A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle
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 limita...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-09-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/13/17/4529 |
| _version_ | 1797554922365911040 |
|---|---|
| author | S. N. Shivappriya S. Karthikeyan S. Prabu R. Pérez de Prado B. D. Parameshachari |
| author_facet | S. N. Shivappriya S. Karthikeyan S. Prabu R. Pérez de Prado B. D. Parameshachari |
| author_sort | S. N. Shivappriya |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T16:38:59Z |
| format | Article |
| id | doaj.art-a474eba2a8b2423793a657496c822d4e |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T16:38:59Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-a474eba2a8b2423793a657496c822d4e2023-11-20T12:10:19ZengMDPI AGEnergies1996-10732020-09-011317452910.3390/en13174529A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric VehicleS. N. Shivappriya0S. Karthikeyan1S. Prabu2R. Pérez de Prado3B. D. Parameshachari4Kumaraguru College of Technology, Coimbatore, Tamil Nadu 641049, IndiaM. Kumarasamy College of Engineering, Karur, Tamil Nadu 639113, IndiaMahendra Institute of Technology, Namakkal, Tamil Nadu 637503, IndiaTelecommunication Engineering Department, University of Jaén, 23700 Jaén, SpainGSSS Institute of Engineering and Technology for Women, Mysuru 570016, IndiaIn 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.https://www.mdpi.com/1996-1073/13/17/4529automotive systemSQP approachdynamic optimizationparallel hybrid electric vehicleartificial bee colonyoptimization algorithm |
| spellingShingle | S. N. Shivappriya S. Karthikeyan S. Prabu R. Pérez de Prado B. D. Parameshachari A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle Energies automotive system SQP approach dynamic optimization parallel hybrid electric vehicle artificial bee colony optimization algorithm |
| title | A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle |
| title_full | A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle |
| title_fullStr | A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle |
| title_full_unstemmed | A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle |
| title_short | A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle |
| title_sort | modified abc sqp based combined approach for the optimization of a parallel hybrid electric vehicle |
| topic | automotive system SQP approach dynamic optimization parallel hybrid electric vehicle artificial bee colony optimization algorithm |
| url | https://www.mdpi.com/1996-1073/13/17/4529 |
| work_keys_str_mv | AT snshivappriya amodifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT skarthikeyan amodifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT sprabu amodifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT rperezdeprado amodifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT bdparameshachari amodifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT snshivappriya modifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT skarthikeyan modifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT sprabu modifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT rperezdeprado modifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle AT bdparameshachari modifiedabcsqpbasedcombinedapproachfortheoptimizationofaparallelhybridelectricvehicle |