电动车动力蓄电池实验建模研究
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摘要
动力蓄电池是电动车的薄弱环节，也是目前电动车产业化的主要障碍。蓄电池管理系统(BMS)技术电动车的关键技术之一。由于不同种类的蓄电池的性能存在很大差异，而同一类型的蓄电池的不同个体也存在相当大的个体差异，这些差异对蓄电池组的性能和电动车的整体性能都有重大影响。
本论文介绍用实验建模方法研究电动车动力蓄电池的放电性能，它是北京市科委下达的科技项目“基于现场总线的实用型电动车能量管理系统”(合同编号：9550421000)的基础研究部分。论文首先论述了试验信号的采集和处理，介绍了静态和动态实验数据采集系统构成。由于使用了国外新近推出的基于现场总线技术的蓄电池智能化专用芯片，使得蓄电池的在线检测系统的结构简单，而性价比高。
论文的重点在动力蓄电池放电性能的实验建模研究，它分为静态模型和动态模型两部分。前者包含电压—安时模型和充放电电量平衡模型的研究；后者是基于系统辨识的实验建模方法，研究动力蓄电池模型和放电条件(放电强度、间歇程度和环境温度)对数学模型诸参数的影响。本论文通过上百次的放电试验测试，通过实验建模方法对比研究了四种电动车动力蓄电池(铅酸蓄电池、胶体铅酸蓄电池、镍氢蓄电池和锂离子蓄电池)的性能，并得出了一些有意义的结果。
论文最后扼要介绍了蓄电池实验建模研究在BMS设计和剩余电量估计SOC(State Of Charge)等方面的应用。
As the feeble section of electric vehicle, power battery was the main obstacle of the industrialization of electric vehicle. Designing a sound battery management system was one of the key technologies of electric vehicles. It was known that the performance difference among different kinds of batteries and considerable individual difference among the same kind of battery had great influence on the performance of battery team and the whole capability of electric vehicle.
Firstly, how to study the performance of battery discharging by experiment modeling was introduced. Experiment modeling was the fundamental research of the project appointed by Beijing science and technology committee (the project name is practical energy management system based on field bus for electric vehicles, contract No. 9550421000). Secondly, how to collect and deal with experiment signal was discussed. The configurations of system including static data collecting system and dynamic data collecting system were discussed next. By using the newly issued chip abroad applied in monitoring battery, the system had a simple configuration and sound ratio between performance and price.
The study of experiment modeling about the discharging performance of power battery was emphasized. Experiment modeling was divided into static experiment modeling and dynamic experiment modeling. The static experiment model including voltage & ampere-time model and the model of the equilibrium of battery capacity when the battery was charged and discharged was discussed in detail. The latter was focused on how the discharging conditions including discharging intensity, intermission time and environmental temperature influenced the parameters of the
math model. Through the method of experiment modeling, the performances of the four kinds of power batteries (Valve regulated lead-acid battery, Colloid Lead-Acid battery, MH-Ni battery and Lithium-ion battery) were compared. With hundreds of discharging tests, some significant results were gained.
In addition, the application of experimental modeling of battery in designing BMS and estimating SOC was demonstrated briefly.
本论文介绍用实验建模方法研究电动车动力蓄电池的放电性能，它是北京市科委下达的科技项目“基于现场总线的实用型电动车能量管理系统”(合同编号：9550421000)的基础研究部分。论文首先论述了试验信号的采集和处理，介绍了静态和动态实验数据采集系统构成。由于使用了国外新近推出的基于现场总线技术的蓄电池智能化专用芯片，使得蓄电池的在线检测系统的结构简单，而性价比高。
论文的重点在动力蓄电池放电性能的实验建模研究，它分为静态模型和动态模型两部分。前者包含电压—安时模型和充放电电量平衡模型的研究；后者是基于系统辨识的实验建模方法，研究动力蓄电池模型和放电条件(放电强度、间歇程度和环境温度)对数学模型诸参数的影响。本论文通过上百次的放电试验测试，通过实验建模方法对比研究了四种电动车动力蓄电池(铅酸蓄电池、胶体铅酸蓄电池、镍氢蓄电池和锂离子蓄电池)的性能，并得出了一些有意义的结果。
论文最后扼要介绍了蓄电池实验建模研究在BMS设计和剩余电量估计SOC(State Of Charge)等方面的应用。
As the feeble section of electric vehicle, power battery was the main obstacle of the industrialization of electric vehicle. Designing a sound battery management system was one of the key technologies of electric vehicles. It was known that the performance difference among different kinds of batteries and considerable individual difference among the same kind of battery had great influence on the performance of battery team and the whole capability of electric vehicle.
