| With the global environmental pollution and energy shortage becoming more and more serious,countries have successively promoted the development of vehicles in the direction of electrification.New energy electric vehicles will be the main means of transportation in the future.The driving system formed by battery,motor controller and motor is the core of electric vehicle.As the core of motor controller,semiconductor switching device IGBT(insulated gate bipolar transistor)plays a key role in inverter and rectification.The thermal stress of IGBT in the working process is the main factor leading to the failure of IGBT.Accurately estimating and controlling the junction temperature of IGBT plays a vital role in protecting IGBT and prolonging the working life of IGBT.This paper studies from the direction of engineering application.Taking the power semiconductor IGBT of electric vehicle as the research object,an on-line IGBT junction temperature estimation method with engineering significance is proposed.Based on the framework of foster thermal network model,combined with the heat generation of IGBT module measured by double pulse experiment during on,on and off,as well as the thermal impedance and thermal coupling parameters between chips extracted by finite element method,this paper accurately estimates the junction temperature of IGBT.The main research contents of this paper are as follows:(1)The internal structure of IGBT module and its topology in electric vehicle motor controller are studied.The failure analysis of IGBT module is carried out according to the characteristics of structure and material,and the measures to improve the reliability of IGBT module are put forward.(2)The power loss model of IGBT is established.Through the double pulse experiment and data manual,the on,on,off and reverse recovery characteristic parameters of IGBT chip and diode chip in IGBT module are obtained,the power loss of IGBT module is calculated,and the power loss model of IGBT module is built.(3)This paper expounds the common equivalent thermal network model,analyzes its advantages and disadvantages,and selects the equivalent thermal network model suitable for the engineering application of junction temperature estimation of IGBT module to fit the thermal impedance of IGBT module.The thermal impedance parameters between IGBT chip and diode chip and coolant are extracted by finite element analysis.Considering the mutual influence of heating between IGBT chip and diode chip,the thermal coupling parameters between the two chips are calculated by finite element method.(4)The IGBT junction temperature estimation model is verified by setting up a supporting platform.The "black module" experiment is carried out on the bench.The infrared thermometer is used to record the real-time junction temperature and the maximum steady-state junction temperature of IGBT.The junction temperature estimated by the IGBT junction temperature estimation model is compared with the junction temperature measured by the infrared thermometer to verify the accuracy and feasibility of the model.Based on the measured junction temperature data,the power loss of the motor in locked rotor state is corrected.In the normal rotation state of the motor,the upper and lower bridge arm IGBT chips and diode chips of a certain phase of the IGBT module heat alternately,while in the locked rotor state,the upper bridge arm IGBT chip and lower bridge arm diode chip heat alternately,or the upper bridge arm diode chip and lower bridge arm IGBT chip heat alternately,and the degree of heating is related to the locked rotor position.At the same time,the three-phase current will change to DC under locked rotor condition.Based on the measured data of junction temperature,this paper corrects the power loss under the special working condition of motor locked rotor,which makes the model development process more efficient.At the same time,it also ensures the high accuracy of junction temperature estimation under locked rotor working condition,and realizes the adaptation of the junction temperature estimation model to the whole working condition of electric vehicle. |