CN111891111B8 - 基于mcpso的混合动力汽车区间ii型模糊逻辑自适应控制方法 - Google Patents

基于mcpso的混合动力汽车区间ii型模糊逻辑自适应控制方法 Download PDF

Info

Publication number
CN111891111B8
CN111891111B8 CN202010361996.4A CN202010361996A CN111891111B8 CN 111891111 B8 CN111891111 B8 CN 111891111B8 CN 202010361996 A CN202010361996 A CN 202010361996A CN 111891111 B8 CN111891111 B8 CN 111891111B8
Authority
CN
China
Prior art keywords
type
hybrid electric
interval
mcpso
fuzzy
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010361996.4A
Other languages
English (en)
Other versions
CN111891111B (zh
CN111891111A (zh
Inventor
周健豪
张仁鹏
顾城
薛四伍
薛源
廖宇晖
刘军
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Nanjing University of Aeronautics and Astronautics
Original Assignee
Nanjing University of Aeronautics and Astronautics
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing University of Aeronautics and Astronautics filed Critical Nanjing University of Aeronautics and Astronautics
Priority to CN202010361996.4A priority Critical patent/CN111891111B8/zh
Publication of CN111891111A publication Critical patent/CN111891111A/zh
Publication of CN111891111B publication Critical patent/CN111891111B/zh
Application granted granted Critical
Publication of CN111891111B8 publication Critical patent/CN111891111B8/zh
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W20/00—Control systems specially adapted for hybrid vehicles
    • B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
    • B60W20/15—Control strategies specially adapted for achieving a particular effect
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/24—Conjoint control of vehicle sub-units of different type or different function including control of energy storage means
    • B60W10/26—Conjoint control of vehicle sub-units of different type or different function including control of energy storage means for electrical energy, e.g. batteries or capacitors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/24—Energy storage means
    • B60W2510/242—Energy storage means for electrical energy
    • B60W2510/244—Charge state
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/06—Combustion engines, Gas turbines
    • B60W2710/0666—Engine torque
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/62—Hybrid vehicles
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84—Data processing systems or methods, management, administration

Landscapes

  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Feedback Control In General (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

本发明公开一种基于MCPSO的混合动力汽车区间II型模糊逻辑自适应控制方法，属于混合动力汽车的能量管理领域，共分为两层优化逻辑。内层是基于区间II型模糊控制，用于建立系统能量分配。外层是基于多群体协同进化粒子群算法在线优化II型模糊集伸缩因子，用于区间II型模糊控制规则的论域动态寻优。通过引入改进的粒子群算法(MCPSO)优化区间II型模糊控制器隶属度函数伸缩因子以达到II型模糊控制自适应调节能力。外层与内层相互协调，最终实现在高不确定性、非线性环境下的混合动力汽车近优能量管理控制，采用本申请，可以在实现能量管理控制策略优化的同时，能够确保混合动力汽车行驶所需的动力性能及动力模式切换的合理切换频率。
CN202010361996.4A 2020-04-30 2020-04-30 基于mcpso的混合动力汽车区间ii型模糊逻辑自适应控制方法 Active CN111891111B8 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010361996.4A CN111891111B8 (zh) 2020-04-30 2020-04-30 基于mcpso的混合动力汽车区间ii型模糊逻辑自适应控制方法

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010361996.4A CN111891111B8 (zh) 2020-04-30 2020-04-30 基于mcpso的混合动力汽车区间ii型模糊逻辑自适应控制方法

Publications (3)

Publication Number Publication Date
CN111891111A CN111891111A (zh) 2020-11-06
CN111891111B CN111891111B (zh) 2021-11-23
CN111891111B8 true CN111891111B8 (zh) 2021-12-24

Family

ID=73207355

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010361996.4A Active CN111891111B8 (zh) 2020-04-30 2020-04-30 基于mcpso的混合动力汽车区间ii型模糊逻辑自适应控制方法

Country Status (1)

Country Link
CN (1) CN111891111B8 (zh)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112373458B (zh) * 2020-11-26 2021-10-08 同济大学 一种基于自适应模糊控制的混合动力汽车能量管理方法
CN112498332B (zh) * 2020-11-27 2023-02-28 重庆邮电大学 一种并联式混合动力汽车模糊自适应能量管理控制方法
CN112886036B (zh) * 2021-01-08 2022-07-12 南京航空航天大学 一种基于改进灰狼优化的pemfc供气系统控制策略
CN117318562B (zh) * 2023-10-24 2024-05-03 北京皓德创业科技有限公司 一种节能电机曲线设计方法

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102501737A (zh) * 2011-11-02 2012-06-20 青岛大学 一种车辆半主动悬架系统智能粒子群模糊混合控制方法
CN106408084A (zh) * 2016-09-09 2017-02-15 山东建筑大学 一种知识与数据混合驱动的二型模糊神经网络设计方法
CN106786696A (zh) * 2016-12-29 2017-05-31 东南大学 一种基于模糊逻辑控制器的混合储能系统控制方法
CN107161140A (zh) * 2017-05-09 2017-09-15 南京航空航天大学 一种插电式混合动力汽车系统及其能量控制方法
CN107272419A (zh) * 2017-08-01 2017-10-20 成都雅骏新能源汽车科技股份有限公司 一种基于改进pso的驾驶员自适应方向控制方法
CN108001447A (zh) * 2017-11-23 2018-05-08 江苏大学 一种智能车辆路径跟踪前轮转角补偿控制方法
CN108985440A (zh) * 2018-09-05 2018-12-11 河南工业大学 区间二型直觉模糊随机向量函数连接神经网络设计方法
CN110111367A (zh) * 2019-05-07 2019-08-09 深圳大学 模糊模型粒子滤波方法、装置、设备及存储介质

