单轴ISG混合动力汽车转矩分配控制策略的研究
|
摘要
单轴ISG混合动力汽车控制策略设计是整车及其各子系统控制器设计中的重要一环，是实现单轴ISG混合动力汽车节能减排的基础。本文以国家“十一五”863节能与新能源汽车重大专项ISG混合动力汽车项目及其整车控制策略设计子课题为背景，研究了驱动工况下转矩分配控制策略、制动力矩动态分配控制策略、再生制动系统与ABS动态协调控制策略以及制动稳定性控制策略，并基于dSPACE实时系统进行了转矩分配控制策略的快速控制原型仿真试验。本文完成的主要工作和结论总结如下：
基于试验数据，建立了发动机、ISG电机、镍氢电池的半经验仿真模型和基于魔术公式的全工况轮胎经验模型，并基于理论建模的方法建立了传动系模型、液压制动系统模型、七自由度整车动力学模型和驾驶员模型，为单轴ISG混合动力汽车转矩分配控制策略的研究提供了仿真和验证的基础。
建立了ISG混合动力系统燃油经济性和排放性能的数值函数，以整车燃油经济性和排放性能最佳为目标函数，采用求解多元函数极值的方法求出在任一转速下的发动机和ISG电机的最佳转矩分配值，作为ISG混合动力系统的最佳工作点。将求解的最佳工作点作为ANFIS系统的先验知识，建立了ANFIS转矩分配系统，用于驱动工况下整车的转矩分配控制。仿真结果表明：与Insight电动辅助控制策略相比，在ANFIS转矩分配控制策略下，ISG混合动力汽车实现了更好的燃油经济性和排放性能。
提出了一种制动路面最佳滑移率的实时估计方法。通过将制动过程中前后轮利用附着系数与各种典型路面的峰值附着系数进行对比来判断为制动路面。根据路面附着系数与滑移率的函数关系，采用黄金分割法对附着系数极大值进行直接搜寻，获得路面的最佳滑移率。根据求得的路面最佳滑移率，设计了基于滑移率控制的制动力矩动态分配控制策略。仿真结果表明：基于滑移率控制的制动力矩动态分配控制策略能够有效的协调再生制动力矩和液压制动力矩，在轻中度制动工况下能高比率的回收制动能量；紧急制动时，在高、中、低以及突变附着路面上均能够通过对制动力矩的动态调整，保证车轮不出现抱死拖滑，在保证制动效能和制动安全的前提下有效的回收制动能量。
针对制动过程中路况的不确定性，将滑移率最优控制问题归结为极值漂移的实时动态寻优问题，提出了基于滑移率自寻优的再生制动系统与ABS动态协调控制策略。设计了滑移率模糊自寻优控制器，并采用遗传算法在线优化模糊控制规则。在高低附着路面、突变路面和分离路面上紧急制动的仿真结果表明：所提出的控制策略不仅能快速自动搜寻并控制车轮滑移率在最佳值附近，实现再生制动系统与ABS的动态协调，保证制动效能和制动稳定性，而且能够在紧急制动情况下回收到可观的制动能量。
为了保证在转向制动工况下的制动横向稳定性，提出了制动稳定性分层协调控制策略。基于模糊控制理论，对制动过程中需求的校正横摆力矩进行估计，将校正横摆力矩的补偿对制动力矩的需求转化为对再生制动力矩和车轮滑移率的调节。设计了滑移率模糊控制器，控制车轮滑移率在判定的目标值。通过对目标滑移率的实时确定，实现上层横摆力矩控制与下层滑移率及再生制动力矩控制的统一调节，保证了车轮不出现抱死。分别进行了转向情况下高低附着路面轻度制动和紧急制动的仿真分析，其结果表明：所提出的制动稳定性分层协调控制策略，在保持制动效能的基础上，实现了比单独实施滑移率控制更好的制动横向稳定性。
最后，进行了单轴ISG混合动力汽车转矩分配控制策略的快速控制原型仿真试验，验证了转矩分配控制策略及算法的基本控制性能，使经离线仿真验证的控制策略及算法进一步的得到完善和验证。
The design of control strategy for singleshaft ISG Hybrid Electric Vehicles is an importantpart in vehicle and subsystems controller development, and the foundation of achieving energysaving and emission reduction. This paper is supported by the energy saving and new energyvehicles major projects of National “The Eleventh Five-year Planning”, and torque distributioncontrol strategy for driving conditions, dynamic braking torque distribution control strategy,dynamical coordinated control strategy for regenerative braking with ABS system, and controlstrategy for enhancing the braking stability of Hybrid Electric Vehicle were researched, and rapidcontrol prototype simulation test of the proposed control strategy were implemented based ondSPACE real-time system. The main research work and conclusions were summarized asfollowing:
In order to provide the simulation and verification foundation of the torque distributioncontrol strategy, Engine model, ISG model, batteries model and all condition tire model usingmagic formula were built based on experimental data, and power train model, hydraulic brakingsystem model, seven-DOF vehicle dynamics model and driver model were developed based onphysical logic of parameters.
The fuel economy and emission performance function of the ISG Hybrid power system wasestablished based on the test data of internal combustion engine and ISG motor, and the data ofoptimal operating points for training ANFIS system was got by the method of searching globalminimum point of multivariable function. A torque distribution system for reasonably distributingthe vehicle’s demand torque of driving to the internal combustion engine and ISG motor based onthe trained ANFIS system was built for decreasing the fuel consumption and emissions. Theresults of simulation show that much better fuel economy and emission performance are achievedunder the ANFIS torque distribution control strategy than electrical assistance control strategy.
A real-time computation method of optimal slip ratio acquisition for braking road conditionwas proposed. The braking road was confirmed by comparing the wheels achieved adhesioncoefficient with peak adhesion coefficient of typical roads, and optimal slip ratio of braking roadwas real-time searched by golden section method according to the function between adhesioncoefficient and slip ratio. A coordinated control strategy based on slip ratio control was designedfor dynamical distribution between regenerative braking torque and hydraulic braking torque. Thesimulation results show that braking energy can be high ratio recycled in mild-moderate brake,braking efficiency and braking safety were assured by avoiding wheel lock under emergencybraking condition.
As the road condition is uncertain, the problem of optimal slip ratio estimation duringbraking was considered as a real-time self-optimizing problem of extremum drift, and a dynamicalcoordinated control method for regenerative braking with ABS system was proposed based on slipratio self-optimization. A fuzzy self-optimizing controller for optimal slip ratio control wasdesigned, and the fuzzy control rules were on-line optimized by a genetic algorithm. Regenerativebraking torque is preferentially adjusted to meet the adjustment demand of total braking torqueunder the state of emergency braking. The braking processes on high, low, mutative and splitadhesion coefficient road were simulated respectively, and results show that the proposed controlalgorithm not only can achieve optimal slip ratio automatically and rapidly, and regenerativebraking system is dynamically coordinated with Anti-lock braking system to ensure the brakingefficiency and braking stability, but also considerable braking energy can be regenerated under thestate of emergency braking.
A hierarchical coordinated control strategy for enhancing the braking stability of hybridelectric vehicle equipped with a regenerative braking system and a hydraulic braking system wasproposed. The desired yaw moment compensation was formulated with a preference toregenerative braking torque and wheels slip ratio control during braking process. The upper-levelyaw moment control was coordinated with lower-level wheels slip ratio and regenerative brakingtorque control by the nominated target slip ratio. Simulation was performed under low and highadhesion coefficience road with cornering, and the results show that the hybrid electric vehiclewith the hierarchical coordinated control strategy not only can keep good Braking efficiency, butalso achieves better performances of dynamic braking stability than the vehicle only with slip ratiocontrol.
Finally, the proposed torque distribution control strategy was further verified and perfectedby Rapid control prototype test.
