Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle. (15th October 2022)
- Record Type:
- Journal Article
- Title:
- Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle. (15th October 2022)
- Main Title:
- Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle
- Authors:
- da Silva, Samuel Filgueira
Eckert, Jony Javorski
Corrêa, Fernanda Cristina
Silva, Fabrício Leonardo
Silva, Ludmila C.A.
Dedini, Franco Giuseppe - Abstract:
- Abstract: This study presents a comprehensive multi-objective optimization approach for a dual HESS-based electric vehicle (EV) powertrain using the interactive adaptive-weight genetic algorithm (i-AWGA) method. The dual HESS EV concept aims to show the benefits of combining independent traction systems powered by their respective energy sources. Therefore, the main purpose of this optimization is to simultaneously maximize driving autonomy and battery lifespan and minimize HESS size, considering design variables from components such as batteries, electric motors, differential, and ultracapacitors. At the same time, three independent fuzzy logic controllers – which perform the power management control between the hybrid energy storage systems – are likewise optimized, tuning their parameters according to the applied constraints. The best trade-off solution, equipped with a 332.34 kg dual HESS mass, achieved a driving range of 285.56 km and a front battery life cycle of 36585 h. As compared to a similar EV powered by a single HESS and optimized under the same driving conditions, the dual HESS EV improved the ratio between the driving range and energy storage system's overall mass by 3%, reaching a driving range 19.57% longer, and increasing the battery life by up to 22.88%. Graphical abstract: Highlights: Dual hybrid energy storage concept to improve EV drive range and battery life cycle. Multi-objective optimization of the EV drivetrain, energy storage and fuzzy control.Abstract: This study presents a comprehensive multi-objective optimization approach for a dual HESS-based electric vehicle (EV) powertrain using the interactive adaptive-weight genetic algorithm (i-AWGA) method. The dual HESS EV concept aims to show the benefits of combining independent traction systems powered by their respective energy sources. Therefore, the main purpose of this optimization is to simultaneously maximize driving autonomy and battery lifespan and minimize HESS size, considering design variables from components such as batteries, electric motors, differential, and ultracapacitors. At the same time, three independent fuzzy logic controllers – which perform the power management control between the hybrid energy storage systems – are likewise optimized, tuning their parameters according to the applied constraints. The best trade-off solution, equipped with a 332.34 kg dual HESS mass, achieved a driving range of 285.56 km and a front battery life cycle of 36585 h. As compared to a similar EV powered by a single HESS and optimized under the same driving conditions, the dual HESS EV improved the ratio between the driving range and energy storage system's overall mass by 3%, reaching a driving range 19.57% longer, and increasing the battery life by up to 22.88%. Graphical abstract: Highlights: Dual hybrid energy storage concept to improve EV drive range and battery life cycle. Multi-objective optimization of the EV drivetrain, energy storage and fuzzy control. Robust Dual-HESS solutions evaluated under standard and real-world driving cycles. Battery life extension in up to 22.88% against single HESS-equipped EV. Increase of driving range in 19.57% as compared to the single HESS configuration. … (more)
- Is Part Of:
- Applied energy. Volume 324(2022)
- Journal:
- Applied energy
- Issue:
- Volume 324(2022)
- Issue Display:
- Volume 324, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 324
- Issue:
- 2022
- Issue Sort Value:
- 2022-0324-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-10-15
- Subjects:
- Electric vehicle -- Hybrid energy storage system (HESS) -- Fuzzy logic control -- Battery state of health (SoH) -- Multi-objective optimization
Power (Mechanics) -- Periodicals
Energy conservation -- Periodicals
Energy conversion -- Periodicals
621.042 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03062619 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apenergy.2022.119723 ↗
- Languages:
- English
- ISSNs:
- 0306-2619
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.300000
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- 23313.xml