PSO-based MPPT controller for an Interleaved DC charging system /
The idea of standalone solar charging has inspired solutions for power crisis issues while suggesting a clean and sustainable power source for Electric Vehicle. However, solar energy system dependent for high power charging system faces some challenges due to system performance efficiency and power...
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| 主要作者: | |
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
Kuala Lumpur :
Kulliyyah of Engineering, International Islamic University Malaysia,
2018
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| 主题: | |
| 在线阅读: | http://studentrepo.iium.edu.my/handle/123456789/5152 |
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| 总结: | The idea of standalone solar charging has inspired solutions for power crisis issues while suggesting a clean and sustainable power source for Electric Vehicle. However, solar energy system dependent for high power charging system faces some challenges due to system performance efficiency and power availability. Integration of an improved maximum power point tracking (MPPT) controller and charging controller promises better overall system performance. Recently, more advanced soft computing methods have been used for better performance and flexible in handling abnormal conditions such as partial shading and module mismatch. Therefore, based on the speed and complexity of the system, the research simulates the feasibility of two algorithms in determining the best method for controlling MPPT which is Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). Due to the performance of PSO is better in MSE and convergence speed, the research proposes the development of a particle swarm optimization (PSO) based maximum power point tracking (MPPT) controller. Besides, due to various charging methods used in market, the most promising method for high current application on battery to battery storage transfer is using Interleaved Boost Converter (IBC). Therefore, the research proposes an integrated Particle Swarm Optimization (PSO) based maximum power point tracking (MPPT) for an Interleaved Direct Current (DC) Charging System in Electric Vehicle. Therefore, the research is expected to reach 30% faster convergence speed compare to the other computational method mainly Firefly Algorithm (FA). The research aimed for charging system able to achieve efficiency of 90%. |
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| 实物描述: | xiii, 81 leaves : colour illustrations ; 30cm. |
| 参考书目: | Includes bibliographical references (leaves 65-67). |