基于试验数据，建立了发动机、ISG电机、镍氢电池的半经验仿真模型和基于魔术公式的全工况轮胎经验模型，并基于理论建模的方法建立了传动系模型、液压制动系统模型、七自由度整车动力学模型和驾驶员模型，为单轴ISG混合动力汽车转矩分配控制策略的研究提供了仿真和验证的基础。
建立了ISG混合动力系统燃油经济性和排放性能的数值函数，以整车燃油经济性和排放性能最佳为目标函数，采用求解多元函数极值的方法求出在任一转速下的发动机和ISG电机的最佳转矩分配值，作为ISG混合动力系统的最佳工作点。将求解的最佳工作点作为ANFIS系统的先验知识，建立了ANFIS转矩分配系统，用于驱动工况下整车的转矩分配控制。仿真结果表明：与Insight电动辅助控制策略相比，在ANFIS转矩分配控制策略下，ISG混合动力汽车实现了更好的燃油经济性和排放性能。
提出了一种制动路面最佳滑移率的实时估计方法。通过将制动过程中前后轮利用附着系数与各种典型路面的峰值附着系数进行对比来判断为制动路面。根据路面附着系数与滑移率的函数关系，采用黄金分割法对附着系数极大值进行直接搜寻，获得路面的最佳滑移率。根据求得的路面最佳滑移率，设计了基于滑移率控制的制动力矩动态分配控制策略。仿真结果表明：基于滑移率控制的制动力矩动态分配控制策略能够有效的协调再生制动力矩和液压制动力矩，在轻中度制动工况下能高比率的回收制动能量；紧急制动时，在高、中、低以及突变附着路面上均能够通过对制动力矩的动态调整，保证车轮不出现抱死拖滑，在保证制动效能和制动安全的前提下有效的回收制动能量。
针对制动过程中路况的不确定性，将滑移率最优控制问题归结为极值漂移的实时动态寻优问题，提出了基于滑移率自寻优的再生制动系统与ABS动态协调控制策略。设计了滑移率模糊自寻优控制器，并采用遗传算法在线优化模糊控制规则。在高低附着路面、突变路面和分离路面上紧急制动的仿真结果表明：所提出的控制策略不仅能快速自动搜寻并控制车轮滑移率在最佳值附近，实现再生制动系统与ABS的动态协调，保证制动效能和制动稳定性，而且能够在紧急制动情况下回收到可观的制动能量。
为了保证在转向制动工况下的制动横向稳定性，提出了制动稳定性分层协调控制策略。基于模糊控制理论，对制动过程中需求的校正横摆力矩进行估计，将校正横摆力矩的补偿对制动力矩的需求转化为对再生制动力矩和车轮滑移率的调节。设计了滑移率模糊控制器，控制车轮滑移率在判定的目标值。通过对目标滑移率的实时确定，实现上层横摆力矩控制与下层滑移率及再生制动力矩控制的统一调节，保证了车轮不出现抱死。分别进行了转向情况下高低附着路面轻度制动和紧急制动的仿真分析，其结果表明：所提出的制动稳定性分层协调控制策略，在保持制动效能的基础上，实现了比单独实施滑移率控制更好的制动横向稳定性。
最后，进行了单轴ISG混合动力汽车转矩分配控制策略的快速控制原型仿真试验，验证了转矩分配控制策略及算法的基本控制性能，使经离线仿真验证的控制策略及算法进一步的得到完善和验证。
The design of control strategy for singleshaft ISG Hybrid Electric Vehicles is an importantpart in vehicle and subsystems controller development, and the foundation of achieving energysaving and emission reduction. This paper is supported by the energy saving and new energyvehicles major projects of National “The Eleventh Five-year Planning”, and torque distributioncontrol strategy for driving conditions, dynamic braking torque distribution control strategy,dynamical coordinated control strategy for regenerative braking with ABS system, and controlstrategy for enhancing the braking stability of Hybrid Electric Vehicle were researched, and rapidcontrol prototype simulation test of the proposed control strategy were implemented based ondSPACE real-time system. The main research work and conclusions were summarized asfollowing:
In order to provide the simulation and verification foundation of the torque distributioncontrol strategy, Engine model, ISG model, batteries model and all condition tire model usingmagic formula were built based on experimental data, and power train model, hydraulic brakingsystem model, seven-DOF vehicle dynamics model and driver model were developed based onphysical logic of parameters.
The fuel economy and emission performance function of the ISG Hybrid power system wasestablished based on the test data of internal combustion engine and ISG motor, and the data ofoptimal operating points for training ANFIS system was got by the method of searching globalminimum point of multivariable function. A torque distribution system for reasonably distributingthe vehicle’s demand torque of driving to the internal combustion engine and ISG motor based onthe trained ANFIS system was built for decreasing the fuel consumption and emissions. Theresults of simulation show that much better fuel economy and emission performance are achievedunder the ANFIS torque distribution control strategy than electrical assistance control strategy.
A real-time computation method of optimal slip ratio acquisition for braking road conditionwas proposed. The braking road was confirmed by comparing the wheels achieved adhesioncoefficient with peak adhesion coefficient of typical roads, and optimal slip ratio of braking roadwas real-time searched by golden section method according to the function between adhesioncoefficient and slip ratio. A coordinated control strategy based on slip ratio control was designedfor dynamical distribution between regenerative braking torque and hydraulic braking torque. Thesimulation results show that braking energy can be high ratio recycled in mild-moderate brake,braking efficiency and braking safety were assured by avoiding wheel lock under emergencybraking condition.
As the road condition is uncertain, the problem of optimal slip ratio estimation duringbraking was considered as a real-time self-optimizing problem of extremum drift, and a dynamicalcoordinated control method for regenerative braking with ABS system was proposed based on slipratio self-optimization. A fuzzy self-optimizing controller for optimal slip ratio control wasdesigned, and the fuzzy control rules were on-line optimized by a genetic algorithm. Regenerativebraking torque is preferentially adjusted to meet the adjustment demand of total braking torqueunder the state of emergency braking. The braking processes on high, low, mutative and splitadhesion coefficient road were simulated respectively, and results show that the proposed controlalgorithm not only can achieve optimal slip ratio automatically and rapidly, and regenerativebraking system is dynamically coordinated with Anti-lock braking system to ensure the brakingefficiency and braking stability, but also considerable braking energy can be regenerated under thestate of emergency braking.
A hierarchical coordinated control strategy for enhancing the braking stability of hybridelectric vehicle equipped with a regenerative braking system and a hydraulic braking system wasproposed. The desired yaw moment compensation was formulated with a preference toregenerative braking torque and wheels slip ratio control during braking process. The upper-levelyaw moment control was coordinated with lower-level wheels slip ratio and regenerative brakingtorque control by the nominated target slip ratio. Simulation was performed under low and highadhesion coefficience road with cornering, and the results show that the hybrid electric vehiclewith the hierarchical coordinated control strategy not only can keep good Braking efficiency, butalso achieves better performances of dynamic braking stability than the vehicle only with slip ratiocontrol.
Finally, the proposed torque distribution control strategy was further verified and perfectedby Rapid control prototype test.
引文
[1]田光宇，彭涛，林成涛，等.混合动力电动汽车关键技术[J].汽车技术.2002，01：8-11.
[2]何洪文，祝嘉光，李剑.混合动力汽车技术发展与现状[J].车辆与动力技术.2004，02：50-55.
[3]张兴业.世界汽车工业新的技术革命[J].山东交通学院学报.2007，15(1):1-7.
[4] Wolfram Buschhaus，Larry R．Brandedburg，Ross M．Stuntz．Hybrid electric vehicledevelopment at Ford． The15th International Electric Vehicle Symposium andExposition．Brussels，Belgium,1998．
[5] TOYOTA Motor Corporation. Development of electric motors for the Toyota hybrid vehicle“PRIUS”．The16th International Electric Vehicle Symposium and Exposition．Beijing，China,1999．
[6]徐汉章，罗慧超.混合动力技术进展及相关建议[J].交通节能与环保.2007，01：15-17.
[7]甑子健实现“三纵三横”关键技术突破，科技创新带动我国新能源汽车战略性新兴产业形成[J].中国科技财富.2011,26-28.
[8]吴憩棠《.十二五》“863计划”电动汽车重大项目已启动[J].新能源汽车.2011，22(02):14-17.
[9]刑伟岩，宋振宽，周雅夫.混合动力电动汽车实现商品化的关键因素[J].汽车工业研究.2002，09：14-16.
[10]李鹏. ISG型轻度混合动力汽车系统概述[J].上海汽车.2007，03：3-6.
[11]徐乔. B-ISG混合动力汽车[J].汽车与配件.2006，27(13):37-39.
[12]朱喆.车用BSG系统简介[J].汽车维修.2011，4:46-47.
