Vehicle control device

Abstract

The present invention provides a vehicle control device that links a water circuit system for cooling or warming up a drive device of an electric vehicle with an air conditioning heat pump system and that efficiently controls these systems using predictive control, thereby capable of reducing the electric energy consumption of the electric vehicle. For example, the present invention is provided with a water circuit system and an air conditioning heat pump system, calculates the total heat generation amount of the drive device, predicts the heat dissipation amount of a radiator which is a component of the water circuit system to calculate the pump work of the water circuit system, calculates a required heat pump heat transport amount, which is a required air conditioning system cooling amount, from the difference between the total heat generation amount and the heat dissipation amount of the radiator, and calculates the compressor work of the air conditioning heat pump system.

Description

Vehicle control device

[0001] The present invention relates to a vehicle control device.

[0002] In recent years, the electrification of automobiles has progressed, and there is a need for more advanced thermal management systems to reduce the electricity costs of electric vehicles, such as electric vehicles and hybrid vehicles.In addition, it is becoming possible to perform predictive control of electric vehicles based on the use of external information provided by V2X, such as V2V (Vehicle-to-Vehicle, vehicle-to-vehicle communication), V2N (Vehicle-to-Network), and V2I (Vehicle-to-Infrastructure, vehicle-to-infrastructure communication).

[0003] Patent Document 1 discloses a technology that estimates the gradient of the road on which an electric vehicle is currently and will be traveling in the future, and increases the power of a cooling device that cools the motor and inverter when high output is required from the motor and inverter when climbing a slope.

[0004] JP 2013-158221 A

[0005] Patent Document 1 discloses a configuration for increasing the power of a cooling device that cools a motor and an inverter when high output is required from the motor and inverter when going uphill. However, there is a problem in that it does not take into consideration the detailed cooling method of the drive devices of an electric vehicle, such as the motor and inverter.

[0006] The present invention has been made in consideration of the above circumstances, and aims to provide a vehicle control device that links a water circuit system that cools or warms the drive unit of an electric vehicle with an air conditioning heat pump system, and efficiently controls these systems using look-ahead control, thereby reducing the electricity consumption of the electric vehicle.

[0007] In order to solve the above problems, a vehicle control device according to one aspect of the present invention is a vehicle including a heat medium circuit system having a pump that draws in and discharges a heat medium, and through which the heat medium circulates through electric devices of the vehicle, a refrigerant circuit system having a compressor that draws in and discharges a refrigerant, and constituting a heat pump system for air conditioning of the vehicle, and a heat exchanger that exchanges heat between the refrigerant and the heat medium to cool or heat the heat medium, the vehicle control device controls operation of at least one of the pump or the compressor, and performs temperature regulation control of the electric devices and the air conditioning, The control device includes a required torque prediction calculation unit that calculates the future required torque of the vehicle based on the future vehicle speed, road surface information, and vehicle weight of the vehicle; a heat quantity prediction calculation unit that calculates the total heat generation amount or the amount of heat rise of the electric devices of the vehicle based on the future vehicle speed and required torque of the vehicle; and a compressor work prediction calculation unit that calculates the required heat pump heat transport amount in the heat pump system based on the future vehicle speed of the vehicle, outside air temperature, and the total heat generation amount or the amount of heat rise of the electric devices of the vehicle, and calculates the work of the compressor based on the required heat pump heat transport amount.

[0008] According to one aspect of the present invention, for example, a water circuit system and an air conditioning heat pump system are provided, the total heat generation amount of the drive unit is calculated, the heat dissipation amount of the radiator, which is a component of the water circuit system, is predicted to calculate the pump work of the water circuit system, the required heat pump heat transport amount, which is the required air conditioning system cooling amount, is calculated from the difference between the total heat generation amount and the heat dissipation amount of the radiator, and the compressor work of the air conditioning heat pump system is calculated, so that by minimizing air conditioning usage, it is possible to reduce the electricity consumption of electric vehicles.

[0009] FIG. 1 is a block diagram showing the configuration of a main part of a vehicle control system according to an embodiment of the present invention. FIG. 1 is a diagram showing the configuration of a water circuit system and a refrigerant circuit system according to an embodiment of the present invention. FIG. 2 is a diagram showing paths when cooling an electric device and cooling a cabin in the configuration of a water circuit system and a refrigerant circuit system according to an embodiment of the present invention. FIG. 3 is a diagram showing paths when warming an electric device and heating a cabin in the configuration of a water circuit system and a refrigerant circuit system according to an embodiment of the present invention. FIG. 4 is a block diagram explaining data-driven modeling of an air conditioning cycle according to an embodiment of the present invention. FIG. 5 is a block diagram explaining data-driven modeling of an air conditioning cycle according to another embodiment of the present invention. FIG. 6 is a diagram showing an example of time series data of compressor work and expansion valve passage flow rate in an air conditioning cycle. FIG. 7 is a diagram showing calculation results of refrigerant pressures upstream and downstream of a compressor using a physical model and an NN model for an air conditioning cycle. FIG. 8 is a diagram showing calculation results of refrigerant temperatures upstream and downstream of a compressor and before and after an evaporator using a physical model and an NN model for an air conditioning cycle. FIG. 9 is a diagram showing calculation results of heat transfer amounts between a condenser and an evaporator using a physical model and an NN model for an air conditioning cycle. FIG. 10 is a diagram explaining a state space model of a vehicle model. FIG. 11 is a diagram explaining a state space model of a circuit temperature (water / device) model. FIG. 1 is a diagram illustrating a state space model of a radiator model. FIG. 2 is a diagram illustrating calculation of the total heat generation amount of devices in an electric vehicle. FIG. 3 is a flowchart of model predictive control of a vehicle control device according to an embodiment of the present invention. FIG. 4 is a block diagram illustrating model predictive cooling control by a radiator and air conditioning in a vehicle control device according to an embodiment of the present invention. FIG. 5 is a diagram illustrating the effect of model predictive cooling control. FIG. 6 is a block diagram illustrating model predictive warm-up control by device temperature rise and air conditioning in a vehicle control device according to an embodiment of the present invention. FIG. 7 is a diagram illustrating the effect of model predictive warm-up control. FIG. 8 is a block diagram illustrating the input / output relationship between an estimator and an observer. FIG. 9 is a diagram illustrating a method for describing an air conditioning system using a state space model. FIG. 10 is a diagram illustrating a Kalman filter algorithm and its flowchart. FIG. 11 is a block diagram illustrating the input / output relationship between an estimator and a controller. FIG. 12 is a block diagram illustrating the input / output relationship between an observer and a controller.1 is a diagram illustrating a calculation result of model predictive control of motor torque by looking ahead at vehicle speed behavior; FIG. 2 is a diagram illustrating a calculation result of model predictive control of motor torque by looking ahead at vehicle speed behavior and road surface inclination; and FIG. 3 is a diagram illustrating a difference in device temperature rise depending on whether look-ahead is performed or not.

