Recognition Using Genetic Optimized Kmeans Clustering Algorithm[J].China Journal of Highway and Transport,2016,29(4):130-152.
[8]BAUL P,TAMARO C,WARPE H,et al.EcoRouting for Performance Plug-in Hybrid Electric Vehicles[J].SAE Papers 2016-01-2219.
[9]ZHANG Q,JU F,ZHANG S,et al.Power Management for Hybrid Energy Storage System of Electric Vehicles Considering Inaccurate Terrain Information[J].IEEE Transactions on Automation Science and Engineering,2017,14(2):608-618.
[10]YU V F,REDI A A N P,HIDAYAT Y A,et al.ASimulated Annealing Heuristic for the Hybrid Vehicle Routing Problem[J].Applied Soft Computing Journal,2017,53(1):119-132.
[11]欧阳,周舟,唐国强,等.自适应路况的插电式混合动力汽车能量管理策略[J].中国公路学报,2016,29(9):152-158.OU Yang,ZHOU Zhou,TANG Guo-qiang,et al.Control Strategy for Plug-in Hybrid Electric Vehicle Based on Self-adaptive Road Condition[J].China Journal of Highway and Transport,2016,29(9):152-158.
[12]SHEN D L,BENSCH V,MUELLER S.Model Predictive Energy Management for a Range Extender Hybrid Vehicle Using Map Information[J].IFAC-Papers On Line,2016,28(15):263-270.
[13]张昕,王松涛,张欣,等.基于马尔可夫链的混合动力汽车行驶工况预测研究[J].汽车工程,2014,36(10):1217-1236.ZHANG Xin,WANG Song-tao,ZHANG Xin,et al.A Research on Driving Condition Prediction for HEVs Based on Markov Chain[J].Automotive Engineering,2014,36(10):1217-1236.
[14]龙海威.基于效率优化的AMT中度混合动力汽车能量管理策略研究[D].重庆:重庆大学,2012.LONG Hai-wei.Study on Energy Management Strategy for AMT Medium Hybrid Electric Vehicle based on Efficiency Optimized[D].Chongqing:Chongqing University,2012.
[15]彭志远,秦大同,段志辉,等.基于系统效率最优的新型混合动力汽车控制策略[J].沈阳工业大学学报,2012,34(4):412-419.PENG Zhi-yuan,QIN Da-tong,DUAN Zhi-hui,et al.Control Strategy for Novel Hybrid Electric Vehicle Based on System Efficiency Optimization[J].Journal of Shenyang University of Technology,2012,34(4):412-419.
[16]秦大同,胡明辉,杨亚联,等.CVT轻度混合动力系统电动机和发动机联合工作模式下的系统效率优化[J].机械工程学报,2008,44(9):148-153.QIN Da-tong,HU Ming-hui,YANG Ya-lian,et al.Optimization and Analysis of System Efficiency for the Mild Hybrid Electric Vehicle Under the Cruise Conditions[J].Chinese Journal of Mechanical Engineering,2008,44(9):148-153.
[17]杨阳,秦大同,胡明辉,等.基于效率优化的混合动力再生制动控制策略[J].中国机械工程,2009,20(11):1376-1380.YANG Yang,QIN Da-tong,HU Ming-hui,et al.Investigation of Control Strategy for Regenerative Braking of HEV Based on Efficiency Optimization[J].China Mechanical Engineering,2009,20(11):1376-1380.
[18]伏开飞.装有CVT的PHEV关键参数匹配与能量管理研究[D].重庆:重庆大学,2015.FU Kai-fei.Research on Key Parameters Matching and Energy Management of PHEV with CVT[D].Chongqing:Chongqing University,2015.
[19]梁金广,洪韬汶,宋传学.混合动力车用汽油机效率模型研究[J].农业机械学报,2012,43(9):1-10.LIANG Jin-guang,HONG Tao-wen,SONG Chuanxue.Efficiency Model of Gasoline Engine Used by Hybrid Electrical Vehicle[J].Transactions of the Chinese Society of Agricultural Machinery,2012,43(9):1-10.
[20]徐俊.无级自动变速器能耗损失预测方法研究[D].长春:吉林大学,2016.XU Jun.Research on Energy Loss Prediction Method of Continuously Variable Transmission[D].Changchun:Jilin University,2016.