Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks

Li Hongliang; Zhang Guojing; Fan Ping

doi:10.16578/j.issn.1004.2539.2024.07.004

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Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks

Theory·Research | 更新时间：2024-07-22

- Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks
- Journal of Mechanical Transmission Vol. 48, Issue 7, Pages: 30-39(2024)
- 作者机构：
  
  1.内蒙古科技大学矿业与煤炭学院，内蒙古包头 014010
  2.内蒙古自治区矿业工程重点实验室，内蒙古包头 014010
  3.内蒙古自治区煤炭安全开采与利用工程技术研究中心，内蒙古包头 014010
  4.内蒙古煤炭绿色开采与绿色利用协同创新中心，内蒙古包头 014010
- 作者简介：
- 基金信息：
- DOI：10.16578/j.issn.1004.2539.2024.07.004
  CLC：
- Published：15 July 2024，
  
  Received：04 April 2023，
  
  Revised：19 May 2023，
- 稿件说明：
扫描看全文
李洪亮,张国靖,樊平.混合动力矿用卡车节能协同优化及最优实时控制综合研究[J].机械传动,2024,48(07):30-39.

Li Hongliang,Zhang Guojing,Fan Ping.Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks[J].Journal of Mechanical Transmission,2024,48(07):30-39.
李洪亮,张国靖,樊平.混合动力矿用卡车节能协同优化及最优实时控制综合研究[J].机械传动,2024,48(07):30-39. DOI： 10.16578/j.issn.1004.2539.2024.07.004.

Li Hongliang,Zhang Guojing,Fan Ping.Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks[J].Journal of Mechanical Transmission,2024,48(07):30-39. DOI： 10.16578/j.issn.1004.2539.2024.07.004.

摘要

混合动力汽车的燃油经济性很大程度上取决于系统的传动系参数和能量管理策略。然而，针对传动系参数和能量管理策略对燃油经济性优化存在交互影响的问题，以及能量管理策略实时性和全局最优性难以兼顾的问题，尚缺乏一套行之有效的实现方法。为此，以混合动力矿用卡车为研究对象，建立整车数学模型，以减少燃油消耗为目标，建立了综合考虑传动系参数与能量管理策略交互作用的协同优化模型；联合粒子群优化（Particle Swarm Optimization，PSO）算法和动态规划（Dynamic Programming，DP）算法构建双层交互式优化算法进行求解，以消除传动系参数和能量管理策略之间的交互效应，实现在对传动系参数最优化的同时完成最优能量分配。在此基础上，针对DP算法难以实现在线控制的问题，对最优传动系参数对应的DP能量管理最优解进行整合，设计了一种有效提取DP最优控制规则的方法，建立了基于最优控制规则的能量管理策略，以此来实现混合动力矿用卡车的在线控制。依据建立的传动系参数和能量管理策略协同优化及最优能量管理实时控制策略的一体化实现方法，将获得的最优传动系参数和对应的最优能量管理实时控制策略一同在Stateflow-AMESim联合仿真平台上进行仿真验证。结果表明，该方法所得到的燃油消耗结果优于单独的DP优化结果，并且与PSO-DP优化得到的结果接近程度较高，表明了该优化方法是有效、可行的。

Abstract

The fuel economy of hybrid electric vehicles largely depends on the transmission system parameters and energy management strategy. However

due to the interaction between the transmission system parameters and energy management strategies on the optimization of fuel economy

and the difficulty in balancing the real-time and global optimality of energy management strategies

there is still a lack of an effective implementation method. This study takes the hybrid electric mining truck as a research object

establishes the mathematical model of the whole vehicle

takes reducing fuel consumption as the goal

establishes a collaborative optimization model that comprehensively considers the interaction between transmission system parameters and energy management strategies

and combines particle swarm optimization (PSO) algorithm and dynamic programming (DP) algorithm to build a two-layer interactive optimization algorithm to eliminate the interaction between transmission system parameters and energy management strategies. The optimal energy distribution can be achieved while optimizing the transmission parameters. On this basis

in order to solve the problem that the DP algorithm is difficult to realize online control

the optimal solution of DP energy management corresponding to the optimal transmission parameters is integrated

an effective method to extract the optimal control rules of DP is designed

and an energy management strategy based on the optimal control rules is established to realize online control of hybrid electric mining trucks. Thus

the integrated realization method of the coordinated optimization of transmission system parameters and energy management strategy

as well as the optimal energy management real-time control strategy

is established. The obtained optimal transmission system parameters and corresponding optimal energy management real-time control strategy are simulated and verified on the Stateflow-AMESim joint simulation platform. The results show that the fuel consumption results obtained by this method are better than those obtained by DP optimization alone

and they are closer to the results obtained by PSO-DP optimization

indicating that the optimization method is effective and feasible.

关键词

混合动力矿用卡车传动系参数能量管理策略燃油经济性协同优化

Keywords

Hybrid mining truckTransmission system parameterEnergy management strategyFuel economyJoint optimization

references

ZHANG P，WU X P，DU C Q，et al.Adaptive equivalent consumption minimization strategy for hybrid heavy-duty truck based on driving condition recognition and parameter optimization［J］.Energies，2020，13（20）：5407.

郭晓勐，郭长浩，王坤玉，等.氢燃料电池卡车动力传动系统参数匹配和性能研究［J］.重型汽车，2021（4）：5-7.

GUO Xiaomeng，GUO Changhao，WANG Kunyu，et al.Research on parameter matching and performance of power transmission system of hydrogen fuel cell truck［J］.Heavy Truck，2021（4）：5-7.