[0010] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In this specification and the accompanying drawings, components having substantially the same functions or configurations are designated by the same reference numerals, and redundant description will be omitted.

[0011] FIG. 1 is a block diagram showing a schematic configuration of a main part of a vehicle control system 3 mounted on a vehicle 10 according to an embodiment of the present invention.

[0012] The vehicle control system 3 includes a thermal circuit system (also referred to as a thermal management system) 2, which includes a thermal circuit 11, a water circuit pump 12 (hereinafter may be simply referred to as the pump 12), a motor 13, a motor inverter 14 (hereinafter may be simply referred to as the inverter 14), a battery 15, a radiator 16, a DC / DC converter 17, a heating-side heat exchanger 18, a cooling-side heat exchanger 19, and an on-board charger 20 (hereinafter may be referred to as an OBC (On Board Charger) 20). The water circuit pump 12, the motor 13, the motor inverter 14, the battery 15, the radiator 16, the DC / DC converter 17, the heating-side heat exchanger 18, the cooling-side heat exchanger 19, and the on-board charger 20 are incorporated into the thermal circuit 11 by being connected by coolant piping 21 that constitutes the thermal circuit 11.

[0013] The vehicle 10 is an electric vehicle (electrically powered vehicle) that drives wheels with a motor 13. The motor 13 operates by receiving power from a battery 15. The motor inverter 14 is a motor drive device that supplies drive power to the motor 13. The drive of the motor 13 is controlled by the current generated by the motor inverter 14. The battery 15 is a high-voltage battery (e.g., 350 V) that supplies power to the motor 13. The battery 15 is charged with power supplied from a 200 V outlet and boosted by an on-board charger 20. The on-board charger 20 generates heat during boosting, and is therefore connected to a thermal circuit 11. In addition, a battery water temperature sensor 23 is provided downstream of the battery 15 in a coolant pipe 21, and the battery water temperature sensor 23 detects the temperature of the coolant downstream of the battery 15. The coolant temperature detected by the battery water temperature sensor 23 is transmitted to the vehicle control device 1.

[0014] The DC / DC converter 17 reduces the voltage of the power stored in the battery 15 and charges the 12V battery 24. The 12V battery 24 is a battery that stores power for operating the auxiliary equipment. The DC / DC converter 17 generates heat when reducing the voltage, and is therefore connected to a thermal circuit 11.

[0015] The radiator 16 is a heat dissipation device that dissipates heat stored in the refrigerant (coolant) in the coolant pipe 21. The radiator 16 is provided with a cooling fan 25. When the temperature of the coolant is higher than the outside air temperature, the cooling fan 25 rotates, and the radiator 16 dissipates heat from the coolant to the outside air through heat exchange. A radiator water temperature sensor 22 is provided downstream of the coolant pipe 21 from the radiator 16, and the radiator water temperature sensor 22 detects the temperature of the coolant at the outlet side of the radiator 16. The coolant temperature detected by the radiator water temperature sensor 22 is transmitted to the vehicle control device 1. The vehicle control device 1 increases or decreases the amount of heat dissipated by the radiator 16 by controlling the number of rotations (rotational speed) of the cooling fan 25 based on the received coolant temperature.

[0016] The water circuit pump 12 is provided upstream of the thermal circuit 11 with respect to the battery 15. The water circuit pump 12 is an electric water pump that circulates coolant through the coolant pipe 21 (thermal circuit 11). The water circuit pump 12 is driven by the rotation of the water pump driver, and draws in coolant stored in the reserve tank 26 and discharges it into the coolant pipe 21. The discharge rate of the coolant discharged by the water circuit pump 12 increases or decreases as the rotational speed of the pump motor is controlled by the vehicle control device 1.

[0017] The heating-side heat exchanger 18 and the cooling-side heat exchanger 19 are mounted on the vehicle 10 and provided in an air conditioning refrigerant circuit 35 ( FIG. 2 ) that utilizes the heat pump effect. The heating-side heat exchanger 18 exchanges heat with air conditioning refrigerant that has been pressurized (compressed) to a high temperature by a compressor 27 provided in the refrigerant circuit 35 ( FIG. 2 ). The cooling-side heat exchanger 19 exchanges heat with air conditioning refrigerant that has been expanded to a low temperature by an expansion valve or the like provided in the refrigerant circuit 35 ( FIG. 2 ). The discharge amount or discharge pressure of the refrigerant discharged from the compressor 27 increases or decreases by controlling the rotation speed (rotational speed) of the compressor motor by the vehicle control device 1.

[0018] The vehicle control device 1 is configured with an electronic control unit (ECU) consisting of a microcomputer equipped with a processor (CPU), a storage device, an input / output device, etc. The vehicle control device 1 acquires vehicle information such as vehicle weight from the vehicle 10, as well as outside-vehicle information such as road surface information based on V2X, such as the inclination angle (gradient angle) of the road surface. Based on the acquired information, the vehicle control device 1 controls the operation of at least one of the cooling fan 25, the water circuit pump 12, and the compressor 27 (details will be explained later).

[0019] Next, the configurations of the water circuit system 6 and the air conditioning refrigerant circuit system 5 in one embodiment of the present invention will be described using Figure 2. Note that in this embodiment, the heat medium that circulates through the electric devices of the vehicle 10 in the water circuit system 6 to cool or warm them is illustrated as a coolant (hereinafter, also referred to as "coolant"). However, the present invention is not limited to this, and a heat medium other than coolant may also be used.

[0020] The water circuit system 6 includes a water circuit 36, which is a path through which cooling water circulates. The water circuit 36 ​​includes a battery 15, an OBC 20, a DC / DC converter 17, an inverter 14, a motor 13, a pump 12, a capacitor 29, a switching valve 28, a radiator 16, a chiller 30, etc., and regulates the cooling and warming of the electric devices, such as the battery 15, the OBC 20, the DC / DC converter 17, the inverter 14, and the motor 13.

[0021] On the other hand, the refrigerant circuit system 5 includes a refrigerant circuit 35, which is a path through which the refrigerant circulates, and the refrigerant circuit 35 includes a compressor 27, a condenser 29, a chiller 30, an evaporator 31, an evaporator 32, a condenser 33, and expansion valves 37 to 39, and the evaporator 32 cools the cabin 34, and the condenser 33 heats the cabin 34, thereby controlling air conditioning. In other words, the refrigerant circuit system 5 constitutes a heat pump system for air conditioning the vehicle 10 (cabin 34).