[13]李振磊，林逸，龚旭.基于Star t-Stop技术的微混轿车仿真及试验研究[J].中国机械工程.2010，21(01):110-113.
[14]叶先军，赵韩，张炳力，等. BSG混合动力轿车动力系统参数设计及试验研究[J].汽车技术.2008，6:24-27.
[15]曹占国. ISG混合动力车转矩控制策略及前向式Simulink建模仿真[D].镇江：江苏大学，2010.
[16]胡洪祥.驱动工况的ISG型混合动力汽车控制策略研究[D].重庆：重庆大学，2006.
[17]王峰，冒晓建，卓斌. ISG并联混合动力轿车最优转矩分配策略[J].重庆大学学报.2008，31(05):499-504.
[18] Sun Hui, Jiang Ji-hai, Wang Xin. Torque control strategy for a parallel hydraulic hybridvehicle [J]. Journal of Terramechanics.2009,46(6):259-265.
[19]彭栋,殷承良,张建武.混合动力汽车制动力矩动态分配控制策略研究[J].系统仿真学报,2007，19（22）：5254-5259.
[20] Xiao Wenyong, Wang Feng, Zhuo Bin. Regenerative Braking Algorithm for an ISG HEVBased on Regenerative Torque Optimization[J]. Journal of ShangHai JiaotongUniversity(Science),2008，Vol.13No.2:193-200
[21]郭金刚，王军平，曹秉刚.电动车最大化能量回收制动力分配策略研究[J].西安交通大学学报.2008，42(05):607-611.
[22]何仁，陈庆樟.汽车制动能量再生系统制动力分配研究[J].兵工学报.2009，30(02):205-208.
[23] Gao Y, Ehsani M. Electronic Braking System of EV-Integration of Regenerative Braking,Automatic Braking Force Control and ABS [J]. SAE Paper2002-01-2478.
[24]张元才，余卓平，徐乐，等.基于制动意图的电动汽车复合制动系统制动力分配策略研究[J].汽车工程.2009，31(03):244-249.
[25]童毅，张俊智，欧阳明高.混合动力汽车扭矩管理策略[J].清华大学学报(自然科学版).2003，43(08):1134-1137.
[26]于秀敏，曹珊，李君，等.混合动力汽车控制策略的研究现状及其发展趋势[J].机械工程学报,2006,42(11):10-16.
[27]田甜，郑燕萍，蒋元广，戴能红，汪涵.混合动力汽车控制策略优化研究综述[J].公路与汽运.2010，05：1-4.
[28]张承慧，李珂，崔纳新，等.混合动力汽车能量及驱动系统的关键控制问题研究进展[J].山东大学学报（工学版）.2011，41(5):1-8.
[29] SALMASI F R. Control strategies for hybrid electric vehicles: evolution, classification，comparison, and future trends [J]. IEEE Transactions on Vehicular Technology，2007，56(5):2393-2404．
[30] Kimura A, Abe T, Sasaki S. Drive force control of a parallel-series hybrid system [J]. JSAEReview.1999,20(3):337-341.
[31] Ehsani M, Gao Yimin, Butler K L. Application of electrically peaking hybrid (ELPH)propulsion system to a full-size passenger car with simulated design verification [J]. IEEETransactions on Vehicular Technology,1999,48(6):1779-1787.
[32] Rahman Z, Butler K L, Ehsani M. A comparison study between two parallel hybrid controlConcepts[J]. SAE Paper2000-01-0994.
[33] Chan-Chiao Lin, Jun-Mo Kang, Grizzle J W, et al. Energy Management Strategy for aParallel Hybrid Electric Truck[C].Proceedings of the American Control Conference.Arlington: VA, USA,2001.
[34] Chan-Chiao Lin, Huei Peng, Soonil Jeon, et al. Control of a Hybrid Electric Truck Basedon Driving Pattern Recognition [C].Proceeding of the AVEC.2002.
[35]张欣，李国岫，宋建锋，等.并联式混合动力汽车多能源动力总成控制单元的研究与开发[J].高技术通讯.2003，13（2）：92-96.
[36] ADVISOR2002software, http://www.ctts.nrel.gov/.
[37] National Renewable Energy Laboratory. ADVISOR Documentation. Golden Co.[Online].Available: http://www.ctts.nrel.gov/analysis/.
[38] Johnson V H, Wipke K B, Rausen D J. HEV control strategy for real-time optimization offuel economy and emissions [J]. SAE Paper2000-01-1543.
[39] Paganelli G, Guerra T M, Delprat S, et al. Simulation and assessment of power controlstrategies for a parallel hybrid car[J]. Proc Institution Mechanical Engineers, Part D: Journalof Automobile Engineering.2000,214(7):705-717.
[40] Wagener A., Korner C., Seger P. et al. Cost function based adaptive energy management inhybrid drivetrains[C]. Proceedings of the18th International Electric Vehicle Symposium.Berlin,Germany,2001.
[41] Paganelli G, Ercole G, Brahma A, et al. General supervisory control policy for the energyoptimization of charge-sustaining hybrid electric vehicles[J]. JSAE Review.2001,22(4):511-518.
[42] Paganelli G, Tateno M. Control development for a hybrid-electric sport-utility vehicle:strategy, implementation and field test results[C]. Proceeding of the American ControlConference.Arlington, VA, USA,2001,5064-5069
[43]胡红斐，罗玉涛，赵克刚.基于瞬时优化的HEV控制策略[J].交通与计算机.2006,24(1)：130-136.
[44]朱诗顺，任永乐，张月滨等.基于电量平衡的串联混合动力汽车瞬时优化控制[J].中国机械工程，2008.03
[45] Galdi V, Ippolito L, Piccolo A, et al. Multi-objective optimization for fuel economy andemissions of HEV using the goal-attainment method. Proc of the18th International ElectricVehicle Symposium, Berlin, Germany,2001
[46] Delprat S, Guerra T M, Rimaux J. Optimal control of a parallel powertrfrom globaloptimization to real time control strategy. Proc of the18th International Electric VehicleSymposium, Berlin, Germany,2001
[47]胡红斐，黄向东，罗玉涛，等.并联式混合动力电动汽车全局优化控制[J].华南理工大学学报，2006，(4):28-32.
[48]房立存，秦世引.混合动力电动汽车最优控制与实例仿真[J].系统仿真学报，2007,19(1):110-114.
[49]浦金欢.混合动力汽车能量优化管理与控制策略研究[D].上海：上海交通大学，2004.
[50] Schouten Niels J，Salman Mutasim A，Kheir Naim A. Fuzzy Logic Control for ParallelHybrid Vehicles [J]. IEEE Transactions on Control Systems Technology.2002，10(3):460-468．
[51] N J Schouten, M A Salman, N A Kheir, Energy management strategies for parallel hybridvehicles using fuzzy logic[J]. Control Engineering Practice.2003,11(2):171-177.
[52]陈健，李彦，吴亚祥，廖荣福.混合动力电动汽车模糊逻辑控制策略的研究与仿真[J].汽车工程,2006,28(4):322-326.
[53] Kheir N A, Salman M A, Schouten N J. Emissions and fuel economy trade-off for hybridvehicles using fuzzy logic[J]. Mathematics And Computers In Simulation,2004,66(2):155-172.
[54]胡洪祥，秦大同，舒红，杨亚联，丁李辉. ISG型混合动力汽车模糊控制策略及仿真[J].重庆大学学报（自然科学版）.2006，29(11):1-5.
[55] QUN Zeng,Juhua Huang. The design and simulation of fuzzy logic controller for parallelhybrid electric vehicles[C]//2007Proceedings of the IEEE International Conference onAutomation and Logistics.2007:8-18.
[56] Tomaz Katrasnik. Hybridization of powertrain and downsizing of IC engine-A way to reducefuel consumption and pollutant emissions-Part1[J]. Energy Conversion andManagement.2007,48(5):1411–1423.
[57]姚明亮，秦大同，胡明辉，叶心.基于模糊逻辑控制策略的混合动力汽车仿真研究[J].汽车工程，2007,29(11):934-937.
[58] H Zhong, F Wang,G-Q Ao, et al. An optimal torque distribution strategy for an integratedstarter—generator parallel hybrid electric vehicle based on fuzzy logic control [J].Proceedings of the Institution of Mechanical Engineers, Part D: Journal of AutomobileEngineering.2008,222(1):79-92.
