Abstract
The electric vehicle battery life is generally affected by its rapid utilization, accumulated heat and overall energy throughput. Inclusion of ultracapacitor along with battery provides enhanced flexibility in operating and utilizing the battery more adequately. In such dual storage systems, the energy management scheme plays an important role in determining the overall system efficiency. In this paper, a new concept to manage the state of charge (SOC) of ultracapacitor is proposed. The aim of the proposed approach is, based on the vehicle velocity at acceleration, to regulate the amount of energy that ultracapacitor should support in order to ensure its availability for an extended period. A two-stage artificial neural network based strategy is developed to achieve the aforementioned ultracapacitor SOC control. The battery energy throughput and its temperature rise during a complete battery discharge are taken as key parameters for the evaluation. It is shown in the paper that with the proposed approach, the energy storage system efficiency and battery life can be improved significantly. Finally, the applicability of the proposed concept is demonstrated experimentally.
| Original language | British English |
|---|---|
| Article number | 8468067 |
| Pages (from-to) | 10470-10481 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Vehicular Technology |
| Volume | 67 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Battery
- Drive cycle
- Dual storage
- Electric vehicle
- Energy management
- Fuzzy
- Neural network
- Rule-based
- Supercapacitor
- Ultracapacitor
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