[0022] Here, the condenser 29 and the chiller 30 are capable of exchanging heat between the water circuit 36 ​​and the refrigerant circuit 35, more specifically, between the cooling water circulating in the water circuit 36 ​​and the refrigerant circulating in the refrigerant circuit 35. The condenser 29 and the chiller 30 correspond to the heating-side heat exchanger 18 and the cooling-side heat exchanger 19 in FIG. 1, respectively.

[0023] The paths for cooling the electrically powered devices and the cabin will be described with reference to Fig. 3. The heat medium circulating in the water circuit 36 ​​is, for example, a coolant.

[0024] In the water circuit 36, the coolant discharged from the pump 12 is directed to the radiator 16 side by the switching valve 28. In the radiator 16, the coolant exchanges heat with the outside air to release the heat of the coolant, thereby lowering the temperature of the coolant. The radiator 16 then cools electrically powered devices such as the battery 15, OBC 20, DC / DC converter 17, inverter 14, and motor 13. If the radiator 16 is not cooling the coolant sufficiently, the chiller 30 provided downstream of the radiator 16 can transfer heat to the refrigerant circuit 35 side through heat exchange between the water circuit 36 ​​and the refrigerant circuit 35, thereby cooling the coolant.

[0025] Meanwhile, in the air conditioning refrigerant circuit 35, the refrigerant compressed by the compressor 27 passes through the condenser 29 and expands in the expansion valve 37 to lower its temperature, and the chiller 30, located downstream of the expansion valve 37, exchanges heat between the refrigerant circuit 35 and the water circuit 36 ​​to further cool the coolant in the water circuit 36, thereby promoting cooling of the electric devices. Also, the cabin 34 is cooled by the refrigerant that has expanded and lowered its temperature in the expansion valve 39, located downstream of the condenser 29 and upstream of the evaporator 32.

[0026] Next, the paths for warming up the electrically powered devices and heating the cabin will be described with reference to FIG.

[0027] In the water circuit 36, the coolant discharged from the pump 12 bypasses the radiator 16 and chiller 30 via the switching valve 28 and circulates through electric devices such as the battery 15, OBC 20, DC / DC converter 17, inverter 14, and motor 13, and is warmed up by the heat generated by the electric devices themselves. If the warming up of the electric devices is insufficient due to the heat generated by the electric devices themselves, the capacitor 29 exchanges heat between the water circuit 36 ​​and the refrigerant circuit 35, allowing the coolant to receive heat from the refrigerant circuit 35, thereby accelerating the warming up of the electric devices.

[0028] Meanwhile, in the air conditioning refrigerant circuit 35, the refrigerant compressed by the compressor 27 and heated to a high temperature is transferred to the coolant in the water circuit 36 ​​through heat exchange between the refrigerant circuit 35 and the water circuit 36 ​​in the condenser 29, thereby facilitating the warming up of the electric devices. Also, the cabin 34 is heated by the condenser 33, and heat is absorbed from the outside air by the evaporator 31 through an expansion valve 38 provided downstream of the condenser 33 and upstream of the evaporator 31.

[0029] An example of data-driven modeling of an air conditioning cycle will be described with reference to FIG.

[0030] The vehicle control device 1 constructs a state space model from a state equation that takes as input the compressor work of the air conditioning cycle (heat pump system), the flow rate through the expansion valve, the outside temperature, and the current values ​​of the pressure upstream and downstream of the compressor, and outputs the differential value or future value of the pressure upstream and downstream of the compressor, and an observation equation that calculates the heat transfer amount of the evaporator and condenser, which are components of the air conditioning cycle (heat pump system), based on the compressor work, the flow rate through the expansion valve, the outside temperature, and the differential value or future value of the pressure upstream and downstream of the compressor, and approximates the state equation and the observation equation using a neural network (NN) model to model them as mathematical model A and mathematical model B, respectively. In other words, the vehicle control device 1 includes a mathematical model A that calculates differential values ​​or future values ​​of the pressure upstream and downstream of the compressor based on the compressor work of the heat pump system, the flow rate through the expansion valve, the outside temperature, and the current values ​​of the pressure upstream and downstream of the compressor, and a mathematical model B that calculates the heat transfer amount of the evaporator and the condenser, which are components of the heat pump system, based on the compressor work, the flow rate through the expansion valve, the outside temperature, and the differential values ​​or future values ​​of the pressure upstream and downstream of the compressor, and uses neural network (NN) models for mathematical model A and mathematical model B. k are the compressor upstream pressure and compressor downstream pressure, and the input variable u k is the compressor work, the flow rate through the expansion valve, and the external input d k is the outside temperature, and the output variable y k are the refrigerant temperatures (before and after the condenser, before and after the evaporator), the condenser heat transfer amount, and the evaporator heat transfer amount, the state space model is described by the following equation (1) as a state equation and an observation equation.

[0031] Similarly, another example of data-driven modeling of an air conditioning cycle will be described with reference to FIG.

[0032] The vehicle control device 1 constructs a state space model from a state equation that takes as input the compressor work of the air conditioning cycle (heat pump system), outside air temperature, and the current values ​​of the compressor's upstream pressure and the differential pressure before and after the compressor, and outputs the differential value or future value of the compressor's upstream pressure and the differential pressure before and after, and an observation equation that calculates the heat transfer amount of the evaporator and condenser, which are components of the air conditioning cycle (heat pump system), based on the compressor work, outside air temperature, and the differential value or future value of the compressor's upstream pressure and the differential pressure before and after, and approximates the state equation and observation equation using an NN model, and models them as mathematical model A and mathematical model B, respectively. In other words, the vehicle control device 1 includes a mathematical model A that calculates the differential values ​​or future values ​​of the upstream pressure of the compressor and the differential pressure before and after the compressor based on the compressor work of the heat pump system, the outside air temperature, and the current values ​​of the upstream pressure of the compressor and the differential pressure before and after the compressor, and a mathematical model B that calculates the heat transfer amount of the evaporator and the condenser, which are components of the heat pump system, based on the compressor work, the outside air temperature, and the differential values ​​or future values ​​of the upstream pressure of the compressor and the differential pressure before and after the compressor, and uses neural network (NN) models for mathematical model A and mathematical model B. k is the compressor upstream pressure, the differential pressure before and after the compressor, and the input variable u k is the compressor work, and the exogenous input d k is the outside temperature, and the output variable y k are the refrigerant temperatures (before and after the condenser, before and after the evaporator), the condenser heat transfer amount, and the evaporator heat transfer amount, the state space model is described by the above equation (1) as a state equation and an observation equation, similar to FIG. 5 .

