{"title":"An efficiency control strategy of dual-motor multi-gear drive algorithm","authors":"Lijun Xiao, Wei Liang, Jiahong Cai, Ming Wang, Jiahong Xiao, Yinyan Gong, Weigang Zhang","doi":"10.1080/09540091.2023.2249264","DOIUrl":null,"url":null,"abstract":"The Dual-motor multi-gear coupling powertrain (DMCP) has the potential to improve transmission system efficiency and driving comfort, but its complex structure and multiple working modes present challenges. The switching between different modes is easy to cause longitudinal biggish vehicle jerk. To address these issues,this paper introduces the Deep Deterministic Policy Gradient (DDPG) algorithm in the design of an Energy Management Strategy (EMS) that minimises total drive power consumption. And the number of working modes is divided and simplified. The process of switching dual motor and single motor to single motor is introduced in detail. The simulation results using AMESim and MATLAB show that the energy management strategy can effectively improve the economy, achieve no power interruption during mode switching, shift impact is less than 8m/s3, and output torque is remains stable.","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":"27 1","pages":"0"},"PeriodicalIF":3.2000,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Connection Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09540091.2023.2249264","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The Dual-motor multi-gear coupling powertrain (DMCP) has the potential to improve transmission system efficiency and driving comfort, but its complex structure and multiple working modes present challenges. The switching between different modes is easy to cause longitudinal biggish vehicle jerk. To address these issues,this paper introduces the Deep Deterministic Policy Gradient (DDPG) algorithm in the design of an Energy Management Strategy (EMS) that minimises total drive power consumption. And the number of working modes is divided and simplified. The process of switching dual motor and single motor to single motor is introduced in detail. The simulation results using AMESim and MATLAB show that the energy management strategy can effectively improve the economy, achieve no power interruption during mode switching, shift impact is less than 8m/s3, and output torque is remains stable.
期刊介绍：
Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing.
A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.
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