Firstly, how to study the performance of battery discharging by experiment modeling was introduced. Experiment modeling was the fundamental research of the project appointed by Beijing science and technology committee (the project name is practical energy management system based on field bus for electric vehicles, contract No. 9550421000). Secondly, how to collect and deal with experiment signal was discussed. The configurations of system including static data collecting system and dynamic data collecting system were discussed next. By using the newly issued chip abroad applied in monitoring battery, the system had a simple configuration and sound ratio between performance and price.
The study of experiment modeling about the discharging performance of power battery was emphasized. Experiment modeling was divided into static experiment modeling and dynamic experiment modeling. The static experiment model including voltage & ampere-time model and the model of the equilibrium of battery capacity when the battery was charged and discharged was discussed in detail. The latter was focused on how the discharging conditions including discharging intensity, intermission time and environmental temperature influenced the parameters of the
math model. Through the method of experiment modeling, the performances of the four kinds of power batteries (Valve regulated lead-acid battery, Colloid Lead-Acid battery, MH-Ni battery and Lithium-ion battery) were compared. With hundreds of discharging tests, some significant results were gained.
In addition, the application of experimental modeling of battery in designing BMS and estimating SOC was demonstrated briefly.
引文
[1]李建平，关于汽车排放控制及其建议，汽车研究与应用，1999．5，P18-23
[2]雷惊雷等，电动车、电动车用电源及其发展战略，《电源技术》，2001．2 Vol．25 No．1 P40
[3]http://www.chinabatteryonline.com
[4]http://www.china-ev.com
[5]新华网
[6]陈清泉，电动车技术发展和前景展望，电工技术杂志，1996．11第6期，P2
[7]程夕明等，电动汽车能量存储技术概况，电源技术，2001．2，Vol．25 No．1，P48
[8]麻友良、陈全世，混合动力电动汽车用蓄电池不一致的影响分析，电动车辆研究与开发，2001年8月
[9]Doanh Tran, Euthemios Stamos, Michael Cummins, Jeep Commander 2 Fuel Cell Hybrid Electric Demonstration Vehicle, EVS18
[10]Yuh-Fwu Chou, Kuo-Kuang Peng, Mei-Fang Huang, Ho-Yin Pun, Chi-Sang Lau,etc.,A Battery Management System of Electric Scooter using Li-ion Battery Pack, EVS18
[11]Dipl.-Ing. Detlef Heinemann, Prof. Dr.-Ing. Dietrich Naunin, Diagnosis Software to Assess the Genera/Condition of Traction Modules Evaluation of Measured Data from a BMS and a Test Bench, EVS15
[12]Herman L.N. Wiegman Prof. R.D. Lorenz, High Efficiency Battery State Control and Power Capability Prediction, EVS15
[13]朱元，韩晓东，田光宇，电动汽车动力电池SOC预测技术研究，电动车辆研究与开
发，2000-07-15，P14
[14]电动车辆研究与开发汇编(上，下) 1999
[15]Li SUN (孙力), Xinde TAN (谭新德), Fuchun XIE, Chunli SONG, The Battery Management System for Electric Vehicle Based on Estimating Battery's States, EVS15
[16]马润津、孙力、田红芳，The Identify of Dynamic Model and Self-tuning Prediction of SOC for EV, EVS18
[17]陈世全 等，轻型客货车的研究与开发，中国电动汽车研究与开发，1997，P76