[0033] Next, an example of calculation results using data-driven modeling of an air conditioning cycle is shown. Figure 7 shows an example of time-series data for the compressor work and the flow rate through the expansion valve in an air conditioning cycle. Figure 8 shows the results of time-series data for refrigerant pressure upstream and downstream of the compressor. It compares the results calculated using a physical model with those calculated using a neural network model according to an embodiment of the present invention, demonstrating that the neural network model reproduces the results of the physical model. Figure 9 compares the results calculated using a physical model with those calculated using a neural network model for time-series data for refrigerant temperature upstream and downstream of the condenser and before and after the evaporator. The results of the neural network model closely approximate the results of the physical model. Figure 10 compares the results calculated using a physical model and a neural network model for the heat transfer rate between the condenser and the evaporator. It shows good agreement between the two. The compressor work also captures the trend shown in Figure 7.

[0034] The state space model of the vehicle model will be described with reference to FIG. k is the motor rotation speed, and the input variable u k is the motor torque, and the external input d k is the vehicle weight and the tilt angle, and the output variable y k When the vehicle speed is represented by the vehicle speed, the state space model is described by the above equation (1) as a state equation and an observation equation.

[0035] Similarly, the state space model of the circuit temperature (water / device) model will be explained using FIG. 12. State variable x k is the cooling water temperature of each part, and the input variable u k are the cooling water pump work, the heat generation amount of the device, the heat radiation amount of the radiator, the heat exchange amount of the air conditioning refrigerant (heating side), and the heat exchange amount of the air conditioning refrigerant (cooling side), and the external input d k is the outside air temperature, and the output variable y k is the representative cooling water temperature, the state space model is described by the above equation (1) as a state equation and an observation equation.

[0036] Next, the state space model of the radiator model will be described with reference to FIG. 13. The state variable x k is the radiator temperature, and the input variable u kis the cooling water flow rate (pump work), and the exogenous input d k are the vehicle speed, outside air temperature, radiator inlet water temperature, and radiator fan flow rate, and the output variable y k If θ is the radiator outlet water temperature and θ is the radiator heat radiation amount, the state space model is similarly described by the above equation (1) as a state equation and an observation equation.

[0037] Calculation of the total device heat value of an electric vehicle will be described using Figure 14. The vehicle control device 1 calculates the motor heat value, inverter heat value, battery heat value, OBC heat value, and DC / DC converter heat value from the motor rotation speed and torque, and adds these values ​​together to calculate the total device heat value of the electric vehicle (total heat value of electric devices).

[0038] FIG. 15 shows a flowchart of the model predictive control of the vehicle control device 1.

[0039] In S801, road surface information (inclination angle) and vehicle weight are acquired. The road surface information (inclination angle) can be acquired, for example, from image information of the surroundings of the electric vehicle acquired by an on-board camera, map information stored in a storage device, or information acquired or stored by an external device. Then, in S802, the future vehicle speed of the electric vehicle (after a predetermined time) is calculated, and in S803, the future required torque is calculated. Based on this, in S804, the total heat generation amount of the drive unit (electric device) is calculated. Furthermore, in S805, the outside air temperature is acquired, and in S806, the future maximum heat exchange amount (= maximum heat dissipation amount) of the radiator is predicted. In S807, if the value obtained by subtracting the maximum heat exchange amount of the radiator from the total heat generation amount is negative, the maximum heat exchange amount of the radiator is greater than the total heat generation amount, and therefore, in S808, the pump work of the water circuit system is calculated. On the other hand, if the value obtained by subtracting the maximum heat exchange amount of the radiator from the total heat generation amount is not negative in S807, the total heat generation amount is equal to or greater than the maximum heat exchange amount of the radiator, so in S809 the pump work of the water circuit system is maximized, in S810 the required heat pump heat transport amount (required air conditioning system cooling amount) of the refrigerant circuit system (heat pump system) is calculated, and in S811 the compressor work of the refrigerant circuit system (heat pump system) is calculated.

[0040] 16 will be used to explain model predictive cooling control by the radiator and air conditioning of the vehicle control device 1. The vehicle control device 1 includes, as functional blocks for executing this model predictive cooling control, a vehicle MPC (Model Predictive Control) unit 101 as a required torque prediction calculation unit, a total heat generation amount prediction calculation unit 102 as a heat amount prediction calculation unit, an MPC unit 103 for the pump of the water circuit system as a pump work prediction calculation unit, a heat radiation amount prediction calculation unit 104 as a heat exchange amount prediction calculation unit, and an MPC unit 105 for the compressor of the air conditioning system as a compressor work prediction calculation unit.

[0041] The vehicle control device 1 performs optimization while predicting future responses based on the electric vehicle's future speed and road inclination angle readout information and vehicle weight using V2X using the vehicle's MPC unit (required torque prediction calculation unit) 101, thereby determining the future required torque and rotation speed of the motor. Next, a total heat generation amount prediction calculation unit (heat amount prediction calculation unit) 102 predicts the total heat generation amount of the electric vehicle's future drive unit (electric device) based on the electric vehicle's future speed and the motor's future required torque and rotation speed. Next, a pump MPC unit (pump work prediction calculation unit) 103 of the water circuit system calculates pump work based on a target cooling amount for the total heat generation amount, the electric vehicle's future vehicle speed, and outside air temperature. Furthermore, a heat release amount prediction calculation unit (heat exchange amount prediction calculation unit) 104 predicts the (maximum) future heat release amount (heat exchange amount) of the radiator based on the electric vehicle's future vehicle speed and outside air temperature. Then, the MPC section (compressor work prediction calculation section) 105 of the compressor of the air conditioning system calculates the required heat pump heat transport amount (required air conditioning system cooling amount) of the air conditioning system from the difference between the target cooling amount for the total heat generation amount calculated by the total heat generation amount prediction calculation section 102 and the future heat radiation amount (heat exchange amount) of the radiator calculated by the heat radiation amount prediction calculation section 104, and calculates the compressor work based on the required heat pump heat transport amount (required air conditioning system cooling amount) of the air conditioning system.

