{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T01:10:15Z","timestamp":1769217015925,"version":"3.49.0"},"reference-count":21,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2019,9,30]],"date-time":"2019-09-30T00:00:00Z","timestamp":1569801600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2020,1]]},"abstract":"<jats:p> One of the main research areas of the automotive sector is energy consumption and the reduction of pollutant emissions. Therefore, the hybrid electrical vehicle Vehicle electrical hybrid (VEH) is a possible approach to improve the vehicle components or its architecture to maximize system efficiency. This vehicle benefits from levels of consumption and emission of pollutants lower than the thermal vehicle. The problem is then to find the right split power between the two hybrid sources, the internal combustion engine (ICE) and the electrical machines (EM) to minimize fuel consumption. These energy management strategies are the algorithms that achieve instant split power between the two sources in the hybrid electric vehicle (HEV) while controlling the battery state of charge (SOC), in order to improve the fuel economy and optimize the performance HEV. In this research, a parametric study on the impact of optimization of the energy management strategy on the optimal operation of the vehicle is presented. A hybrid vehicle model is described and rules-based energy management strategy is presented. Later these rules are optimized with an optimization algorithm based on Grey Wolf optimizer (GWO). It is a new meta-heuristic based on the population. The results of the simulation make it possible to deduce the impact of this optimal strategy of energy management on fuel consumption and CO2 emissions. The obtained results show that the optimal operation of the vehicle varies according to the best energy management strategies. <\/jats:p>","DOI":"10.1177\/0142331219874152","type":"journal-article","created":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T02:48:55Z","timestamp":1569898135000},"page":"69-80","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":24,"title":["An efficient method for energy management optimization control: Minimizing fuel consumption for hybrid vehicle applications"],"prefix":"10.1177","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4360-8131","authenticated-orcid":false,"given":"Mohamed Elhedi","family":"Hmidi","sequence":"first","affiliation":[{"name":"Research Laboratory Smart Electricity & ICT, SEICT, LR18ES44"},{"name":"National Engineering School of Carthage (ENICarthage), University of Carthage, Tunisia"}]},{"given":"Ines","family":"Ben Salem","sequence":"additional","affiliation":[{"name":"Research Laboratory Smart Electricity & ICT, SEICT, LR18ES44"},{"name":"National Engineering School of Carthage (ENICarthage), University of Carthage, Tunisia"}]},{"given":"Lilia","family":"El Amraoui","sequence":"additional","affiliation":[{"name":"Research Laboratory Smart Electricity & ICT, SEICT, LR18ES44"},{"name":"National Engineering School of Carthage (ENICarthage), University of Carthage, Tunisia"}]}],"member":"179","published-online":{"date-parts":[[2019,9,30]]},"reference":[{"key":"bibr1-0142331219874152","doi-asserted-by":"publisher","DOI":"10.1109\/4235.985692"},{"key":"bibr2-0142331219874152","volume-title":"Optimal Control of a Parallel Powertrain: From Global Optimization to Real Time Control Strategy","author":"Delprat S","year":"2001"},{"key":"bibr3-0142331219874152","doi-asserted-by":"publisher","DOI":"10.1109\/VPPC.2009.5289754"},{"key":"bibr4-0142331219874152","author":"Duoba M","year":"1996","journal-title":"HEV Dynamometer Testing with State-of-Charge Corrections HEV Challenge, SAE Technical Paper"},{"key":"bibr5-0142331219874152","unstructured":"EEA (2016), Transition towards a more sustainable mobility system \u2013 TERM 2016: Transport indicators tracking progress towards environmental targets in Europe. 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