[59] CHEN Jian, LI Yan, WANG Jian. Simultaneous optimisation of fuel consumption andemissions for a parallel hybrid electric SUV using fuzzy logic control [J]. InternationalJournal Of Vehicle Design,2008,46(2):204-218.
[60] Ferreira AA, Pomilio JA, Spiazzi G, Slva L D. Energy management fuzzy logic supervisoryfor electric vehicle power supplies system [J]. IEEE Transactions on Power Electronics,2008,23(1):107~115.
[61]吴晓刚，王旭东，毛亮. ISG型混合动力汽车能量管理模糊控制的研究[J].汽车工程.2011，33(07):558-562.
[62]白中浩,王耀南,曹立波,等.混合动力电动汽车能量自适应模糊控制研究[J].汽车工程,2005,27(4):389-391.
[63] WU Jian, ZHANG Chenghui, CUI Naxin. Fuzzy energy management strategy of parallelhybrid electric vehicle based on particle swarm optimization [J]. Control and Decision,2008,23(1):46-50.
[64] Amir Poursamad, Morteza Montazeri. Design of genetic-fuzzy control strategy for parallelhybrid electric vehicles[J]. Control Engineering Practice.2008,16(7):861-873.
[65] Mohebbi M,Charkhgard M,Farrokhi M.Optimal neuro-fuzzy control of parallel hybridelectric vehicles[C]//2005IEEE Conference on Vehicle Power and Propulsion.2005:252-256.
[66]钱立军,袭著永，赵韩.基于模糊神经网络的混合动力汽车控制策略仿真[J].系统仿真学报,2006,18(5):1384～1387.
[67] Poursamad A, Montazeri M. Design of genetic-fuzzy control strategy for parallel hybridelectric vehicles [J]. Control Engineering Practice,2008,16(7):861-873
[68]叶先军，赵韩，张炳力最佳工作点ISG混合动力汽车性能优化[J].应用科学学报.2008，(26)5:541-546.
[69]郭金刚，王军平，曹秉刚.电动车最大化能量回收制动力分配策略研究[J].西安交通大学学报.2008，42(05):607-611.
[70]周磊，罗禹贡，杨殿阁，等.基于滑移率试探的电动车辆制动控制策略[J].清华大学学报（自然科学版）.2008，48(5):883-887.
[71]彭栋.混合动力汽车制动能量回收与ABS集成控制研究[D].上海：上海交通大学，2007.
[72]张建龙，殷承良，张建武，等.混合动力汽车机电复合制动控制系统研究[J].系统仿真学报，2009，21（16）：5169-5174.
[73]彭栋,殷承良,张建武.混合动力汽车制动力矩动态分配控制策略研究[J].系统仿真学报,2007，19（22）：5254-5259.
[74] D. Peng, Y. Zhang, C.-L. Yin and J.-W. Zhang. Combined control of a regenerative brakingand antilock braking system for hybrid electric vehicles [J]. International Journal ofAutomotive Technology.2008,9(6):749-757.
[75]何仁，陈庆樟.汽车制动能量再生系统制动力分配研究[J].兵工学报.2009，30(02):205-208.
[76] F Wang, B Zhuo. Regenerative braking strategy for hybrid electric vehicles based onregenerative torque optimization control[J]. Proceedings of the Institution of MechanicalEngineers, Part D: Journal of Automobile Engineering.2008,222(4):499-513.
[77]李鑫.并联式Plug-in HEV整车控制及能量管理系统研究[D].合肥：合肥工业大学.2010.
[78]陈庆樟，何仁，赵连生.汽车能量再生制动防抱死集成控制方法研究[J].中国机械工程.2009，20（2）：245-247.
[79]周磊，罗禹贡，李克强，等.电动汽车回馈制动与防抱死制动集成控制[J].清华大学学报（自然科学版），2009，49（5）：728-732.
[80] T K Bera, K Bhattacharya, A K Samantaray. Bond graph model-based evaluation of a slidingmode controller for a combined regenerative and antilock braking system[J]. Proceedings ofthe Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering.2011,225(07):918-934.
[81] J-Z Zhang, X Chen, P-J Zhang. Integrated control of braking energy regeneration andpneumatic anti-lock braking[J]. Proceedings of the Institution of Mechanical Engineers, PartD: Journal of Automobile Engineering.2010,224(5):587-610.
[82] Zhang J，Kong D，Chen L，et al. Optimization of control strategy for regenerative braking ofan electrified bus equipped with an anti-lock braking system [J]. Proc. IMechE Part D: J.Automobile Engineering,2011，published online19October2011,1-13.
[83]张勇.基于主动制动的汽车稳定性控制系统开发研究[D].上海：上海交通大学，2007.
[84]赵国柱，杨正林，魏民祥，等.电动微型客车的机电复合制动稳定性分析[J]汽车工程2006，28（7）：681-685.
[85] Sakai, S. and Hori, Y. Advanced motion control of electric vehicle with fast minor feedbackloops: basic experiments using the4-wheel motored EV “UOT Electric March II”[J]. JSAEReview.2001,22(4):527-536.
[86]张建龙，张建武，袁明，殷承良.混合动力汽车操纵稳定性模糊控制仿真研究[J].系统仿真学报.2009，21（20）：6600-6607.
[87] Donghyun Kim, Hyunsoo Kim. Vehicle stability control with regenerative braking andelectronic brake force distribution for a four-wheel drive hybrid electric vehicle [J].Proceedings of the Institution of Mechanical Engineers, Part D: Journal of AutomobileEngineering.2006220(6):683-693
[88] D-H Kim, J-M Kim, S-H Hwang, et al. Optimal brake torque distribution for a Four wheeldrive hybrid electric vehicle stability enhancement. Proceedings of the Institution ofMechanical Engineers, Part D: Journal of Automobile Engineering2007221(11):1357-1366.
[89] Leo Gilles. ESC与再生型制动在混合动力车上的集成[J].汽车与配件.2011，14：27-29.
[90]李卫民.混合动力汽车控制系统与能量管理策略研究[D].上海：上海交通大学，2008.
[91]黄伟.基于CVT的四轮驱动混合动力汽车传动控制策略研究[D].长沙：湖南大学，2008.
[92]朱阳，赵治国.混合动力汽车发动机建模方法的研究[J].上海汽车.2009,6:9-12.
[93] Johnson V H, Wipke K B, Rausen D J. HEV control strategy for real-time optimization offuel economy and emissions. SAE2000-01-1543.
[94]钱立军.混合动力电动汽车控制策略与传动系的优化匹配研究[D].合肥：合肥工业大学，2004.
[95]李贵海.电池SOC估算策略研究[D].杭州：浙江大学，2006.
[96]刘惟信.汽车设计.北京：清华大学出版社，2001.
[97]余志生.汽车理论[M].3版.北京:机械工业出版社，2004.
[98]葛安林、李焕松、武文治等.动态三参数最佳换档规律的研究.汽车工程.1992（4）.
[99]张俊智、王丽芳、葛安林.自动换档规律的研究.机械工程学报.1999（8）
[100]郭孔辉，侯永平.轮胎非稳态转向特性半经验模型[J].汽车工程.1999,21(3):129-133.
[101] Pacejka, H. B., Tire and Vehicle Dynamics, Society of Automotive Engineers andButterworth-Heinemann, Oxford,2002.
[102]安丽华.汽车电子稳定性程序（ESP）控制方法及联合仿真研究[D].南京：南京理工大学，2009.
[103]庄晔.轮胎高速侧向试验方法与数据处理[D].长春：吉林大学，2001年．
[104]秦大同，邓涛，杨阳，等.基于前向建模的ISG型CVT混合动力系统再生制动仿真研究[J].中国机械工程.2009,19(5):618-624.
[105]黄妙华，喻厚宇.采用CVT的并联HEV驱动系统最佳工作点的确定[J].武汉理工大学学报:信息与管理工程版,2004,26(3):168-172.
[106]陈继光. Matlab与自适应神经网络模糊推理系统[M].济南：山东省地图出版社，2002.
[107] Jang, J.-S. R., ANFIS: Adaptive-Network-based Fuzzy Inference Systems [J]. IEEETransactions on Systems, Man, and Cybernetics.1993,23(3):665-685.
[108]孙增圻，邓志东，张再兴.智能控制理论及技术[M].北京：清华大学出版社.