[0042] Here, if the future heat radiation amount (heat exchange amount) of the radiator calculated by the heat radiation amount prediction calculation unit 104 is greater than the target cooling amount for the total heat generation amount calculated by the total heat generation amount prediction calculation unit 102, the target cooling amount can be achieved by the heat radiation of the radiator alone, so the MPC unit (pump work prediction calculation unit) 103 of the pump in the water circuit system will calculate the pump work according to the target cooling amount for the total heat generation amount calculated by the total heat generation amount prediction calculation unit 102. On the other hand, if the target cooling amount for the total heat generation amount calculated by the total heat generation amount prediction calculation unit 102 is equal to or greater than the future heat generation amount (heat exchange amount) of the radiator calculated by the heat radiation amount prediction calculation unit 104, the target cooling amount cannot be achieved by the heat radiation of the radiator alone; in other words, the cooling amount by the heat radiation of the radiator alone is insufficient for the target cooling amount. Therefore, the MPC unit (pump work prediction calculation unit) 103 of the pump in the water circuit system maximizes the pump work, and the MPC unit (compressor work prediction calculation unit) 105 of the compressor in the air conditioning system calculates the required heat pump heat transport amount (required air conditioning system cooling amount) of the air conditioning system from the difference between the target cooling amount for the total heat generation amount calculated by the total heat generation amount prediction calculation unit 102 as described above and the future heat generation amount (heat exchange amount) of the radiator calculated by the heat radiation amount prediction calculation unit 104, and calculates the compressor work.

[0043] The vehicle control device 1 controls the operation of the pump 12 based on the pump work calculated by the MPC unit (pump work prediction calculation unit) 103 of the pump in the water circuit system, and controls the operation of the compressor 27 based on the compressor work calculated by the MPC unit (compressor work prediction calculation unit) 105 of the compressor in the air conditioning system, thereby enabling efficient control of the electric devices of the electric vehicle and the temperature regulation (cooling) of the air conditioning.

[0044] The effects of model predictive cooling control will be explained using Figure 17. Without model predictive control, for example, cooling is performed by setting the pump work and compressor work at equal rates. In contrast, with model predictive cooling control, the proportion of pump work, which has a large effect on device cooling, is increased, and the proportion of compressor work, which has a small effect on device cooling, is decreased. This reduces air conditioning usage, making it possible to reduce the overall energy consumption required for equivalent cooling.

[0045] 18 will be used to explain model predictive warm-up control using device temperature rise and air conditioning in the vehicle control device 1. The vehicle control device 1 includes, as functional blocks for executing this model predictive warm-up control, a vehicle MPC unit 101 serving as a required torque prediction calculation unit, a device temperature rise heat quantity prediction calculation unit 106 serving as a heat quantity prediction calculation unit, a temperature estimation unit 107, a required heat quantity calculation unit 108, and an air conditioning system compressor MPC unit 105 serving as a compressor work prediction calculation unit.

[0046] The vehicle control device 1 uses the vehicle's MPC unit (required torque prediction calculation unit) 101 to calculate the future required torque and rotation speed of the motor based on the vehicle weight and forward-looking information on the electric vehicle's future speed and road inclination angle using V2X. Next, a device temperature rise heat amount prediction calculation unit (heat amount prediction calculation unit) 106 predicts the device temperature rise heat amount, which is the amount of heat rise in the electric devices of the electric vehicle, based on the electric vehicle's future speed and the motor's future required torque and rotation speed. A temperature estimation unit 107 estimates the temperatures of the coolant in the water circuit system and the electric devices based on a target heat amount for the device temperature rise heat amount, the electric vehicle's future speed, and the outside air temperature. Based on the estimated temperatures of the coolant in the water circuit system and the electric devices, a required heat amount calculation unit 108 calculates the required heat amounts of the coolant in the water circuit system and the electric devices. Then, the MPC section (compressor work prediction calculation section) 105 of the compressor of the air conditioning system calculates the required heat pump heat transport amount (required air conditioning system heat transport amount) of the air conditioning system from the difference between the target heat transport amount for the device heat rise calculated by the device heat rise heat amount prediction calculation section 106 and the required heat transport amount calculated by the required heat amount calculation section 108, and calculates the compressor work based on the required heat pump heat transport amount (required air conditioning system heat transport amount) of the air conditioning system.

[0047] The vehicle control device 1 controls the operation of the compressor 27 based on the compressor work calculated by the MPC section (compressor work prediction calculation section) 105 of the compressor of the air conditioning system, thereby enabling efficient control of the electric devices of the electric vehicle and the temperature regulation (warm-up) of the air conditioning.

[0048] The effect of model predictive warm-up control will be explained using Figure 19. Without model predictive control, for example, warm-up is performed by equating the ratio of device heat generation to compressor work. In contrast, with model predictive warm-up control, the ratio of compressor work, which has little effect on warm-up, is reduced, and the ratio of warm-up that relies on the heat generated by the device itself is increased. This reduces air conditioning usage and makes it possible to reduce the overall energy consumption required for warm-up.

[0049] Fig. 20 is a block diagram illustrating the input / output relationship between an estimator and an observer. The estimator derives output variables from internal state variable model constants for input variables. In contrast, the observer receives inputs consisting of input variables, output variables (sensor detection values), and model constants, and outputs state variables. One method for achieving this is the Kalman filter.

[0050] 21 is a diagram for explaining a method for describing an air conditioning system using a state space model. The time derivative of the state variable is defined as a discrete equation according to Euler's first-order forward difference as shown in the following equation (2). Here, the upper right subscript k represents the current value when discretized on the time axis. Here, a first-order accuracy forward difference is used, but the present invention is not limited to this. Discretization is performed according to equation (2) and described by the state space model of the following equation (3). where A, B, and C are matrices. k is the state variable vector, u k is the input variable vector, y k are output variable vectors, which are given by the following equation (4) (also see FIG. 21). The state equation is arranged in a state space model, and the vector defined by equation (4) is passed to the Kalman filter processing.

[0051] 22 is a diagram illustrating a Kalman filter algorithm and its flowchart. While the system of this embodiment employs a linear Kalman filter algorithm, the present invention is not limited to this. In other words, similar effects can be achieved by applying an extended Kalman filter, known as a nonlinear Kalman filter, or an ensemble Kalman filter. Regarding the Kalman filter, which is one of the components of cylinder-specific air-fuel ratio correction control, the algorithm and a method for applying it to this control will be described.

[0052] In a Kalman filter, the controlled object is described by a state equation, and sensor measurement information is specified as the output variable of the state equation. Then, internal state variables that cannot be directly measured are estimated based on the sensor measurement information specified as the output variable.

[0053] When executing the Kalman filter, in S901, it is determined whether or not the Kalman filter can be executed. The sensor state and the prediction range of the assumed state equation are taken into consideration as indicators for determining whether or not the Kalman filter can be executed. The specific calculation formulas executed in S902 to S906 are shown below.

[0054] The Kalman filter is based on a state equation including the system noise Q and the observation noise R defined by the following equation (5). Here, (k) means the current value of the discrete time.

