{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T19:37:52Z","timestamp":1767901072118,"version":"3.49.0"},"reference-count":18,"publisher":"Wiley","license":[{"start":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T00:00:00Z","timestamp":1554076800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Scientific and Technology Research Program of Chongqing Municipal Education Commission","award":["KJQN201800718"],"award-info":[{"award-number":["KJQN201800718"]}]},{"name":"Scientific and Technology Research Program of Chongqing Municipal Education Commission","award":["cstc2017jcyjAX0053"],"award-info":[{"award-number":["cstc2017jcyjAX0053"]}]},{"DOI":"10.13039\/501100013223","name":"Chongqing Research Program of Basic Research and Frontier Technology","doi-asserted-by":"crossref","award":["KJQN201800718"],"award-info":[{"award-number":["KJQN201800718"]}],"id":[{"id":"10.13039\/501100013223","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100013223","name":"Chongqing Research Program of Basic Research and Frontier Technology","doi-asserted-by":"crossref","award":["cstc2017jcyjAX0053"],"award-info":[{"award-number":["cstc2017jcyjAX0053"]}],"id":[{"id":"10.13039\/501100013223","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Control Science and Engineering"],"published-print":{"date-parts":[[2019,4,1]]},"abstract":"<jats:p>For global optimal control strategy, it is not only necessary to know the driving cycle in advance but also difficult to implement online because of its large calculation volume. As an artificial intelligent-based control strategy, reinforcement learning (RL) is applied to an energy management strategy of a super-mild hybrid electric vehicle. According to time-speed datasets of sample driving cycles, a stochastic model of the driver\u2019s power demand is developed. Based on the Markov decision process theory, a mathematical model of an RL-based energy management strategy is established, which assumes the minimum cumulative return expectation as its optimization objective. A policy iteration algorithm is adopted to obtain the optimum control policy that takes the vehicle speed, driver\u2019s power demand, and state of charge (SOC) as the input and the engine power as the output. Using a MATLAB\/Simulink platform, CYC_WVUCITY simulation model is established. The results show that, compared with dynamic programming, this method can not only adapt to random driving cycles and reduce fuel consumption of 2.4%, but also be implemented online because of its small calculation volume.<\/jats:p>","DOI":"10.1155\/2019\/9259712","type":"journal-article","created":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T23:37:40Z","timestamp":1554161860000},"page":"1-12","source":"Crossref","is-referenced-by-count":10,"title":["An Energy Management Strategy for a Super-Mild Hybrid Electric Vehicle Based on a Known Model of Reinforcement Learning"],"prefix":"10.1155","volume":"2019","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5416-3169","authenticated-orcid":true,"given":"Yanli","family":"Yin","sequence":"first","affiliation":[{"name":"School of Mechatronics & Automobile Engineering, Chongqing Jiao Tong University, Chongqing 400054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Ran","sequence":"additional","affiliation":[{"name":"School of Mechatronics & Automobile Engineering, Chongqing Jiao Tong University, Chongqing 400054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liufeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechatronics & Automobile Engineering, Chongqing Jiao Tong University, Chongqing 400054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoliang","family":"Pan","sequence":"additional","affiliation":[{"name":"Chongqing Changan Automobile Stock Co., Ltd., Chongqing 400054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2086-125X","authenticated-orcid":true,"given":"Yong","family":"Luo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Advanced Manufacturing Technology for Automobile Parts, Ministry of Education, Chongqing University of Technology, Chongqing 400054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"issue":"4","key":"1","first-page":"583","volume":"34","year":"2013","journal-title":"Journal of Northeastern University"},{"issue":"2","key":"2","first-page":"121","volume":"35","year":"2013","journal-title":"Automotive Engineering"},{"issue":"8","key":"3","doi-asserted-by":"crossref","first-page":"162","DOI":"10.3901\/JME.2016.08.162","volume":"52","year":"2016","journal-title":"Journal of Mechanical Engineering"},{"issue":"4","key":"4","first-page":"130","volume":"29","year":"2016","journal-title":"Chinese Journal of Highway and Transport"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2015.2409235"},{"issue":"3","key":"6","first-page":"263","volume":"38","year":"2016","journal-title":"Automotive Engineering Magazine"},{"issue":"6","key":"8","first-page":"674","volume":"38","year":"2016","journal-title":"Automotive Engineering"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2013.2287102"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/tcst.2014.2361294"},{"issue":"11","key":"11","volume":"29","year":"2013","journal-title":"Materia"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2527244"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.3901\/JME.2017.16.086"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2018.07.022"},{"issue":"10","key":"15","first-page":"1","volume":"2018","year":"2018","journal-title":"IEEE Transactions on Industrial Informatics"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2018.03.104"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1109\/TMECH.2017.2707338"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2018.2797322"},{"key":"19","year":"2011"}],"container-title":["Journal of Control Science and Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/jcse\/2019\/9259712.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jcse\/2019\/9259712.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jcse\/2019\/9259712.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,21]],"date-time":"2020-05-21T04:31:17Z","timestamp":1590035477000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/jcse\/2019\/9259712\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,1]]},"references-count":18,"alternative-id":["9259712","9259712"],"URL":"https:\/\/doi.org\/10.1155\/2019\/9259712","relation":{},"ISSN":["1687-5249","1687-5257"],"issn-type":[{"value":"1687-5249","type":"print"},{"value":"1687-5257","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,1]]}}}