[18]Sun Fengchun, Zhang Chengning, Sun Liqing, Demonstration Program of Electric Bus for Public Transport in Beijing, EVS17
[19]M.Ceraolo,R. etc. State-of-charge estimation for improving management of Electric Vehicle lead-acid batteries during charge and discharge, EVS13
[20]Luigi Piegari, Ciro Tortora, Ottorino Veneri, A Mathematical Model of Charge and Discharge for Lead Batteries in Electric Road Vehicles, Eva18
[21]Buonarota, A.,Menga,P. ENEL,Electrical Research Centre Italy, Application of Mathematical Model of the Lead Acid Battery in the Design and Operation of Electric Vihicles, EVS10
[22]Giglioli,R.,Buonarota,A.,Menga,P. ENEL-D.S.R Italy, Ceraolo,M., Charge and Discharge Fourth Order Dynamic Model of Lead Acid Battery, EVS10
[23]Jae-Seung Koo, Sun-Soon Park, Kil-Young Youn, and Chul-Soo Kim, Development of SOC Estimation Logic using the Steady State DC-IR for SHEV, EVS18
[24]E. Rulli(?)re E. Toutain, A simulation Program for Multi Energy Sources Electric
Vehicles, EVS14
[25]T.Shinpo H.Suzuki, Development of Battery Management System for Electric Vehicle, EVS14
[26]M. Pasquali, M. Ceraolo, V. Sglavo, Modeling and Test on E.V. Lead-Acid Batteries, EVS18
[27]方崇智、萧德云，过程辨识，清华大学出版社，2000年2月
[28]胡汉才编著，单片机原理及其接口技术，清华大学出版社，2001年1月
[29]肖秀玲、王贵明、王金灿，基于DS2438芯片的电动车蓄电池在线监测系统，制造业自动化，Vol．24 No．11 P15-18，2002年11月
[30]李华 主编，MCS-51系列单片机实用接口技术，北京航空航天大学出版社，1993年8月
[31]王幸之、王雷等，单片机应用系统抗干扰技术，北京航空航天大学出版社，2000年9月
[32]李朝青编著，PC机及单片机数据通信技术，北京航空航天大学出版社，2001年6月
[33]Mark Nelson，串行通信开发指南(第二版)，中国水利水电出版社，2001年3月
[34]吴师通，Visual Basic实用编程百例，清华大学出版社，2000年7月
[35]David J.Kruglinski等，Visual C++6.0技术内幕，北京希望电子出版社，2000年2月
[36]王俊、温旭辉、徐志捷，质子交换膜燃料电池电气性能实验及建模研究，电源技术，Vol．25 No．1 Feb．2001，P10-12
[37]ThermoAnalytics Inc., Battery modeling for HEV Simulation by ThermoAnalytics Inc, web site at http://www.thermoanalytics.com/support/publications/batteryrnodelsdoc.html,
accessed 28 May 2002
[38]Ren(?) Stra(?)nick, Dietrich Naunin, Dirk Freyer, Berlin University of technology, Lead-Gel-Traction-Battery Modelling in a Battery Management System for Electric Vehicles, 2002, EVS19
[39]肖秀玲、王贵明，用于电动自行车的四种动力蓄电池实验建模比较研究，2002中国电动汽车研究与开发，P79-89，北京理工大学出版社，2002年12月
[40]肖秀玲、王贵明，低成本、高性能电动车电池管理系统的研究，工业自动化应用实践，电子工业出版社，2002年1月
[41]朱元、韩晓东、田光宇，电动汽车动力电池SOC预测技术研究，电源技术，Vol．24 No．3 Jun．2000,P153-156
[42]韩晓东、傅春江等，判断电动车电池放电终止状态的新标准，电池，Vol．32 No．2 Apr．2002 P117-120
[43]Gregory L. Plett，Kalman-Filter SOC Estimation for LiPB HEV Cells, 2002, EVS19
[44]郏航，电动车电池电量监测系统的研究与实现，清华大学硕士学位论文，1996年6月
[45]陈清泉、孙逢春等，现代电动汽车技术，北京理工大学出版社，2002年11月
[46]胡居琦，电动车蓄电池电量监测技术研究，北方工业大学硕士学位论文，2002年6月
[47]谭新德，电动车能量管理系统的设计，北方工业大学硕士学位论文，1998年6月
[48]S. Piller, M. Perrin and A. Jossen, Methods for state-of-charge determination and their applications,Journal of Power Sources, vol. 96 (2001), pp. 113-120
[49]C. Barbier, H. Meyer, B. Nogarede and S. Bensaoud, A battery state of charge
indicator for electric vehicle, Proceedings of the Institution of Mechanical Engineers. Automotive Electronics. International Conference, 17-19 May 1994, pp. 29-34, London, UK.
