A Novel Adaptive Equivalence Fuel Consumption Minimisation Strategy for a Hybrid Electric Two-Wheeler

Naga Kavitha Kommuri, Andrew McGordon, Antony Allen and Dinh Quang Truong
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Naga Kavitha Kommuri: Warwick Manufacturing Group (WMG), University of Warwick, Coventry CV4 7AL, UK
Andrew McGordon: Warwick Manufacturing Group (WMG), University of Warwick, Coventry CV4 7AL, UK
Antony Allen: Warwick Manufacturing Group (WMG), University of Warwick, Coventry CV4 7AL, UK
Dinh Quang Truong: Warwick Manufacturing Group (WMG), University of Warwick, Coventry CV4 7AL, UK

Energies, 2022, vol. 15, issue 9, 1-19

Abstract: One of the major challenges in implementing the equivalent fuel consumption minimisation strategy in hybrid electric vehicles is the adaptation of the equivalence factor to real-world driving. In this paper, a novel adaptive equivalent fuel consumption minimisation strategy (A-ECMS) has been developed for a hybrid two-wheeler to further improve fuel savings by predicting the drive cycles and thereby estimating and adapting the equivalence factor online for the ECMS energy management control. A learning vector quantitative neural network (LVQNN)-based classifier was first proposed to recognise the real-world driving cycle based on a fixed time window of past driving information. Along with standardised drive cycles, real-world driving data were used in the learning process to increase the robustness of the learning. The A-ECMS is then capable of regulating its equivalence factors online based on the LVQNN controller output. Numerical simulation results indicated that there was considerable improvement in fuel economy of the vehicle with the proposed methodology, up to 10.7%, compared to the use of traditional ECMS which was manually optimised for a single drive cycle. The average improvement in fuel economy over the ten drive cycles considered for testing is 3.93%.

Keywords: optimal real-time control; ECMS; hybrid two-wheeler; equivalence factor adaptation; neural network; drive cycle recognition (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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