[109]方锡邦.汽车检测技术与设备[M].北京：人民交通出版社，2005.
[110]秦大同，叶心，胡明辉，等. ISG型中度混合动力汽车驱动工况控制策略优化[J].机械工程学报.2010,46(12):86-92.
[111]刘传李，贾东红，杨中乐.内燃机节油率计算的探讨[J].内燃机工程.1996，17(1):52-58.
[112] Li J, Zhang J W, Yu F. An investigation into fuzzy controller for anti-lock braking systembased on road autonomous identification [R].SAE Technical Paper2001-01-0599.
[113] Zhou Lei, Luo Yugong, Yang Diange, et al. A Novel Brake Control Strategy for ElectricVehicles Based on Slip Trial Method[C]//Proceedings of the2007IEEE InternationalConference on Vehicular Electronics and Safety, Beijing, china,2007：225-230.
[114] Okan TUR, Ozgur USTUN, R. Nejat TUNCAY. An Introduction to Regenerative Brakingof Electric Vehicles as Anti-Lock Braking System[C]//Proceedings of the2007IEEEIntelligent Vehicles Symposium. Istanbul, Turkey, June13-15,2007:944-948.
[115]齐志权，刘昭度，时开斌，等.基于汽车ABS/ASR/ACC集成化系统的ABS参考车速确定方法的研究[J].汽车工程.2003，25(6):617-620.
[116]刘国福.基于滑移率的车辆防抱死制动系统的研究[D].长沙：国防科学技术大学，2007.
[117]叶先军，赵韩.基于路面识别的HEV制动系统控制算法研究[J].系统仿真学报，2010，22(12):2990-2994.
[118]王纪森，杨旭东.汽车防抱制动系统的自寻最优控制[J].汽车工程，2004，26（3）：299-301.
[119]沈俊，宋健，王会义.用小波分析获取路面最佳滑移率的研究[J].农业机械学报.2007，38(7):29-31.
[120]孙仁云，李治.基于变路面SBC最佳滑移率的研究[J].中国机械工程.2008,19(4):481-485.
[121]张代胜，李伟.基于滑移率的汽车防抱模糊控制方法与仿真[J].农业机械学报.2002，33(2):28-31.
[122] Yimin Gao, Mehrdad Ehsani. Electronic braking system of EV and HEV-Integration ofregenerative braking, automatic braking force control and ABS[C]//Future TransportationTechnology Conference.California,USA:SAE,2001:2001-01-2478.
[123] Nakamura E,Soga M,Sa kaiki hiroA et al. Development of Electronically Controlled BrakeSystem for Hybrid Vehicle[J]. SAE Paper,2002-01-0300.
[124] Yasushi Aoki, Kenji Suzuki, Hiroshi Nakano, et al.Development of Hydraulic Servo BrakeSystem for Cooperative Control with Regenerative Brake[C]//SAE2007Word Congress.Detroit, USA: SAEPaper,2007-01-0868.
[125] Hoon Yeo, Sungho Hwang, Hyunsoo Kim. Regenerative braking algorithm for a hybridelectric vehicle with CVT ratio control [J].Proceedings of the Institution of MechanicalEngineers,2006,220(11):1589-1600.
[126]杨阳，杨文辉，杨亚联，等. ISG混合动力再生制动系统压力协调控制策略[J].重庆大学学报（自然科学版）.2009,32(5):493-498.
[127]李国强，赵伟丽，贾小军，刘文江.自适应动态寻优控制系统仿真研究[J].现代电子技术.2009(02):76-78.
[128]王纪森，杨旭东.汽车防抱制动系统的自寻最优控制[J].汽车工程，2004，26（3）：299-301.
[129]武超，段建民，于涌川.气压ABS的模糊自寻优控制器设计与硬件在环验证[J].汽车工程.2010,32(11):899-992.
[130] Chen Wenhua，Donald J Balance，Peter J Gawthrop. Optimal control of nonlinear systems:A predictive control approach [J]. Automatica,2003,39(4):633-641.
[131]玄光男，周根贵等.遗传算法与工程优化[M].北京：清华大学出版社，2004.
[132]余卓平，高晓杰，张立军.用于车辆稳定性控制的直接横摆力矩及车轮变滑移率联合控制研究[J].汽车工程.2006，28(9):844-848.
[133]刘翔宇,陈无畏.基于DYC和ABS分层协调控制策略的ESP仿真[J].农业机械学报.2009，40（4）：1-6.
[134]皮大伟,陈南，张丙军.基于主动制动的车辆稳定性系统最优控制策略[J]2009，40（11）：1-6.
[135]赵伟.汽车动力学稳定性横摆力矩和主动转向联合控制策略的仿真研究[D].西安：长安大学，2008.
[136]李彬，喻凡.车辆横摆稳定性的模糊控制[J].上海交通大学学报.2008，42（6）：900-904.
[137] Kenneth R Buckholtz. Use of Fuzzy Logic in Wheel Slip Assignment–Part I: Yaw RateControl[c]. SAE2002World Congress,Detroit, Michigan,USA.2002-01-1221.
[138] Kenneth R Buckholtz. Use of Fuzzy Logic in Wheel Slip Assignment Part II: Yaw RateControl with Sideslip Angle Limitation[C]. SAE2002World Congress,Detroit,Michigan,USA.2002-01-1220.
[139] B L Boada, M J L Boada, V Díaz. Fuzzy-logic applied to yaw moment control for vehiclestability[J]. Vehicle System Dynamics.2005,43(10):753-770.
[140] Farzad Tahami, Shahrokh Farhangi, Reza Kazemi. A Fuzzy Logic Direct Yaw-MomentControl System for All-Wheel-Drive Electric Vehicles[J]. Vehicle System Dynamics.2004,41(3):203-221.
[141] B Li, F Yu. Design of a vehicle lateral stability control system via a fuzzy logic controlapproach [J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal ofAutomobile Engineering.2010,224(D3):313-326.
[142]李建秋，田光宇，卢青春，等.利用V型开发模式研制燃料电池混合动力客车的整车控制器[J].机械工程学报.2005，41(12):30-36.
[143]戴海峰，魏学哲，孙泽昌. V-模式及其在汽车电子系统开发中的应用[J].机电一体化.2006,6:20-24.
[144]朱庆林，王庆年，曾小华，等.基于V模式的混合动力汽车多能源动力总成控制器开发平台[J].吉林大学学报（工学版）.2007,37(6):1242-1246.
[145]秦大同，杨阳，詹迅，等. ISG混合动力再生制动系统硬件在环仿真[J].重庆大学学报(自然科学学报).2006,29(3):1-5.
[146]马培蓓，吴进华，纪军，等. dSPACE实时仿真平台软件环境及应用[J].系统仿真学报.16(4):667-670.
[147]张平平.并联式混合动力汽车控制策略的研究[D].合肥：合肥工业大学，2009.
[148]聂保钱，赵辉，张德成，等. HEV半实物仿真测试平台的设计[J].汽车工程.2008,30(3):215-218.
[149]张建.混合动力公交车整车控制器的研究与开发[D].合肥：合肥工业大学，2011.
[150]罗禹贡，杨殿阁，李孟海，等.并联式混合动力汽车（PHEV）动态协调控制方法硬件在环仿真[J].机械工程学报.2008,44(5):80-85.
[151]韦作高，刘振军，叶明，等.基于dSPACE的混合动力实验台系统开发研究[J].重庆交通大学学报（自然科学版）.2008，27（3）：470-473.
[2]何洪文，祝嘉光，李剑.混合动力汽车技术发展与现状[J].车辆与动力技术.2004，02：50-55.
[3]张兴业.世界汽车工业新的技术革命[J].山东交通学院学报.2007，15(1):1-7.
[4] Wolfram Buschhaus，Larry R．Brandedburg，Ross M．Stuntz．Hybrid electric vehicledevelopment at Ford． The15th International Electric Vehicle Symposium andExposition．Brussels，Belgium,1998．
[5] TOYOTA Motor Corporation. Development of electric motors for the Toyota hybrid vehicle“PRIUS”．The16th International Electric Vehicle Symposium and Exposition．Beijing，China,1999．
[6]徐汉章，罗慧超.混合动力技术进展及相关建议[J].交通节能与环保.2007，01：15-17.