[50]W. Steffens and P. L(?)rkens, Ladezustandssch(?)tzung von bleibatterien mit hilfe des Kalman-filters, etzArchiv, vol. 8, no. 7, 1986, pp. 231-236. (In German. English title: State of charge estimation of leadacid batteries using a Kalman filtering technique).
[51]G. Plett, LiPB dynamic cell models for Kalman-filter SOC estimation, EVS19
[52]Gregory L. Plett Kalman-Filter SOC Estimation for LiPB HEV Cells, EVS19
[2]雷惊雷等，电动车、电动车用电源及其发展战略，《电源技术》，2001．2 Vol．25 No．1 P40
[3]http://www.chinabatteryonline.com
[4]http://www.china-ev.com
[5]新华网
[6]陈清泉，电动车技术发展和前景展望，电工技术杂志，1996．11第6期，P2
[7]程夕明等，电动汽车能量存储技术概况，电源技术，2001．2，Vol．25 No．1，P48
[8]麻友良、陈全世，混合动力电动汽车用蓄电池不一致的影响分析，电动车辆研究与开发，2001年8月
[9]Doanh Tran, Euthemios Stamos, Michael Cummins, Jeep Commander 2 Fuel Cell Hybrid Electric Demonstration Vehicle, EVS18
[10]Yuh-Fwu Chou, Kuo-Kuang Peng, Mei-Fang Huang, Ho-Yin Pun, Chi-Sang Lau,etc.,A Battery Management System of Electric Scooter using Li-ion Battery Pack, EVS18
[11]Dipl.-Ing. Detlef Heinemann, Prof. Dr.-Ing. Dietrich Naunin, Diagnosis Software to Assess the Genera/Condition of Traction Modules Evaluation of Measured Data from a BMS and a Test Bench, EVS15
[12]Herman L.N. Wiegman Prof. R.D. Lorenz, High Efficiency Battery State Control and Power Capability Prediction, EVS15
[13]朱元，韩晓东，田光宇，电动汽车动力电池SOC预测技术研究，电动车辆研究与开
发，2000-07-15，P14
[14]电动车辆研究与开发汇编(上，下) 1999
[15]Li SUN (孙力), Xinde TAN (谭新德), Fuchun XIE, Chunli SONG, The Battery Management System for Electric Vehicle Based on Estimating Battery's States, EVS15
[16]马润津、孙力、田红芳，The Identify of Dynamic Model and Self-tuning Prediction of SOC for EV, EVS18
[17]陈世全 等，轻型客货车的研究与开发，中国电动汽车研究与开发，1997，P76
[18]Sun Fengchun, Zhang Chengning, Sun Liqing, Demonstration Program of Electric Bus for Public Transport in Beijing, EVS17
[19]M.Ceraolo,R. etc. State-of-charge estimation for improving management of Electric Vehicle lead-acid batteries during charge and discharge, EVS13
[20]Luigi Piegari, Ciro Tortora, Ottorino Veneri, A Mathematical Model of Charge and Discharge for Lead Batteries in Electric Road Vehicles, Eva18
[21]Buonarota, A.,Menga,P. ENEL,Electrical Research Centre Italy, Application of Mathematical Model of the Lead Acid Battery in the Design and Operation of Electric Vihicles, EVS10
[22]Giglioli,R.,Buonarota,A.,Menga,P. ENEL-D.S.R Italy, Ceraolo,M., Charge and Discharge Fourth Order Dynamic Model of Lead Acid Battery, EVS10
[23]Jae-Seung Koo, Sun-Soon Park, Kil-Young Youn, and Chul-Soo Kim, Development of SOC Estimation Logic using the Steady State DC-IR for SHEV, EVS18
