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

Author

Listed:
  • 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)

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.

Suggested Citation

  • S. N. Shivappriya & S. Karthikeyan & S. Prabu & R. Pérez de Prado & B. D. Parameshachari, 2020. "A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle," Energies, MDPI, vol. 13(17), pages 1-22, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4529-:d:407245
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    References listed on IDEAS

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    1. Prabu Subramani & Ganesh Babu Rajendran & Jewel Sengupta & Rocío Pérez de Prado & Parameshachari Bidare Divakarachari, 2020. "A Block Bi-Diagonalization-Based Pre-Coding for Indoor Multiple-Input-Multiple-Output-Visible Light Communication System," Energies, MDPI, vol. 13(13), pages 1-16, July.
    2. Zhang, Pei & Yan, Fuwu & Du, Changqing, 2015. "A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 88-104.
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