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논문 기본 정보
- 자료유형
- 학위논문
- 저자정보
- 지도교수
- 尹泰雄
- 발행연도
- 2016
- 저작권
- 고려대학교 논문은 저작권에 의해 보호받습니다.
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The objective of this thesis is to present a battery charging algorithm for Electric Vehicles (EVs). The goal of using this method is to reduce the charging cost.
For the purposes of the control design, a third order model is presented for a battery. Using a Singular Perturbation Theory, we derive a first order model from the third order model. Then, we use this first order model to design a controller.
The controller proposed is based on Economic Model Predictive Control (EMPC) Theory, which is similar to Model Predictive Control (MPC) Theory. The difference between these two algorithms is the characteristic of the cost function. Unlike the standard MPC algorithms, the EMPC cost functions are not positive definite, and therefore the optimal cost cannot be a Lyapunov function for the closed-loop system. The cost function in this thesis reflects the meaning of the charging cost so that we can reduce charging cost in real applications.
The conditions for the feasibility of the proposed EMPC and the boundness of the state variables are given. Also, it is shown that the optimal steady-state solution of the EMPC is marginally stable. It is guaranteed that the terminal state converges to its terminal constraint.
The effectiveness of the proposed algorithm is shown using computer simulations. It is seen that the resulting EMPC strategy is effective in reducing the charging cost, in comparison to the case where a traditional MPC algortithm is employed.
For the purposes of the control design, a third order model is presented for a battery. Using a Singular Perturbation Theory, we derive a first order model from the third order model. Then, we use this first order model to design a controller.
The controller proposed is based on Economic Model Predictive Control (EMPC) Theory, which is similar to Model Predictive Control (MPC) Theory. The difference between these two algorithms is the characteristic of the cost function. Unlike the standard MPC algorithms, the EMPC cost functions are not positive definite, and therefore the optimal cost cannot be a Lyapunov function for the closed-loop system. The cost function in this thesis reflects the meaning of the charging cost so that we can reduce charging cost in real applications.
The conditions for the feasibility of the proposed EMPC and the boundness of the state variables are given. Also, it is shown that the optimal steady-state solution of the EMPC is marginally stable. It is guaranteed that the terminal state converges to its terminal constraint.
The effectiveness of the proposed algorithm is shown using computer simulations. It is seen that the resulting EMPC strategy is effective in reducing the charging cost, in comparison to the case where a traditional MPC algortithm is employed.
목차
iii목 차Abstract ----------------------------------------------- i목 차 ----------------------------------------------- iii그 림 목 차 ----------------------------------------------- v제 1 장 서 론 ------------------------------------------- 1제 1 절 연구 배경 및 내용 ---------------------------------- 1제 2 절 논문 구성 --------------------------------------- 4제 2 장 배터리 모델 ---------------------------------------- 6제 1 절 3 차 모델 ---------------------------------------- 6제 2 절 1 차 모델 ---------------------------------------- 82.1 특이 섭동 이론 ------------------------------------- 82.2 근사화 모델 --------------------------------------- 9제 3 장 배터리 충전 알고리즘 --------------------------------- 12제 1 절 경제적 모델예측제어( Economic Model Predictive Control, EMPC) ----------------------------------------------- 121.1 경제적 모델예측제어알고리즘 --------------------------- 121.2 제안하는 배터리 충전 전략 ----------------------------- 16제 2 절 EMPC 해석 -------------------------------------- 192.1 해의 존재성 --------------------------------------- 192.2 상태 변수의 유한성 ---------------------------------- 222.3 EMPC 의 안정성 ------------------------------------ 22제 4 장 모의실험 ------------------------------------------ 24제 1 절 EMPC 성능 평가 ----------------------------------- 251.1 EMPC 파라미터 Ν에 따른 성능 비교 --------------------- 251.2 다른 제어기와 성능 비교 ----------------------------- 29제 5 장 결 론 ------------------------------------------- 32참고 문헌 ----------------------------------------------- 34
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