CN-122008781-A - Whole vehicle thermal management method and device, electronic equipment and storage medium

CN122008781ACN 122008781 ACN122008781 ACN 122008781ACN-122008781-A

Abstract

The application relates to the technical field of vehicles, and discloses a whole vehicle thermal management method, a whole vehicle thermal management device, electronic equipment and a storage medium. The method comprises the steps of at least obtaining state information of a vehicle, at least establishing a battery domain heat load prediction model, a motor domain heat load prediction model, an electric control domain heat load prediction model, a cabin domain heat load prediction model, a navigation working condition identification model, a power demand prediction model and an environment change prediction model of the vehicle on the basis of a preset algorithm framework and each state information, constructing a whole vehicle multi-objective optimization function and constraint conditions thereof according to the state information, and executing whole vehicle heat management cooperative operation according to each model, the whole vehicle multi-objective optimization function and the constraint conditions thereof. The application can realize the cooperative control of the battery, the motor, the electric control and the passenger cabin in the new energy commercial vehicle at least, so as to realize the multi-objective optimization of the energy efficiency, the service life and the response speed of the whole vehicle on the premise of ensuring the temperature control precision of each domain, and is beneficial to ensuring the driving experience of users.

Inventors

CAI WENWEN
PANG XUEWEN
WANG DAZHONG
LI SONGSONG
SHI RUOXIN

Assignees

一汽解放汽车有限公司

Dates

Publication Date: 20260512
Application Date: 20260106

Claims (10)

1. The whole vehicle heat management method is characterized by being at least used for a new energy commercial vehicle; The whole vehicle thermal management method at least comprises the following steps: At least acquiring battery domain state information, motor domain state information, electric control domain state information, cabin domain state information and whole vehicle running state information of a vehicle; On the basis of a preset algorithm architecture and each state information, at least establishing a battery domain heat load prediction model, a motor domain heat load prediction model, an electric control domain heat load prediction model, a cabin domain heat load prediction model, a navigation working condition recognition model, a power demand prediction model and an environment change prediction model of the vehicle, and constructing a multi-objective optimization function of the whole vehicle and constraint conditions thereof according to the state information; and executing the whole vehicle thermal management collaborative operation according to each thermal load prediction model, the navigation working condition identification model, the power demand prediction model, the environment change prediction model, the whole vehicle multi-objective optimization function and the constraint condition thereof.
2. The overall vehicle thermal management method of claim 1, wherein the battery domain thermal load prediction model is implemented at least by: Q_bat=I 2 R_int+IVη_loss+k_conv(T_bat-T_amb); In the above formula, q_bat represents a battery thermal load, I 2 r_int represents a battery internal resistance heat generation, I represents a battery charge-discharge current, r_int represents a battery equivalent internal resistance, IV η_loss represents a battery charge-discharge loss, V represents a battery charge-discharge voltage, η_loss represents a battery loss coefficient, k_conv (t_bat-t_amb) represents a battery convection heat dissipation, k_conv represents a battery convection coefficient, t_bat represents a battery average temperature, and t_amb represents an ambient temperature.
3. The overall vehicle thermal management method of claim 1, wherein the electric machine domain thermal load prediction model is implemented at least by: Q_mot=P_mot(1-η_mot)+P_iron+P_mech; In the above formula, q_mot represents a motor heat load, p_mot (1- η_mot) represents a motor copper loss and a motor iron loss, p_mot represents a motor output power, η_mot represents a motor efficiency, p_iron represents a motor iron loss, and p_mech represents a motor mechanical loss.
4. The method of overall thermal management according to claim 1, wherein the electric domain thermal load prediction model is implemented at least by: Q_inv=P_sw+P_cond+P_cap; in the above equation, q_inv represents an electrically controlled thermal load, p_sw represents a switching loss, p_cond represents a conduction loss, and p_cap represents a capacitance loss.
5. The overall vehicle thermal management method of claim 1, wherein the cabin domain thermal load prediction model is implemented at least by: Q_cab=Q_conv+Q_solar+Q_human+Q_equip; In the above formula, q_conv represents convection heat, q_solar represents solar radiation, q_human represents passenger heat dissipation, and q_ equip represents equipment heat dissipation.
6. The method for thermal management of a vehicle according to claim 1, wherein the predetermined algorithm architecture at least employs a recurrent neural network combined with a long and short term memory layer.
7. The whole vehicle thermal management method according to claim 1, wherein the whole vehicle multi-objective optimization function is implemented at least by: J=w1E_total+w2ΔT_max+w3N_switch+w4T_response; In the above formula, J represents the whole vehicle multi-objective optimization function, e_total represents the total energy consumption of the system, Δt_max represents the maximum temperature difference of the battery domain, the motor domain, the electric control domain or the cabin domain, n_switch represents the number of switching times of the actuator, t_response represents the temperature response time, w1 represents the first weight coefficient, w2 represents the second weight coefficient, w3 represents the third weight coefficient, and w4 represents the fourth weight coefficient.
8. A whole vehicle thermal management device, characterized by being configured to perform the whole vehicle thermal management method according to any one of claims 1-7; The whole car heat management device at least comprises: the information acquisition module is at least used for acquiring battery domain state information, motor domain state information, electric control domain state information, cabin domain state information and whole vehicle running state information of the vehicle; The model building module is used for at least building a battery domain thermal load prediction model, a motor domain thermal load prediction model, an electric control domain thermal load prediction model, a cabin domain thermal load prediction model, a navigation working condition identification model, a power demand prediction model and an environment change prediction model of the vehicle on the basis of a preset algorithm architecture and each state information, and building a multi-objective optimization function of the whole vehicle and constraint conditions of the multi-objective optimization function according to the state information; And the collaborative management module is used for executing the whole vehicle thermal management collaborative operation according to each thermal load prediction model, each navigation working condition identification model, each power demand prediction model, each environment change prediction model, each whole vehicle multi-objective optimization function and each constraint condition thereof.
9. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, wherein the processor, when executing the program, implements the steps of the overall thermal management method of any of claims 1-7.
10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor performs the steps in the whole vehicle thermal management method as claimed in any one of claims 1-7.