ECKERT J J，BARBOSA T P，DA SILVA S F，et al.Electric hydraulic hybrid vehicle powertrain design and optimization-based power distribution control to extend driving range and battery life cycle［J］.Energy Conversion and Management，2022，252：115094.

HU J J，ZU G Q，JIA M X，et al.Parameter matching and optimal energy management for a novel dual-motor multi-modes powertrain system［J］.Mechanical Systems and Signal Processing，2019，116：113-128.

刘继宗，吴小平，孔维华.基于鱼群优化算法的有轨电车用燃料电池混合动力系统参数配置［J］.吉林大学学报（工学版），2022，52（9）：2004-2013.

LIU Jizong，WU Xiaoping，KONG Weihua. Parameter configuration of fuel cell hybrid system for tram based on fish swarm optimization algorithm［J］.Journal of Jilin University（Engineering and Technology Edition），2022，52（9）：2004-2013.

余佳衡，程相，孟垚，等.功率分流式混合动力系统参数匹配优化研究［J］.现代制造工程，2021（9）：33-39.

YU Jiaheng，CHENG Xiang，MENG Yao，et al.Study on optimization for parameters of power-split hybrid power system［J］.Modern Manufacturing Engineering，2021（9）：33-39.

韩爱国，方思远，徐冰洁.插电轴混合动力乘用车能量管理策略优化研究［J］.武汉理工大学学报，2021，43（12）：45-53.

HAN Aiguo，FANG Siyuan，XU Bingjie.Research on optimization of energy management strategy for plug-in two-axle hybrid passenger vehicle［J］.Journal of Wuhan University of Technology，2021，43（12）：45-53.

严正峰，王浩琳，吴景铼，等.燃料电池客车驱动系统建模及能量管理策略优化研究［J］.重庆理工大学学报（自然科学），2021，35（9）：8-16.

YAN Zhengfeng，WANG Haolin，WU Jinglai，et al.Modeling and energy management strategy optimization for the driving system of a fuel cell based bus［J］.Journal of Chongqing University of Technology（Natural Science），2021，35（9）：8-16.

李萍，朱晓璐，焦晓红.基于智能优化规则的并联混合动力汽车能量管理策略［J］.燕山大学学报，2019，43（6）：546-553.

LI Ping，ZHU Xiaolu，JIAO Xiaohong.Parallel hybrid electric vehicle energy management strategy based on intelligent optimization rules［J］.Journal of Yanshan University，2019，43（6）：546-553.

常远.基于动态规划的并联混合动力动车组能量管理策略研究［J］.内燃机与配件，2019（8）：114-119.

CHANG Yuan.Research on energy management strategy of parallel hybrid EMU based on dynamic programming［J］.Internal Combustion Engine ＆ Parts，2019（8）：114-119.

WANG Z，JIAO X H.Optimization of the powertrain and energy management control parameters of a hybrid hydraulic vehicle based on improved multi-objective particle swarm optimization［J］.Engineering Optimization，2021，53（11）：1835-1854.

KWAN T H，WU X F，YAO Q H.Parameter sizing and stability analysis of a highway fuel cell electric bus power system using a multi-objective optimization approach［J］.International Journal of Hydrogen Energy，2018，43（45）：20976-20992.

杜常清，何隽逸，张佩，等.混合动力重型货车参数局部与集成优化仿真研究［J］.汽车工程学报，2022，12（5）：614-623.

DU Changqing，HE Junyi，ZHANG Pei，et al.Simulation research on local and integrated optimization of parameters for hybrid heavy-duty truck［J］.Chinese Journal of Automotive Engineering，2022，12（5）：614-623.

李聪波，朱道光，胡芮，等.电动汽车两挡动力系统参数与控制策略集成优化［J］.计算机集成制造系统，2019，25（7）：1706-1716.

LI Congbo，ZHU Daoguang，HU Rui，et al.Integrated approach of two-speed power system parameter and control strategy optimization for electric vehicle［J］.Computer Integrated Manufacturing Systems，2019，25（7）：1706-1716.

AZAD S，BEHTASH M，HOUSHMAND A，et al.PHEV powertrain co-design with vehicle performance considerations using MDSDO［J］.Structural and Multidisciplinary Optimization，2019，60（3）：1155-1169.

闫祥海，李宗召，徐立友，等.纯电动汽车动力系统结构参数与整车控制参数集成优化［J］.现代制造工程，2022（8）：65-70.

YAN Xianghai，LI Zongzhao，XU Liyou，et al.Pure electric vehicle power system structure parameters and vehicle control parameters integration optimization［J］.Modern Manufacturing Engineering，2022（8）：65-70.

ZHOU X Y，QIN D T，YAO M Y，et al.Representation，generation，and optimization methodology of hybrid electric vehicle powertrain architectures［J］.Journal of Cleaner Production，2020，256：120711.

HU X S，HAN J，TANG X L，et al.Powertrain design and control in electrified vehicles：a critical review［J］.IEEE Transactions on Transportation Electrification，2021，7（3）：1990-2009.

王喜明.基于最优化能量管理策略的混合动力系统参数优化［J］.客车技术与研究，2018，40（4）：11-13.

WANG Ximing.Parameters optimization of hybrid powertrain based on optimization energy management strategy［J］.Bus & Coach Technology and Research，2018，40（4）：11-13.

崔庆虎，杜二磊，侯代峥，等.插电式混合动力汽车传动系统优化设计［J］.农业装备与车辆工程，2020，58（8）：102-106.

CUI Qinghu，DU Erlei，HOU Daizheng，et al.Optimum design of transmission system for plug-in hybrid electric vehicle［J］.Agricultural Equipment ＆ Vehicle Engineering，2020，58（8）：102-106.

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