A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle

S. N. Shivappriya, S. Karthikeyan, S. Prabu, R. Pérez de Prado and B. D. Parameshachari
Additional contact information
S. N. Shivappriya: Kumaraguru College of Technology, Coimbatore, Tamil Nadu 641049, India
S. Karthikeyan: M. Kumarasamy College of Engineering, Karur, Tamil Nadu 639113, India
S. Prabu: Mahendra Institute of Technology, Namakkal, Tamil Nadu 637503, India
R. Pérez de Prado: Telecommunication Engineering Department, University of Jaén, 23700 Jaén, Spain
B. D. Parameshachari: GSSS Institute of Engineering and Technology for Women, Mysuru 570016, India

Energies, 2020, vol. 13, issue 17, 1-22

Abstract: In this paper, an improved fuel consumption and emissions control strategy based on a mathematical and heuristic approach is presented to optimize Parallel Hybrid Electric Vehicles (HEVs). The well-known Sequential Quadratic Programming mathematical method (SQP-Hessian approach) presents some limitations to achieve fuel consumption and emissions control optimization, as it is not able to find the global minimum, and it generally shows efficient results in local exploitation searches. The usage of a combined Modified Artificial Bee Colony algorithm (MABC) with the SQP approach is proposed in this work to obtain better optimal solutions and overcome these limitations. The optimization is performed with boundary conditions, considering that the optimized vehicle performance has to satisfy Partnership for a New Generation of Vehicles (PNGV) constraints. The weighting factor of the vehicle’s performance parameters in the objective function is varied, and optimization is carried out for two different driving cycles, namely Federal Test Procedure (FTP) and Economic commission Europe—Extra Urban Driving Cycle (ECE-EUDC), using the MABC and MABC with SQP approaches. The MABC with SQP approach shows better performance in terms of fuel consumption and emissions than the pure heuristic approach for the considered vehicle with similar boundary conditions. Moreover, it does not present significant penalties for final battery charging and it offers an optimized size of the key vehicle’s components for different driving cycles.

Keywords: automotive system; SQP approach; dynamic optimization; parallel hybrid electric vehicle; artificial bee colony; optimization algorithm (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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