[0055] The Kalman filter is divided into a prediction step and a filtering step. In the prediction step, the internal state variable vector x and the covariance matrix P are updated based on the input variables and the system noise Q using the following equation (6) (S902, S903).

[0056] Next, in the filtering step, the Kalman gain K defined by the updated covariance matrix P and the observation noise R is calculated by the following equation (7) (S904).

[0057] Using the Kalman gain K and the observation data, the internal state variable vector x and the covariance matrix P are updated again by the following equation (8). In this way, the internal state variable vector x and the covariance matrix P are corrected using the actual observation data (S905, S906).

[0058] From the above calculations, the compressor inlet and outlet refrigerant pressures of the internal state variable x(k|k), which are difficult to measure directly, can be estimated based on measurable observation data information. The internal state variables output from the Kalman filter are used for state feedback control.

[0059] FIG. 23 is a block diagram illustrating the input / output relationship between an estimator and a controller. The estimator calculates output variables based on input variables, internal state variable model constants, and static and dynamic characteristics defined by these model constants. This makes it possible to estimate the output behavior and internal state behavior relative to the input. While the estimator describes the controlled object as a forward problem, the control model must solve an inverse problem. In other words, the controller inputs output variables (control targets) as target values ​​and outputs input variables (control signals) to achieve them, and model predictive control is a method for achieving this.

[0060] Fig. 24 is a block diagram showing the input / output relationship between the observer and the controller. As can be clearly seen by referring to Fig. 20 and Fig. 23 together, the input variables, output variables (sensor detection values), and model constants are used as inputs to the observer to determine state variables using a Kalman filter, and the state variables, output variables (control targets), and model constants are used as inputs to the controller to derive input variables (control signals) using model predictive control.

[0061] FIG. 25 shows vehicle speed behavior prediction. FIG. 25(a) shows the state of vehicle speed behavior prediction. The vehicle speed, i.e., motor rotation speed, fluctuates by predicting the current value. FIG. 25(b) shows the inclination angle of the road surface as road surface information, but in this case, there is no inclination. FIG. 25(c) shows the state of motor torque prediction by MPC (model predictive control) from the predicted motor rotation speed.

[0062] Similarly, Figure 26 shows vehicle speed behavior + road surface inclination look-ahead. Figure 26(a) shows the state of look-ahead vehicle speed behavior. The vehicle speed, i.e., motor rotation speed, changes with the current value read-ahead. Figure 26(b) shows the road surface inclination angle as road surface information. The inclination angle changes from a -2 degree downhill slope to a +2 degree uphill slope, and this is also looked-ahead. Figure 26(c) shows motor torque prediction using MPC (model predictive control) from the looked-ahead motor rotation speed and inclination angle.

[0063] As described above, the motor rotation speed and motor torque are predicted from the vehicle speed prediction information and tilt angle prediction information, and the device heat generation amount, temperature, and water temperature are predicted from the predicted motor rotation speed and torque information. This information is used to perform model predictive control of the pump 12 of the water circuit system 6 and the compressor 27 of the air conditioning refrigerant circuit system 5.

[0064] 27 is a diagram illustrating the difference in device temperature rise with and without read-ahead. With read-ahead, a rise in device temperature is predicted from the read-ahead information, and cooling is promoted in advance to keep the rise in device temperature below the device upper limit temperature. However, without read-ahead, device cooling is delayed, and the device temperature exceeds the device upper limit temperature, leading to a decrease in device performance.

[0065] As described above, the vehicle control device 1 of the present embodiment is configured to control the operation of at least one of the pump 12 or the compressor 27 in a vehicle (thermal management system 2) that includes a heat medium circuit system (water circuit system 6) that has a pump 12 that draws in and discharges a heat medium (coolant) and through which the heat medium (coolant) circulates through electric devices of the vehicle (battery 15, OBC 20, DC / DC converter 17, inverter 14, motor 13), a refrigerant circuit system 5 that has a compressor 27 that draws in (compresses) and discharges a refrigerant and constitutes a heat pump system for air conditioning of the vehicle, and heat exchangers (chiller 30 that is a cooling-side heat exchanger 19, condenser 29 that is a heating-side heat exchanger 18) that exchange heat between the refrigerant and the heat medium to cool or heat the heat medium, and controls the operation of at least one of the pump 12 or the compressor 27 to control the temperature of the electric devices and the air conditioning. a required torque prediction calculation unit (vehicle MPC unit 101) that calculates a future required torque of the vehicle based on the future vehicle speed of the vehicle, road surface information (inclination angle), and vehicle weight; a heat amount prediction calculation unit (total heat amount prediction calculation unit 102, device heat amount rise prediction calculation unit 106) that calculates a total heat generation amount or a heat amount of temperature rise of the electric devices of the vehicle based on the future vehicle speed and required torque of the vehicle; and a compressor work prediction calculation unit (compressor MPC unit 105) that calculates a required heat pump heat transport amount in the heat pump system based on the future vehicle speed of the vehicle, outside air temperature, and the total heat generation amount or the heat amount of temperature rise of the electric devices of the vehicle, and calculates the work of the compressor 27 based on the required heat pump heat transport amount.

[0066] The vehicle control device 1 further includes a heat exchange amount prediction calculation unit (heat dissipation amount prediction calculation unit 104) that calculates a future heat exchange amount (heat dissipation amount) of a radiator 16 that exchanges heat between the heat medium (coolant) and outside air in the heat medium circuit system (water circuit system 6) based on the future vehicle speed and outside air temperature of the vehicle, and a pump work prediction calculation unit (pump MPC unit 103) that calculates the work of the pump 12 based on the total heat generation amount of the electric devices and the future heat exchange amount (heat dissipation amount) of the radiator 16, and the compressor work prediction calculation unit (compressor MPC unit 105) calculates the required heat pump heat transport amount using the difference between the total heat generation amount of the electric devices and the future heat exchange amount (heat dissipation amount) of the radiator 16.

[0067] The vehicle control device 1 further includes a temperature estimation unit 107 that estimates the future temperatures of the heat medium (coolant) and the electric devices based on the future vehicle speed and outside air temperature of the vehicle, and a required heat amount calculation unit 108 that calculates the required heat amounts of the heat medium (coolant) and the electric devices based on the future temperatures of the heat medium (coolant) and the electric devices, and the compressor work prediction calculation unit (compressor MPC unit 105) calculates the required heat pump heat transport amount based on the difference between the heat amount of temperature rise of the electric devices and the required heat amount.