[7]甑子健实现“三纵三横”关键技术突破，科技创新带动我国新能源汽车战略性新兴产业形成[J].中国科技财富.2011,26-28.
[8]吴憩棠《.十二五》“863计划”电动汽车重大项目已启动[J].新能源汽车.2011，22(02):14-17.
[9]刑伟岩，宋振宽，周雅夫.混合动力电动汽车实现商品化的关键因素[J].汽车工业研究.2002，09：14-16.
[10]李鹏. ISG型轻度混合动力汽车系统概述[J].上海汽车.2007，03：3-6.
[11]徐乔. B-ISG混合动力汽车[J].汽车与配件.2006，27(13):37-39.
[12]朱喆.车用BSG系统简介[J].汽车维修.2011，4:46-47.
[13]李振磊，林逸，龚旭.基于Star t-Stop技术的微混轿车仿真及试验研究[J].中国机械工程.2010，21(01):110-113.
[14]叶先军，赵韩，张炳力，等. BSG混合动力轿车动力系统参数设计及试验研究[J].汽车技术.2008，6:24-27.
[15]曹占国. ISG混合动力车转矩控制策略及前向式Simulink建模仿真[D].镇江：江苏大学，2010.
[16]胡洪祥.驱动工况的ISG型混合动力汽车控制策略研究[D].重庆：重庆大学，2006.
[17]王峰，冒晓建，卓斌. ISG并联混合动力轿车最优转矩分配策略[J].重庆大学学报.2008，31(05):499-504.
[18] Sun Hui, Jiang Ji-hai, Wang Xin. Torque control strategy for a parallel hydraulic hybridvehicle [J]. Journal of Terramechanics.2009,46(6):259-265.
[19]彭栋,殷承良,张建武.混合动力汽车制动力矩动态分配控制策略研究[J].系统仿真学报,2007，19（22）：5254-5259.
[20] Xiao Wenyong, Wang Feng, Zhuo Bin. Regenerative Braking Algorithm for an ISG HEVBased on Regenerative Torque Optimization[J]. Journal of ShangHai JiaotongUniversity(Science),2008，Vol.13No.2:193-200
[21]郭金刚，王军平，曹秉刚.电动车最大化能量回收制动力分配策略研究[J].西安交通大学学报.2008，42(05):607-611.
[22]何仁，陈庆樟.汽车制动能量再生系统制动力分配研究[J].兵工学报.2009，30(02):205-208.
[23] Gao Y, Ehsani M. Electronic Braking System of EV-Integration of Regenerative Braking,Automatic Braking Force Control and ABS [J]. SAE Paper2002-01-2478.
[24]张元才，余卓平，徐乐，等.基于制动意图的电动汽车复合制动系统制动力分配策略研究[J].汽车工程.2009，31(03):244-249.
[25]童毅，张俊智，欧阳明高.混合动力汽车扭矩管理策略[J].清华大学学报(自然科学版).2003，43(08):1134-1137.
[26]于秀敏，曹珊，李君，等.混合动力汽车控制策略的研究现状及其发展趋势[J].机械工程学报,2006,42(11):10-16.
[27]田甜，郑燕萍，蒋元广，戴能红，汪涵.混合动力汽车控制策略优化研究综述[J].公路与汽运.2010，05：1-4.
[28]张承慧，李珂，崔纳新，等.混合动力汽车能量及驱动系统的关键控制问题研究进展[J].山东大学学报（工学版）.2011，41(5):1-8.
[29] SALMASI F R. Control strategies for hybrid electric vehicles: evolution, classification，comparison, and future trends [J]. IEEE Transactions on Vehicular Technology，2007，56(5):2393-2404．
[30] Kimura A, Abe T, Sasaki S. Drive force control of a parallel-series hybrid system [J]. JSAEReview.1999,20(3):337-341.
[31] Ehsani M, Gao Yimin, Butler K L. Application of electrically peaking hybrid (ELPH)propulsion system to a full-size passenger car with simulated design verification [J]. IEEETransactions on Vehicular Technology,1999,48(6):1779-1787.
[32] Rahman Z, Butler K L, Ehsani M. A comparison study between two parallel hybrid controlConcepts[J]. SAE Paper2000-01-0994.
[33] Chan-Chiao Lin, Jun-Mo Kang, Grizzle J W, et al. Energy Management Strategy for aParallel Hybrid Electric Truck[C].Proceedings of the American Control Conference.Arlington: VA, USA,2001.
[34] Chan-Chiao Lin, Huei Peng, Soonil Jeon, et al. Control of a Hybrid Electric Truck Basedon Driving Pattern Recognition [C].Proceeding of the AVEC.2002.
[35]张欣，李国岫，宋建锋，等.并联式混合动力汽车多能源动力总成控制单元的研究与开发[J].高技术通讯.2003，13（2）：92-96.
[36] ADVISOR2002software, http://www.ctts.nrel.gov/.
[37] National Renewable Energy Laboratory. ADVISOR Documentation. Golden Co.[Online].Available: http://www.ctts.nrel.gov/analysis/.
[38] Johnson V H, Wipke K B, Rausen D J. HEV control strategy for real-time optimization offuel economy and emissions [J]. SAE Paper2000-01-1543.
[39] Paganelli G, Guerra T M, Delprat S, et al. Simulation and assessment of power controlstrategies for a parallel hybrid car[J]. Proc Institution Mechanical Engineers, Part D: Journalof Automobile Engineering.2000,214(7):705-717.
[40] Wagener A., Korner C., Seger P. et al. Cost function based adaptive energy management inhybrid drivetrains[C]. Proceedings of the18th International Electric Vehicle Symposium.Berlin,Germany,2001.
[41] Paganelli G, Ercole G, Brahma A, et al. General supervisory control policy for the energyoptimization of charge-sustaining hybrid electric vehicles[J]. JSAE Review.2001,22(4):511-518.
[42] Paganelli G, Tateno M. Control development for a hybrid-electric sport-utility vehicle:strategy, implementation and field test results[C]. Proceeding of the American ControlConference.Arlington, VA, USA,2001,5064-5069
[43]胡红斐，罗玉涛，赵克刚.基于瞬时优化的HEV控制策略[J].交通与计算机.2006,24(1)：130-136.
[44]朱诗顺，任永乐，张月滨等.基于电量平衡的串联混合动力汽车瞬时优化控制[J].中国机械工程，2008.03
[45] Galdi V, Ippolito L, Piccolo A, et al. Multi-objective optimization for fuel economy andemissions of HEV using the goal-attainment method. Proc of the18th International ElectricVehicle Symposium, Berlin, Germany,2001
[46] Delprat S, Guerra T M, Rimaux J. Optimal control of a parallel powertrfrom globaloptimization to real time control strategy. Proc of the18th International Electric VehicleSymposium, Berlin, Germany,2001
[47]胡红斐，黄向东，罗玉涛，等.并联式混合动力电动汽车全局优化控制[J].华南理工大学学报，2006，(4):28-32.
[48]房立存，秦世引.混合动力电动汽车最优控制与实例仿真[J].系统仿真学报，2007,19(1):110-114.
[49]浦金欢.混合动力汽车能量优化管理与控制策略研究[D].上海：上海交通大学，2004.
[50] Schouten Niels J，Salman Mutasim A，Kheir Naim A. Fuzzy Logic Control for ParallelHybrid Vehicles [J]. IEEE Transactions on Control Systems Technology.2002，10(3):460-468．
[51] N J Schouten, M A Salman, N A Kheir, Energy management strategies for parallel hybridvehicles using fuzzy logic[J]. Control Engineering Practice.2003,11(2):171-177.
[52]陈健，李彦，吴亚祥，廖荣福.混合动力电动汽车模糊逻辑控制策略的研究与仿真[J].汽车工程,2006,28(4):322-326.
[53] Kheir N A, Salman M A, Schouten N J. Emissions and fuel economy trade-off for hybridvehicles using fuzzy logic[J]. Mathematics And Computers In Simulation,2004,66(2):155-172.
[54]胡洪祥，秦大同，舒红，杨亚联，丁李辉. ISG型混合动力汽车模糊控制策略及仿真[J].重庆大学学报（自然科学版）.2006，29(11):1-5.
[55] QUN Zeng,Juhua Huang. The design and simulation of fuzzy logic controller for parallelhybrid electric vehicles[C]//2007Proceedings of the IEEE International Conference onAutomation and Logistics.2007:8-18.