[24]E. Rulli(?)re E. Toutain, A simulation Program for Multi Energy Sources Electric
Vehicles, EVS14
[25]T.Shinpo H.Suzuki, Development of Battery Management System for Electric Vehicle, EVS14
[26]M. Pasquali, M. Ceraolo, V. Sglavo, Modeling and Test on E.V. Lead-Acid Batteries, EVS18
[27]方崇智、萧德云，过程辨识，清华大学出版社，2000年2月
[28]胡汉才编著，单片机原理及其接口技术，清华大学出版社，2001年1月
[29]肖秀玲、王贵明、王金灿，基于DS2438芯片的电动车蓄电池在线监测系统，制造业自动化，Vol．24 No．11 P15-18，2002年11月
[30]李华 主编，MCS-51系列单片机实用接口技术，北京航空航天大学出版社，1993年8月
[31]王幸之、王雷等，单片机应用系统抗干扰技术，北京航空航天大学出版社，2000年9月
[32]李朝青编著，PC机及单片机数据通信技术，北京航空航天大学出版社，2001年6月
[33]Mark Nelson，串行通信开发指南(第二版)，中国水利水电出版社，2001年3月
[34]吴师通，Visual Basic实用编程百例，清华大学出版社，2000年7月
[35]David J.Kruglinski等，Visual C++6.0技术内幕，北京希望电子出版社，2000年2月
[36]王俊、温旭辉、徐志捷，质子交换膜燃料电池电气性能实验及建模研究，电源技术，Vol．25 No．1 Feb．2001，P10-12
[37]ThermoAnalytics Inc., Battery modeling for HEV Simulation by ThermoAnalytics Inc, web site at http://www.thermoanalytics.com/support/publications/batteryrnodelsdoc.html,
accessed 28 May 2002
[38]Ren(?) Stra(?)nick, Dietrich Naunin, Dirk Freyer, Berlin University of technology, Lead-Gel-Traction-Battery Modelling in a Battery Management System for Electric Vehicles, 2002, EVS19
[39]肖秀玲、王贵明，用于电动自行车的四种动力蓄电池实验建模比较研究，2002中国电动汽车研究与开发，P79-89，北京理工大学出版社，2002年12月
[40]肖秀玲、王贵明，低成本、高性能电动车电池管理系统的研究，工业自动化应用实践，电子工业出版社，2002年1月
[41]朱元、韩晓东、田光宇，电动汽车动力电池SOC预测技术研究，电源技术，Vol．24 No．3 Jun．2000,P153-156
[42]韩晓东、傅春江等，判断电动车电池放电终止状态的新标准，电池，Vol．32 No．2 Apr．2002 P117-120
[43]Gregory L. Plett，Kalman-Filter SOC Estimation for LiPB HEV Cells, 2002, EVS19
[44]郏航，电动车电池电量监测系统的研究与实现，清华大学硕士学位论文，1996年6月
[45]陈清泉、孙逢春等，现代电动汽车技术，北京理工大学出版社，2002年11月
[46]胡居琦，电动车蓄电池电量监测技术研究，北方工业大学硕士学位论文，2002年6月
[47]谭新德，电动车能量管理系统的设计，北方工业大学硕士学位论文，1998年6月
[48]S. Piller, M. Perrin and A. Jossen, Methods for state-of-charge determination and their applications,Journal of Power Sources, vol. 96 (2001), pp. 113-120
[49]C. Barbier, H. Meyer, B. Nogarede and S. Bensaoud, A battery state of charge
indicator for electric vehicle, Proceedings of the Institution of Mechanical Engineers. Automotive Electronics. International Conference, 17-19 May 1994, pp. 29-34, London, UK.
[50]W. Steffens and P. L(?)rkens, Ladezustandssch(?)tzung von bleibatterien mit hilfe des Kalman-filters, etzArchiv, vol. 8, no. 7, 1986, pp. 231-236. (In German. English title: State of charge estimation of leadacid batteries using a Kalman filtering technique).
[51]G. Plett, LiPB dynamic cell models for Kalman-filter SOC estimation, EVS19
[52]Gregory L. Plett Kalman-Filter SOC Estimation for LiPB HEV Cells, EVS19