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Maximizing Energy Harvesting in Electric Vehicles through Optimal Regenerative Braking Utilization
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In recent years, electric vehicle (EV) technology has proved to be a viable solution to clean and efficient transportation and is becoming the main focus of many automotive companies. Therefore, extensive research is being conducted in both the industry and academia towards the design and development of EV technology. Despite significant improvements in drivability and performance, the global EV market still only accounts for a fraction of new vehicle sales annually. One important obstacle to the large-scale adoption of EVs is their restricted driving range. In spite of substantial research efforts, there is still a lack of technically and financially viable solutions to address the limited driving range of these vehicles. One way to improve the driving range of EVs is through regenerative braking capability which is defined as the process of recapturing the kinetic energy of the vehicle during braking and converting it to electrical energy. This unique capability of EVs is achieved by controlling the electric motor to operate as a generator. However, this process is influenced by unpredictable factors such as driver behavior and driving conditions which can have significant impact on the electric motor operating point during braking. Furthermore, the coexistence of regenerative and friction braking in EVs introduces complexity when optimizing regenerative braking operation. The research carried out in this dissertation provides new and innovative methods for maximizing energy harvesting in EVs through addressing limitations of regenerative braking with an ultimate goal of extending the driving range of these vehicles. As the first step of this work, various factors influencing regenerative braking capability of EVs are studied and limitations of regenerative braking at low speed operating points are examined. Based on the findings, a detection method is proposed that relies on real-time sensing of the electric motor dc link current and is used to identify a boundary that distinguishes operating points in which regenerative braking is still effective at low speeds. In the next step, the operating principle of regenerative braking and its limitations are mathematically expressed and a brake controller is designed based on electric motor performance map that achieves optimal allocation of braking force among regenerative and friction braking. In the final step of this work, using the electric motor performance map, a maximum-current curve is introduced and a unique brake control strategy is proposed that maintains the electric motor operating point on this curve during braking and results in increased energy extraction during regenerative braking. The results obtained in this dissertation could be useful for EV automotive companies looking into improving regenerative braking capability of their existing products or planning to invest in different EV configurations from the viewpoint of maximizing regenerative braking performance.