[56] Tomaz Katrasnik. Hybridization of powertrain and downsizing of IC engine-A way to reducefuel consumption and pollutant emissions-Part1[J]. Energy Conversion andManagement.2007,48(5):1411–1423.
[57]姚明亮，秦大同，胡明辉，叶心.基于模糊逻辑控制策略的混合动力汽车仿真研究[J].汽车工程，2007,29(11):934-937.
[58] H Zhong, F Wang,G-Q Ao, et al. An optimal torque distribution strategy for an integratedstarter—generator parallel hybrid electric vehicle based on fuzzy logic control [J].Proceedings of the Institution of Mechanical Engineers, Part D: Journal of AutomobileEngineering.2008,222(1):79-92.
[59] CHEN Jian, LI Yan, WANG Jian. Simultaneous optimisation of fuel consumption andemissions for a parallel hybrid electric SUV using fuzzy logic control [J]. InternationalJournal Of Vehicle Design,2008,46(2):204-218.
[60] Ferreira AA, Pomilio JA, Spiazzi G, Slva L D. Energy management fuzzy logic supervisoryfor electric vehicle power supplies system [J]. IEEE Transactions on Power Electronics,2008,23(1):107~115.
[61]吴晓刚，王旭东，毛亮. ISG型混合动力汽车能量管理模糊控制的研究[J].汽车工程.2011，33(07):558-562.
[62]白中浩,王耀南,曹立波,等.混合动力电动汽车能量自适应模糊控制研究[J].汽车工程,2005,27(4):389-391.
[63] WU Jian, ZHANG Chenghui, CUI Naxin. Fuzzy energy management strategy of parallelhybrid electric vehicle based on particle swarm optimization [J]. Control and Decision,2008,23(1):46-50.
[64] Amir Poursamad, Morteza Montazeri. Design of genetic-fuzzy control strategy for parallelhybrid electric vehicles[J]. Control Engineering Practice.2008,16(7):861-873.
[65] Mohebbi M,Charkhgard M,Farrokhi M.Optimal neuro-fuzzy control of parallel hybridelectric vehicles[C]//2005IEEE Conference on Vehicle Power and Propulsion.2005:252-256.
[66]钱立军,袭著永，赵韩.基于模糊神经网络的混合动力汽车控制策略仿真[J].系统仿真学报,2006,18(5):1384～1387.
[67] Poursamad A, Montazeri M. Design of genetic-fuzzy control strategy for parallel hybridelectric vehicles [J]. Control Engineering Practice,2008,16(7):861-873
[68]叶先军，赵韩，张炳力最佳工作点ISG混合动力汽车性能优化[J].应用科学学报.2008，(26)5:541-546.
[69]郭金刚，王军平，曹秉刚.电动车最大化能量回收制动力分配策略研究[J].西安交通大学学报.2008，42(05):607-611.
[70]周磊，罗禹贡，杨殿阁，等.基于滑移率试探的电动车辆制动控制策略[J].清华大学学报（自然科学版）.2008，48(5):883-887.
[71]彭栋.混合动力汽车制动能量回收与ABS集成控制研究[D].上海：上海交通大学，2007.
[72]张建龙，殷承良，张建武，等.混合动力汽车机电复合制动控制系统研究[J].系统仿真学报，2009，21（16）：5169-5174.
[73]彭栋,殷承良,张建武.混合动力汽车制动力矩动态分配控制策略研究[J].系统仿真学报,2007，19（22）：5254-5259.
[74] D. Peng, Y. Zhang, C.-L. Yin and J.-W. Zhang. Combined control of a regenerative brakingand antilock braking system for hybrid electric vehicles [J]. International Journal ofAutomotive Technology.2008,9(6):749-757.
[75]何仁，陈庆樟.汽车制动能量再生系统制动力分配研究[J].兵工学报.2009，30(02):205-208.
[76] F Wang, B Zhuo. Regenerative braking strategy for hybrid electric vehicles based onregenerative torque optimization control[J]. Proceedings of the Institution of MechanicalEngineers, Part D: Journal of Automobile Engineering.2008,222(4):499-513.
[77]李鑫.并联式Plug-in HEV整车控制及能量管理系统研究[D].合肥：合肥工业大学.2010.
[78]陈庆樟，何仁，赵连生.汽车能量再生制动防抱死集成控制方法研究[J].中国机械工程.2009，20（2）：245-247.
[79]周磊，罗禹贡，李克强，等.电动汽车回馈制动与防抱死制动集成控制[J].清华大学学报（自然科学版），2009，49（5）：728-732.
[80] T K Bera, K Bhattacharya, A K Samantaray. Bond graph model-based evaluation of a slidingmode controller for a combined regenerative and antilock braking system[J]. Proceedings ofthe Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering.2011,225(07):918-934.
[81] J-Z Zhang, X Chen, P-J Zhang. Integrated control of braking energy regeneration andpneumatic anti-lock braking[J]. Proceedings of the Institution of Mechanical Engineers, PartD: Journal of Automobile Engineering.2010,224(5):587-610.
[82] Zhang J，Kong D，Chen L，et al. Optimization of control strategy for regenerative braking ofan electrified bus equipped with an anti-lock braking system [J]. Proc. IMechE Part D: J.Automobile Engineering,2011，published online19October2011,1-13.
[83]张勇.基于主动制动的汽车稳定性控制系统开发研究[D].上海：上海交通大学，2007.
[84]赵国柱，杨正林，魏民祥，等.电动微型客车的机电复合制动稳定性分析[J]汽车工程2006，28（7）：681-685.
[85] Sakai, S. and Hori, Y. Advanced motion control of electric vehicle with fast minor feedbackloops: basic experiments using the4-wheel motored EV “UOT Electric March II”[J]. JSAEReview.2001,22(4):527-536.
[86]张建龙，张建武，袁明，殷承良.混合动力汽车操纵稳定性模糊控制仿真研究[J].系统仿真学报.2009，21（20）：6600-6607.
[87] Donghyun Kim, Hyunsoo Kim. Vehicle stability control with regenerative braking andelectronic brake force distribution for a four-wheel drive hybrid electric vehicle [J].Proceedings of the Institution of Mechanical Engineers, Part D: Journal of AutomobileEngineering.2006220(6):683-693
[88] D-H Kim, J-M Kim, S-H Hwang, et al. Optimal brake torque distribution for a Four wheeldrive hybrid electric vehicle stability enhancement. Proceedings of the Institution ofMechanical Engineers, Part D: Journal of Automobile Engineering2007221(11):1357-1366.
[89] Leo Gilles. ESC与再生型制动在混合动力车上的集成[J].汽车与配件.2011，14：27-29.
[90]李卫民.混合动力汽车控制系统与能量管理策略研究[D].上海：上海交通大学，2008.
[91]黄伟.基于CVT的四轮驱动混合动力汽车传动控制策略研究[D].长沙：湖南大学，2008.
[92]朱阳，赵治国.混合动力汽车发动机建模方法的研究[J].上海汽车.2009,6:9-12.
[93] Johnson V H, Wipke K B, Rausen D J. HEV control strategy for real-time optimization offuel economy and emissions. SAE2000-01-1543.
[94]钱立军.混合动力电动汽车控制策略与传动系的优化匹配研究[D].合肥：合肥工业大学，2004.
[95]李贵海.电池SOC估算策略研究[D].杭州：浙江大学，2006.
[96]刘惟信.汽车设计.北京：清华大学出版社，2001.
[97]余志生.汽车理论[M].3版.北京:机械工业出版社，2004.
[98]葛安林、李焕松、武文治等.动态三参数最佳换档规律的研究.汽车工程.1992（4）.
[99]张俊智、王丽芳、葛安林.自动换档规律的研究.机械工程学报.1999（8）
[100]郭孔辉，侯永平.轮胎非稳态转向特性半经验模型[J].汽车工程.1999,21(3):129-133.
[101] Pacejka, H. B., Tire and Vehicle Dynamics, Society of Automotive Engineers andButterworth-Heinemann, Oxford,2002.
[102]安丽华.汽车电子稳定性程序（ESP）控制方法及联合仿真研究[D].南京：南京理工大学，2009.