Description

Whole vehicle thermal management method and device, electronic equipment and storage medium Technical Field The present invention relates to the field of vehicle technologies, and in particular, to a method and apparatus for thermal management of an entire vehicle, an electronic device, and a storage medium. Background With the rapid development of new energy commercial vehicles, the importance of a thermal management system as a key system affecting the energy efficiency of the whole vehicle, the service life of a battery and the riding comfort is increasingly highlighted. The traditional thermal management system adopts a discrete control mode, and the battery thermal management, the motor thermal management, the electric control thermal management and the cabin air conditioner independently operate, so that the cooperative optimization is lacked, and at least the following problems exist: 1. the energy utilization efficiency is low, each subsystem works independently, and effective heat transfer and utilization cannot be realized, for example, waste heat generated by a motor cannot be used for heating a passenger cabin or preheating a battery. 2. Control strategy conflicts control objectives for different subsystems may be contradictory, such as excessive compressor load when battery cooling demand and cabin cooling demand are present at the same time. 3. The system response is lagged, and the lack of predictive control can only passively respond to temperature changes, so that the energy consumption is increased and the comfort is reduced. Disclosure of Invention The invention aims to provide a whole vehicle heat management method, a device, electronic equipment and a storage medium, which at least can realize cooperative control of a plurality of heat management domains in a new energy commercial vehicle so as to realize multi-objective optimization of whole vehicle energy efficiency, system service life and response speed on the premise of ensuring temperature control precision of each domain, thereby being beneficial to ensuring driving experience of users. In order to solve the technical problems, in a first aspect, the present invention provides a whole vehicle thermal management method, which is at least used for a new energy commercial vehicle; The whole vehicle thermal management method at least comprises the following steps: At least acquiring battery domain state information, motor domain state information, electric control domain state information, cabin domain state information and whole vehicle running state information of a vehicle; On the basis of a preset algorithm architecture and each state information, at least establishing a battery domain heat load prediction model, a motor domain heat load prediction model, an electric control domain heat load prediction model, a cabin domain heat load prediction model, a navigation working condition recognition model, a power demand prediction model and an environment change prediction model of the vehicle, and constructing a multi-objective optimization function of the whole vehicle and constraint conditions thereof according to the state information; and executing the whole vehicle thermal management collaborative operation according to each thermal load prediction model, the navigation working condition identification model, the power demand prediction model, the environment change prediction model, the whole vehicle multi-objective optimization function and the constraint condition thereof. Based on the same conception, the second aspect of the invention also provides a whole vehicle thermal management device, which is used for executing the whole vehicle thermal management method of any one of the first aspect; The whole car heat management device at least comprises: the information acquisition module is at least used for acquiring battery domain state information, motor domain state information, electric control domain state information, cabin domain state information and whole vehicle running state information of the vehicle; The model building module is used for at least building a battery domain thermal load prediction model, a motor domain thermal load prediction model, an electric control domain thermal load prediction model, a cabin domain thermal load prediction model, a navigation working condition identification model, a power demand prediction model and an environment change prediction model of the vehicle on the basis of a preset algorithm architecture and each state information, and building a multi-objective optimization function of the whole vehicle and constraint conditions of the multi-objective optimization function according to the state information; And the collaborative management module is used for executing the whole vehicle thermal management collaborative operation according to each thermal load prediction model, each navigation working condition identification model, each power demand prediction model, each environme