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102501737A (zh) * 2011-11-02 2012-06-20 青岛大学 一种车辆半主动悬架系统智能粒子群模糊混合控制方法
CN106408084A (zh) * 2016-09-09 2017-02-15 山东建筑大学 一种知识与数据混合驱动的二型模糊神经网络设计方法
CN106786696A (zh) * 2016-12-29 2017-05-31 东南大学 一种基于模糊逻辑控制器的混合储能系统控制方法
CN107161140A (zh) * 2017-05-09 2017-09-15 南京航空航天大学 一种插电式混合动力汽车系统及其能量控制方法
CN107272419A (zh) * 2017-08-01 2017-10-20 成都雅骏新能源汽车科技股份有限公司 一种基于改进pso的驾驶员自适应方向控制方法
CN108001447A (zh) * 2017-11-23 2018-05-08 江苏大学 一种智能车辆路径跟踪前轮转角补偿控制方法
CN108985440A (zh) * 2018-09-05 2018-12-11 河南工业大学 区间二型直觉模糊随机向量函数连接神经网络设计方法
CN110111367A (zh) * 2019-05-07 2019-08-09 深圳大学 模糊模型粒子滤波方法、装置、设备及存储介质

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
"区间Ⅱ型变论域自适应模糊逻辑控制器";赵国亮、张永立、李洪兴;《大连理工大学学报》;20121130;第52卷(第6期);914-920 *
"双源混合动力系统能量管理策略优化;曾甜、汤泽波、姚堤照、谢长君;《河南科技大学学报（自然科学版）》;20191231;第40卷(第6期);24-31 *
"基于粒子群优化的混合动力客车模糊控制策略研究";尹安东;《２ ０ １０ 中国汽车工程学会年会论文集》;20100715;276-280 *
"新型多群体协同进化粒子群优化算法";牛奔、李丽、楚湘华;《计算机工程与应用》;20090401;第45卷(第3期);28-29 *

Also Published As

Publication number Publication date
CN111891111B (zh) 2021-11-23
CN111891111A (zh) 2020-11-06

Similar Documents

Publication Publication Date Title
CN111891111B8 (zh) 基于mcpso的混合动力汽车区间ii型模糊逻辑自适应控制方法
Eckert et al. Electric vehicle powertrain and fuzzy control multi-objective optimization, considering dual hybrid energy storage systems
Dawei et al. Intelligent fuzzy energy management research for a uniaxial parallel hybrid electric vehicle
Geng et al. Simulation research on a novel control strategy for fuel cell extended-range vehicles
Ming et al. Energy management strategy of a plug-in parallel hybrid electric vehicle using fuzzy control
Yang et al. Research on driving control strategy and Fuzzy logic optimization of a novel mechatronics-electro-hydraulic power coupling electric vehicle
Singh et al. Fuzzy logic and Elman neural network tuned energy management strategies for a power-split HEVs
CN104972918A (zh) 燃料电池混合动力有轨电车多动力源自适应能量管理系统
CN112455420B (zh) 一种基于模糊神经网络的混合动力系统能量控制方法
Sun et al. System power loss optimization of electric vehicle driven by front and rear induction motors
CN104442798B (zh) 混合动力汽车在串联工作模式下的串联发电控制方法
Wang et al. Optimal component sizing of a four-wheel independently-actuated electric vehicle with a real-time torque distribution strategy
Song et al. Study on the Composite ABS Control of Vehicles with Four Electric Wheels.
Taghavipour et al. Implementation of an optimal control strategy for a hydraulic hybrid vehicle using CMAC and RBF networks
Yang et al. Real‐time torque‐distribution strategy for a pure electric vehicle with multiple traction motors by particle swarm optimisation
Gao et al. Torque allocation of four-wheel drive EVs considering tire slip energy
Liu et al. Deep Reinforcement Learning-Based Energy Management Strategy for Hybrid Electric Agriculture Tractor
Zhai et al. Investigation of energy efficient power coupling steering system for dual motors drive high speed tracked vehicle
Shi et al. Research on control strategy of electric vehicle under braking state based on fuzzy control
Wang et al. Energy management for a series-parallel plug-in hybrid electric truck based on reinforcement learning
Oubelaid et al. Artificial Neural Networks-Based Torque Distribution for Riding Comfort Improvement of Hybrid Electric Vehicles
Andriniriniaimalaza et al. Efficiency Optimization Approaches for Hybrid Electric Vehicles
Ren et al. A Fuzzy Logical Threshold Strategy for Optimal Fuel Efficiency of Diesel Engine Based Series Heterogeneous Multi-Energy Drive System
Bhardwaj et al. Study on Fuel Cell Vehicle Braking System Selection and Simulation
Zhang et al. A real-time operational management strategy for vehicular hybrid propulsion system based on GRNN-AECMS

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CI03 Correction of invention patent

Correction item: Inventor

Correct: Zhou Jianhao|Zhang renpeng|Gu Cheng|Xue Siwu|Xue Yuan|Liao Yuhui|Liu Jun

False: Zhou Jianhao|Zhang renpeng|Gu Cheng|Xue Siwu|Xue Yuan|Liao Yuhui|Liu Jun

Number: 48-01

Page: The title page

Volume: 37

Correction item: Inventor

Correct: Zhou Jianhao|Zhang renpeng|Gu Cheng|Xue Siwu|Xue Yuan|Liao Yuhui|Liu Jun

False: Zhou Jianhao|Zhang renpeng|Gu Cheng|Xue Siwu|Xue Yuan|Liao Yuhui|Liu Jun

Number: 48-01

Volume: 37

CI03 Correction of invention patent