{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T20:32:49Z","timestamp":1774643569685,"version":"3.50.1"},"reference-count":189,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T00:00:00Z","timestamp":1749168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Guangxi Science and Technology Major Special Project","award":["2023AA09011"],"award-info":[{"award-number":["2023AA09011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This paper presents a comprehensive analysis of hybrid electric vehicle (HEV) classification and energy management strategies (EMS), with a particular emphasis on the application and potential of genetic algorithms (GAs) in optimizing energy management strategies for hybrid electric vehicles. Initially, the paper categorizes hybrid electric vehicles based on mixing rates and power source configurations, elucidating the operational principles and the range of applicability for different hybrid electric vehicle types. Following this, the two primary categories of energy management strategies\u2014rule-based and optimization-based\u2014are introduced, emphasizing their significance in enhancing energy efficiency and performance, while also acknowledging their inherent limitations. Furthermore, the advantages of utilizing genetic algorithms in optimizing energy management systems for hybrid vehicles are underscored. As a global optimization technique, genetic algorithms are capable of effectively addressing complex multi-objective problems by circumventing local optima and identifying the global optimal solution. The adaptability and versatility of genetic algorithms allow them to conduct real-time optimization across diverse driving conditions. Genetic algorithms play a pivotal role in hybrid vehicle energy management and exhibit a promising future. When combined with other optimization techniques, genetic algorithms can augment the optimization potential for tackling complex tasks. Nonetheless, the advancement of this technique is confronted with challenges such as cost, battery longevity, and charging infrastructure, which significantly influence its widespread adoption and application.<\/jats:p>","DOI":"10.3390\/a18060354","type":"journal-article","created":{"date-parts":[[2025,6,6]],"date-time":"2025-06-06T09:02:03Z","timestamp":1749200523000},"page":"354","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Review of Hybrid Vehicles Classification and Their Energy Management Strategies: An Exploration of the Advantages of Genetic Algorithms"],"prefix":"10.3390","volume":"18","author":[{"given":"Yuede","family":"Pan","sequence":"first","affiliation":[{"name":"College of Mechanical Engineering, Guangxi University, Nanning 530004, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7124-3883","authenticated-orcid":false,"given":"Kaifeng","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Guangxi University, Nanning 530004, China"}]},{"given":"Yubao","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Guangxi University, Nanning 530004, China"}]},{"given":"Mingzhang","family":"Pan","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Guangxi University, Nanning 530004, China"}]},{"given":"Wei","family":"Guan","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Guangxi University, Nanning 530004, China"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Guangxi University, Nanning 530004, China"}]},{"given":"Changye","family":"Liu","sequence":"additional","affiliation":[{"name":"SAIC-GM-Wuling Automobile Corporation, Liuzhou 545007, China"}]},{"given":"Xingjia","family":"Man","sequence":"additional","affiliation":[{"name":"SAIC-GM-Wuling Automobile Corporation, Liuzhou 545007, China"}]},{"given":"Zhiqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou 545006, China"}]},{"given":"Mantian","family":"Li","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Guangxi University, Nanning 530004, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9279","DOI":"10.1016\/j.ijhydene.2009.09.058","article-title":"Transportation options in a carbon-constrained world: Hybrids, plug-in hybrids, biofuels, fuel cell electric vehicles, and battery electric vehicles","volume":"34","author":"Thomas","year":"2009","journal-title":"Int. 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