Research On Thermal Comfort Control Algorithm Of Vehicle Heat Pump Air Conditioning System

China’s automobile industry has begun to develop from traditional vehicles to new energy vehicles.Today,pure electric vehicles have become the main development direction of the modern automobile industry.Since traditional automobile airconditioning heating can use the waste heat of the engine,and the energy supply of the new-energy automobile air-conditioning system is provided by the battery,it is particularly important to improve heating performance and reduce battery energy consumption in low-temperature environments.In order to solve the problem of excessive energy consumption of electric vehicle air conditioning systems in low temperature environments,heat pump air conditioning systems have been developed for new energy vehicles.This paper introduces the control method of the basic components of the heat pump air-conditioning system,and designs the fuzzy control rules for the temperature control of the heat pump compressor,and realizes the precise control of the temperature of the passenger compartment.At the same time,this paper establishes a passenger cabin model and a thermal comfort model,and uses the thermal comfort of the passenger cabin and the energy consumption of the air-conditioning system as the optimization targets to design an optimized control strategy.The main work of the thesis includes:1.Vehicle cabin model modeling and thermal comfort index selection and modelingThis paper analyzes the thermal load of the passenger compartment,establishes a heat exchange model in AMESIM,and simulates the heat pump air-conditioning system.While establishing the passenger compartment model,obtain the temperature and humidity information of the passenger compartment model,and use thermal comfort indicators(PMV and PPD)to evaluate the thermal comfort of the passenger compartment.2.Design of temperature control rules for the passenger compartment based on fuzzy PIDThe traditional automobile air conditioning system uses PID algorithm for control,which has poor anti-interference ability and is difficult to adapt to the changing heat load environment,which affects the thermal comfort of the passenger cabin.Aiming at the heat pump air-conditioning system,this paper uses MATLAB to build a fuzzy PID control algorithm,combined with the heat pump air-conditioning system built by AMESIM to control the temperature of the passenger compartment.Through simulation analysis when the ambient temperature is-15℃ and the set value is 25℃,the rise time of fuzzy PID control is 39 seconds longer than that of PID control,and the overshoot is 3.48% less.Then,the temperature of the passenger compartment is controlled and simulated at a vehicle speed of 30 kilometers per hour and 60 kilometers per hour.The comparison results show that using fuzzy PID to control the temperature overshoot is less and the temperature control is more stable.3.Research on multi-objective optimization control strategy for thermal comfort and heat pump air conditioning energy consumption based on particle swarm optimizationWhen heating in a low-temperature environment,in order to comprehensively test thermal comfort and energy consumption,this paper uses particle swarm optimization algorithm to perform multi-objective optimization for thermal comfort indicators and heat pump air conditioning system energy consumption,and optimizes the air speed and set temperature of the air conditioning system.Adjusting thermal comfort and energy consumption,while changing the weights in optimization,proposed thermal comfort control strategies,energy-saving control strategies and integrated control strategies within the thermal comfort range.Through simulation analysis,the thermal comfort is 0.27 lower than the energy-saving control strategy,the energy consumption is 0.58 k W higher,and the COP value of the integrated control strategy is between the two.