Model predictive control of air-conditioning system for electric vehicles.
In this era, vehicles become part of human life. Without vehicles, it is inconvenient for human to travel, biking or walking will be done instead which will consume a lot of time and energy. Nowadays, everyone is using petrol vehicles, and the emission of petrol vehicles will cause air pollution....
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| 第一著者: | |
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| フォーマット: | Final Year Project / Dissertation / Thesis |
| 出版事項: |
2022
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| 主題: | |
| オンライン･アクセス: | http://eprints.utar.edu.my/4638/1/fyp_CS_2022_AWH.pdf http://eprints.utar.edu.my/4638/ |
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| 要約: | In this era, vehicles become part of human life. Without vehicles, it is
inconvenient for human to travel, biking or walking will be done instead which will
consume a lot of time and energy. Nowadays, everyone is using petrol vehicles, and the
emission of petrol vehicles will cause air pollution. Hence, electric vehicle is introduced
to reduce the air pollution since it can be known as zero emission vehicle. However,
electric vehicle travels shorter distance compared to petrol vehicle. The reason is the
air conditioning system of electric vehicle consumed a lot of energy and this limitation
affected the thought of human by using petrol vehicle will be much better. Hence, there
are various of control algorithm such as PID controller, Fuzzy Logic controller and
Ruled-based Bang-Bang controller can be used to tackle this issue. In this project, a
control algorithm which is model predictive control (MPC) will be introduced to
optimize the energy consumption and the cabin temperature of electric vehicle. The
state space model and neural network model can be identified as the prediction model.
After defining the prediction model, the model will be implemented to the MPC by
using MATLAB. And finally, the result will be simulated. |
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