[0068] That is, the vehicle control device 1 of this embodiment includes a heat medium circuit system (water circuit system 6) that has a pump 12 that draws in and discharges a heat medium (coolant), and the heat medium (coolant) circulates through the vehicle's electric devices (battery 15, OBC 20, DC / DC converter 17, inverter 14, motor 13) to cool or warm up the vehicle's electric devices, a refrigerant circuit system 5 that has a compressor 27 that draws in (compresses) and discharges a refrigerant, and that constitutes a heat pump system for air conditioning of the vehicle, and a compressor 27 that draws in (compresses) and discharges the refrigerant. In a vehicle (thermal management system 2) including a heat exchanger (a chiller 30 which is a cooling-side heat exchanger 19, and a condenser 29 which is a heating-side heat exchanger 18) which exchanges heat with the heat medium to cool or heat the heat medium, a vehicle control device 1 controls the operation of at least one of the pump 12 or the compressor 27 and performs temperature control (cooling and warming control) of the electric device and the air conditioning, and the vehicle control device 1 calculates a temperature of the vehicle based on a future vehicle speed, road surface information (inclination angle), and vehicle weight. a required torque prediction calculation unit (vehicle MPC unit 101) that calculates a future required torque of the vehicle; a total heat generation amount prediction calculation unit 102 that calculates a total heat generation amount of the electric devices of the vehicle based on the future vehicle speed and required torque of the vehicle; a heat exchange amount prediction calculation unit (heat radiation amount prediction calculation unit 104) that calculates a future heat exchange amount (heat radiation amount) of a radiator 16 that exchanges heat between the heat medium (coolant) and outside air in the heat medium circuit system (water circuit system 6) based on the future vehicle speed and outside air temperature of the vehicle; The heat pump system includes a pump work prediction calculation unit (pump MPC unit 103) that calculates the work of the pump 12 based on the heat quantity and the future heat exchange quantity (heat radiation quantity) of the radiator 16, and a compressor work prediction calculation unit (compressor MPC unit 105) that calculates a required heat pump heat transport quantity in the heat pump system based on the difference between the total heat quantity of the electric devices and the future heat exchange quantity (heat radiation quantity) of the radiator 16, and calculates the work of the compressor 27 based on the required heat pump heat transport quantity.

[0069] The vehicle control device 1 of the present embodiment is a vehicle (thermal management system 2) that includes a heat medium circuit system (water circuit system 6) having a pump 12 that draws in and discharges a heat medium (coolant), and in which the heat medium (coolant) circulates through electric devices of the vehicle (battery 15, OBC 20, DC / DC converter 17, inverter 14, motor 13), a refrigerant circuit system 5 that has a compressor 27 that draws in (compresses) and discharges a refrigerant, and that constitutes a heat pump system for air conditioning of the vehicle, and heat exchangers (chiller 30 that is a cooling-side heat exchanger 19, condenser 29 that is a heating-side heat exchanger 18) that exchange heat between the refrigerant and the heat medium to cool or heat the heat medium, and the vehicle control device 1 controls operation of at least one of the pump 12 or the compressor 27 to perform temperature control (cooling and warming control) of the electric devices and the air conditioning, and the vehicle control device 1 determines a future vehicle speed of the vehicle and The heat pump system includes a required torque prediction calculation unit (vehicle MPC unit 101) that calculates a future required torque of the vehicle based on road surface information (inclination angle) and vehicle weight; a device temperature rise heat amount prediction calculation unit 106 that calculates a temperature rise heat amount of the electric devices of the vehicle based on the future vehicle speed and required torque of the vehicle; a temperature estimation unit 107 that estimates the future temperatures of the heat medium (coolant) and the electric devices based on the future vehicle speed of the vehicle and outside air temperature; a required heat amount calculation unit 108 that calculates a required heat amount of the heat medium (coolant) and the electric devices based on the future temperatures of the heat medium (coolant) and the electric devices; and a compressor work prediction calculation unit (compressor MPC unit 105) that calculates a required heat pump heat transport amount in the heat pump system using the difference between the temperature rise heat amount of the electric devices and the required heat amount, and calculates the work of the compressor 27 based on the required heat pump heat transport amount.

[0070] The vehicle control device 1 of this embodiment also includes a mathematical model A that calculates a differential value or a future value of the pressure upstream and downstream of the compressor based on the compressor work of the heat pump system, the flow rate through an expansion valve, the outside temperature, and the current values ​​of the pressure upstream and downstream of the compressor, and a mathematical model B that calculates the heat transfer amount of the evaporator and the condenser, which are components of the heat pump system, based on the compressor work, the flow rate through an expansion valve, the outside temperature, and the differential value or the future values ​​of the pressure upstream and downstream of the compressor. Neural network models are used for mathematical models A and B.

[0071] The vehicle control device 1 of this embodiment also includes a mathematical model A that calculates a differential value or a future value of the upstream pressure of the compressor and the differential pressure before and after the compressor based on the compressor work of the heat pump system, an outside air temperature, and current values ​​of the upstream pressure of the compressor and the differential pressure before and after the compressor, and a mathematical model B that calculates the heat transfer amount of an evaporator and a condenser that are components of the heat pump system based on the compressor work, the outside air temperature, and the differential value or the future value of the upstream pressure of the compressor and the differential pressure before and after the compressor. Neural network models are used for the mathematical models A and B.

[0072] According to this embodiment, for example, a water circuit system and an air conditioning heat pump system are provided, the total heat generation amount of the drive unit is calculated, the heat radiation amount of the radiator, which is a component of the water circuit system, is predicted to calculate the pump work of the water circuit system, the required heat pump heat transport amount, which is the required air conditioning system cooling amount, is calculated from the difference between the total heat generation amount and the heat radiation amount of the radiator, and the compressor work of the air conditioning heat pump system is calculated, so that by minimizing air conditioning usage, it is possible to reduce the electricity consumption of electric vehicles.

[0073] It should be noted that the present invention is not limited to the above-described embodiment, and includes various modifications. For example, the above-described embodiment has been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to an embodiment having all of the described configurations.

[0074] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software, with a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0075] In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected.