[103]庄晔.轮胎高速侧向试验方法与数据处理[D].长春：吉林大学，2001年．
[104]秦大同，邓涛，杨阳，等.基于前向建模的ISG型CVT混合动力系统再生制动仿真研究[J].中国机械工程.2009,19(5):618-624.
[105]黄妙华，喻厚宇.采用CVT的并联HEV驱动系统最佳工作点的确定[J].武汉理工大学学报:信息与管理工程版,2004,26(3):168-172.
[106]陈继光. Matlab与自适应神经网络模糊推理系统[M].济南：山东省地图出版社，2002.
[107] Jang, J.-S. R., ANFIS: Adaptive-Network-based Fuzzy Inference Systems [J]. IEEETransactions on Systems, Man, and Cybernetics.1993,23(3):665-685.
[108]孙增圻，邓志东，张再兴.智能控制理论及技术[M].北京：清华大学出版社.
[109]方锡邦.汽车检测技术与设备[M].北京：人民交通出版社，2005.
[110]秦大同，叶心，胡明辉，等. ISG型中度混合动力汽车驱动工况控制策略优化[J].机械工程学报.2010,46(12):86-92.
[111]刘传李，贾东红，杨中乐.内燃机节油率计算的探讨[J].内燃机工程.1996，17(1):52-58.
[112] Li J, Zhang J W, Yu F. An investigation into fuzzy controller for anti-lock braking systembased on road autonomous identification [R].SAE Technical Paper2001-01-0599.
[113] Zhou Lei, Luo Yugong, Yang Diange, et al. A Novel Brake Control Strategy for ElectricVehicles Based on Slip Trial Method[C]//Proceedings of the2007IEEE InternationalConference on Vehicular Electronics and Safety, Beijing, china,2007：225-230.
[114] Okan TUR, Ozgur USTUN, R. Nejat TUNCAY. An Introduction to Regenerative Brakingof Electric Vehicles as Anti-Lock Braking System[C]//Proceedings of the2007IEEEIntelligent Vehicles Symposium. Istanbul, Turkey, June13-15,2007:944-948.
[115]齐志权，刘昭度，时开斌，等.基于汽车ABS/ASR/ACC集成化系统的ABS参考车速确定方法的研究[J].汽车工程.2003，25(6):617-620.
[116]刘国福.基于滑移率的车辆防抱死制动系统的研究[D].长沙：国防科学技术大学，2007.
[117]叶先军，赵韩.基于路面识别的HEV制动系统控制算法研究[J].系统仿真学报，2010，22(12):2990-2994.
[118]王纪森，杨旭东.汽车防抱制动系统的自寻最优控制[J].汽车工程，2004，26（3）：299-301.
[119]沈俊，宋健，王会义.用小波分析获取路面最佳滑移率的研究[J].农业机械学报.2007，38(7):29-31.
[120]孙仁云，李治.基于变路面SBC最佳滑移率的研究[J].中国机械工程.2008,19(4):481-485.
[121]张代胜，李伟.基于滑移率的汽车防抱模糊控制方法与仿真[J].农业机械学报.2002，33(2):28-31.
[122] Yimin Gao, Mehrdad Ehsani. Electronic braking system of EV and HEV-Integration ofregenerative braking, automatic braking force control and ABS[C]//Future TransportationTechnology Conference.California,USA:SAE,2001:2001-01-2478.
[123] Nakamura E,Soga M,Sa kaiki hiroA et al. Development of Electronically Controlled BrakeSystem for Hybrid Vehicle[J]. SAE Paper,2002-01-0300.
[124] Yasushi Aoki, Kenji Suzuki, Hiroshi Nakano, et al.Development of Hydraulic Servo BrakeSystem for Cooperative Control with Regenerative Brake[C]//SAE2007Word Congress.Detroit, USA: SAEPaper,2007-01-0868.
[125] Hoon Yeo, Sungho Hwang, Hyunsoo Kim. Regenerative braking algorithm for a hybridelectric vehicle with CVT ratio control [J].Proceedings of the Institution of MechanicalEngineers,2006,220(11):1589-1600.
[126]杨阳，杨文辉，杨亚联，等. ISG混合动力再生制动系统压力协调控制策略[J].重庆大学学报（自然科学版）.2009,32(5):493-498.
[127]李国强，赵伟丽，贾小军，刘文江.自适应动态寻优控制系统仿真研究[J].现代电子技术.2009(02):76-78.
[128]王纪森，杨旭东.汽车防抱制动系统的自寻最优控制[J].汽车工程，2004，26（3）：299-301.
[129]武超，段建民，于涌川.气压ABS的模糊自寻优控制器设计与硬件在环验证[J].汽车工程.2010,32(11):899-992.
[130] Chen Wenhua，Donald J Balance，Peter J Gawthrop. Optimal control of nonlinear systems:A predictive control approach [J]. Automatica,2003,39(4):633-641.
[131]玄光男，周根贵等.遗传算法与工程优化[M].北京：清华大学出版社，2004.
[132]余卓平，高晓杰，张立军.用于车辆稳定性控制的直接横摆力矩及车轮变滑移率联合控制研究[J].汽车工程.2006，28(9):844-848.
[133]刘翔宇,陈无畏.基于DYC和ABS分层协调控制策略的ESP仿真[J].农业机械学报.2009，40（4）：1-6.
[134]皮大伟,陈南，张丙军.基于主动制动的车辆稳定性系统最优控制策略[J]2009，40（11）：1-6.
[135]赵伟.汽车动力学稳定性横摆力矩和主动转向联合控制策略的仿真研究[D].西安：长安大学，2008.
[136]李彬，喻凡.车辆横摆稳定性的模糊控制[J].上海交通大学学报.2008，42（6）：900-904.
[137] Kenneth R Buckholtz. Use of Fuzzy Logic in Wheel Slip Assignment–Part I: Yaw RateControl[c]. SAE2002World Congress,Detroit, Michigan,USA.2002-01-1221.
[138] Kenneth R Buckholtz. Use of Fuzzy Logic in Wheel Slip Assignment Part II: Yaw RateControl with Sideslip Angle Limitation[C]. SAE2002World Congress,Detroit,Michigan,USA.2002-01-1220.
[139] B L Boada, M J L Boada, V Díaz. Fuzzy-logic applied to yaw moment control for vehiclestability[J]. Vehicle System Dynamics.2005,43(10):753-770.
[140] Farzad Tahami, Shahrokh Farhangi, Reza Kazemi. A Fuzzy Logic Direct Yaw-MomentControl System for All-Wheel-Drive Electric Vehicles[J]. Vehicle System Dynamics.2004,41(3):203-221.
[141] B Li, F Yu. Design of a vehicle lateral stability control system via a fuzzy logic controlapproach [J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal ofAutomobile Engineering.2010,224(D3):313-326.
[142]李建秋，田光宇，卢青春，等.利用V型开发模式研制燃料电池混合动力客车的整车控制器[J].机械工程学报.2005，41(12):30-36.
[143]戴海峰，魏学哲，孙泽昌. V-模式及其在汽车电子系统开发中的应用[J].机电一体化.2006,6:20-24.
[144]朱庆林，王庆年，曾小华，等.基于V模式的混合动力汽车多能源动力总成控制器开发平台[J].吉林大学学报（工学版）.2007,37(6):1242-1246.
[145]秦大同，杨阳，詹迅，等. ISG混合动力再生制动系统硬件在环仿真[J].重庆大学学报(自然科学学报).2006,29(3):1-5.
[146]马培蓓，吴进华，纪军，等. dSPACE实时仿真平台软件环境及应用[J].系统仿真学报.16(4):667-670.
[147]张平平.并联式混合动力汽车控制策略的研究[D].合肥：合肥工业大学，2009.
[148]聂保钱，赵辉，张德成，等. HEV半实物仿真测试平台的设计[J].汽车工程.2008,30(3):215-218.
[149]张建.混合动力公交车整车控制器的研究与开发[D].合肥：合肥工业大学，2011.
[150]罗禹贡，杨殿阁，李孟海，等.并联式混合动力汽车（PHEV）动态协调控制方法硬件在环仿真[J].机械工程学报.2008,44(5):80-85.
[151]韦作高，刘振军，叶明，等.基于dSPACE的混合动力实验台系统开发研究[J].重庆交通大学学报（自然科学版）.2008，27（3）：470-473.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |