The Reseach Of Electric Vehicle Thermal Management And Intelligent Control Strategy

The control of thermal management and its intellectualization is significant for the developing of electric vehicle.And the performance of the thermal management for the air conditioner(AC)and cabin system affect the comfort,driving experience of occupancies and the market impression of the electric vehicle.Besides,high range is crucial for electric car,nevertheless the AC system is a big energy consumer which would deeply shorten the it.Thus,in order to decrease range anxiety as well as improve the intelligence and comfortable of cabin thermal management,the design and optimization for intelligent control strategy of electric car’s thermal management system should be seriously considered.For that purpose,the thermal management and control strategy of AC-cabin system is researched in this paper.And there are the main contents and results of this research:Firstly,a control-oriented dynamic model of AC-cabin system is established,and the cooling process of simulation model is verified by experiment.Aiming at achieving self-adjustment for thermal comfort inside the cabin,the method of combining the historical temperature adjustment data of passengers and the PMV index is applied to adapt the thermal habit of different individual,then use it to obtained the comfort reference temperature for controller to track.Meanwhile,the fuzzy-PID approach is used to control the compressor in AC system and get an accuracy response for comfort reference temperature tracking under variable working conditions.The results show that the proposed control strategy can keep comfort and reduce the energy consumption compared to the traditional control method.So as to achieved the intelligent and comfort temperature control for electrical vehicle cabin.In order to further improve the control performance,the model predictive control(MPC)approach is applied to manipulated both the compressor and fan of the AC system synchronously.And the vehicle speed preview method is embedding to provide future working condition information to MPC for reducing the influence of disturbance.The results exhibit that the MPC can better handle the multiple-input and multiple-output problem of AC system and promote the corporation between the actuators of AC system.Thus,the MPC has positive influence in the efficiency,energy saving and preventing the frosting of AC system.In addition,the results also show that the vehicle preview can improve the transient response of cabin comfort temperature tracking of MPC.Finally,in the consideration of achieving economic corporative control of thermal management and healthy management of air quality in vehicle cabin,a cooperative temperature and ventilation control strategy for reducing virus infection risk and energy consumption of AC system is proposed.By the mean of combining the off-line ventilation logic optimization and model predictive temperature control,the goal of minimizing the three costs which include infection risk,temperature control error and energy consumption,can be achieved.The control results show that the proposed cooperative control strategy can do healthy ventilation economically,lower the infection risk and keep the thermal comfort in the cabin.Compared with the full ventilation and none ventilation strategies,it has better performance in general.