[0076] REFRIGERATION VALVEHICLE 1 Vehicle control device 2 Thermal circuit system (thermal management system) 3 Vehicle control system 5 Refrigerant circuit system 6 Water circuit system (heat medium circuit system) 10 Vehicle (electric vehicle) 12 Pump 18 Heating side heat exchanger 19 Cooling side heat exchanger 27 Compressor 28 Switching valve 29 Condenser 30 Chiller 35 Refrigerant circuit 36 ​​Water circuit 37, 38, 39 Expansion valve 101 Vehicle MPC unit (required torque prediction calculation unit) 102 Total heat generation amount prediction calculation unit (heat amount prediction calculation unit) 103 Pump MPC unit (pump work prediction calculation unit) 104 Heat release amount prediction calculation unit (heat exchange amount prediction calculation unit) 105 Compressor MPC unit (compressor work prediction calculation unit) 106 Device temperature rise heat amount prediction calculation unit (heat amount prediction calculation unit) 107 Temperature estimation unit 108 Required heat amount calculation unit

Claims

1. A vehicle equipped with a heat medium circuit system having a pump that draws in and discharges a heat medium, the heat medium circulating through electric devices of the vehicle; a refrigerant circuit system having a compressor that draws in and discharges a refrigerant, constituting a heat pump system for air conditioning of the vehicle; and a heat exchanger that exchanges heat between the refrigerant and the heat medium to cool or heat the heat medium, the vehicle control device controlling the operation of at least one of the pump or the compressor and performing temperature control of the electric devices and the air conditioning, the vehicle control device comprising: a required torque prediction calculation unit that calculates a future required torque of the vehicle based on the future vehicle speed, road surface information, and vehicle weight of the vehicle; and a heat amount prediction calculation unit that calculates a total heat amount or a temperature rise heat amount of the electric devices of the vehicle based on the future vehicle speed and required torque of the vehicle. a compressor work prediction calculation unit that calculates a required heat pump heat transport amount in the heat pump system based on the future vehicle speed of the vehicle, the outside air temperature, and the total heat generation amount or the amount of heat rise of the electric devices of the vehicle, and calculates the work of the compressor based on the required heat pump heat transport amount.

2. The vehicle control device according to claim 1, further comprising: a heat exchange amount prediction calculation unit that calculates a future heat exchange amount of a radiator that exchanges heat between the heat medium and outside air in the heat medium circuit system based on the future vehicle speed and outside air temperature of the vehicle; and a pump work prediction calculation unit that calculates the work of the pump based on the total heat generation amount of the electric devices and the future heat exchange amount of the radiator, wherein the compressor work prediction calculation unit calculates the required heat pump heat transport amount using the difference between the total heat generation amount of the electric devices and the future heat exchange amount of the radiator.

3. The vehicle control device according to claim 1, further comprising: a temperature estimation unit that estimates future temperatures of the heat medium and the electric device based on the future speed of the vehicle and the outside air temperature; and a required heat amount calculation unit that calculates the required heat amount of the heat medium and the electric device based on the future temperatures of the heat medium and the electric device, wherein the compressor work prediction calculation unit calculates the required heat pump heat transport amount based on the difference between the heat amount of the temperature rise of the electric device and the required heat amount.

4. A vehicle equipped with a heat medium circuit system having a pump that draws in and discharges a heat medium, the heat medium circulating through electric devices of the vehicle to cool or warm the electric devices of the vehicle, a refrigerant circuit system having a compressor that draws in and discharges a refrigerant, constituting a heat pump system for air conditioning of the vehicle, and a heat exchanger that cools or heats the heat medium by heat exchange between the refrigerant and the heat medium, the vehicle control device controlling the operation of at least one of the pump or the compressor and performing temperature control of the electric devices and the air conditioning, the vehicle control device comprising: a required torque prediction calculation unit that calculates a future required torque of the vehicle based on the future vehicle speed, road surface information, and vehicle weight of the vehicle; a total heat amount prediction calculation unit that calculates a total heat amount of the electric devices of the vehicle based on the future vehicle speed and required torque of the vehicle; and a heat exchange amount prediction calculation unit that calculates a future heat exchange amount of a radiator that exchanges heat between the heat medium and outside air in the heat medium circuit system based on the future vehicle speed and outside air temperature of the vehicle. a pump work prediction calculation unit that calculates the work of the pump based on the total heat generation amount of the electric devices and the future heat exchange amount of the radiator; and a compressor work prediction calculation unit that calculates a required heat pump heat transport amount in the heat pump system using the difference between the total heat generation amount of the electric devices and the future heat exchange amount of the radiator, and calculates the work of the compressor based on the required heat pump heat transport amount.

5. A vehicle equipped with a heat medium circuit system having a pump that draws in and discharges a heat medium, and through which the heat medium circulates through electric devices of the vehicle; a refrigerant circuit system having a compressor that draws in and discharges a refrigerant, constituting a heat pump system for air conditioning of the vehicle; and a heat exchanger that exchanges heat between the refrigerant and the heat medium to cool or heat the heat medium, the vehicle control device controls the operation of at least one of the pump or the compressor and performs temperature control of the electric devices and the air conditioning, the vehicle control device comprising: a required torque prediction calculation unit that calculates a future required torque of the vehicle based on the future vehicle speed, road surface information, and vehicle weight of the vehicle; a device temperature rise heat amount prediction calculation unit that calculates a temperature rise heat amount of the electric devices of the vehicle based on the future vehicle speed and required torque of the vehicle; a temperature estimation unit that estimates the future temperatures of the heat medium and the electric devices based on the future vehicle speed and outside air temperature of the vehicle; and a required heat amount calculation unit that calculates a required heat amount of the heat medium and the electric devices based on the future temperatures of the heat medium and the electric devices. a compressor work prediction calculation unit that calculates a required heat pump heat transport amount in the heat pump system based on the difference between the heat amount of the electric device that has risen in temperature and the required heat amount, and calculates the work of the compressor based on the required heat pump heat transport amount.

6. A vehicle control device according to claim 1, comprising: a mathematical model A that calculates a differential value or a future value of the pressure upstream and downstream of the compressor based on the compressor work of the heat pump system, the flow rate through an expansion valve, the outside temperature, and the current values ​​of the pressure upstream and downstream of the compressor; and a mathematical model B that calculates the heat transfer amount of an evaporator and a condenser, which are components of the heat pump system, based on the compressor work, the flow rate through an expansion valve, the outside temperature, and the differential value or the future values ​​of the pressure upstream and downstream of the compressor.

7. The vehicle control device according to claim 6, wherein the mathematical model A and the mathematical model B are neural network models.

8. A vehicle control device according to claim 1, comprising: a mathematical model A that calculates a differential value or a future value of the upstream pressure of the compressor and the differential pressure before and after the compressor based on the compressor work of the heat pump system, the outside air temperature, and the current values ​​of the upstream pressure of the compressor and the differential pressure before and after the compressor; and a mathematical model B that calculates the amount of heat transfer of an evaporator and a condenser that are components of the heat pump system based on the compressor work, the outside air temperature, and the differential value or the future values ​​of the upstream pressure of the compressor and the differential pressure before and after the compressor.

9. The vehicle control device according to claim 8, wherein the mathematical model A and the mathematical model B are neural network models.

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