CN112650078B - Hardware-in-loop simulation system for vehicle control unit of pure electric vehicle and extended range electric vehicle - Google Patents
Hardware-in-loop simulation system for vehicle control unit of pure electric vehicle and extended range electric vehicle Download PDFInfo
- Publication number
- CN112650078B CN112650078B CN202011471319.4A CN202011471319A CN112650078B CN 112650078 B CN112650078 B CN 112650078B CN 202011471319 A CN202011471319 A CN 202011471319A CN 112650078 B CN112650078 B CN 112650078B
- Authority
- CN
- China
- Prior art keywords
- model
- power battery
- controller
- simulation system
- vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention discloses a hardware-in-loop simulation system of a vehicle control unit of a pure electric and extended range type electric vehicle, which comprises the following steps: the controlled object model of the real-time simulation system comprises a driver model, a virtual controller model, a range extender model and an electric automobile body model. The invention solves the problem that the tested controller of the existing hardware-in-loop simulation system is single, can be simultaneously suitable for hardware-in-loop simulation of the whole vehicle controller of the pure electric vehicle and the extended range type electric vehicle, optimizes the calculation of internal resistance and effective output torque of the engine in the power battery model, and improves the simulation precision of the hardware-in-loop simulation system of the whole vehicle controller.
Description
Technical Field
The invention belongs to the technical field of electric vehicle simulation, and particularly relates to a hardware-in-loop simulation system of a vehicle control unit of a pure electric vehicle and a range-extended electric vehicle.
Background
In the development of pure electric or extended range electric vehicles, the development of a vehicle control unit is a key link. In the system development process of the vehicle control unit, a V-type development process of demand mining, system demand analysis, system architecture design, system integration and integration test and system qualification test is generally adopted. In this V-type development flow, a system qualification test is indispensable. Generally, the system qualification test of the vehicle control unit is generally performed in a hardware-in-loop simulation system.
The system comprises a main computer, a simulation device, an operation monitoring device and a simulation monitoring device, wherein the simulation device is respectively connected with the main computer, the whole vehicle controller to be subjected to simulation test and the simulation monitoring device, the operation monitoring device is connected with the whole vehicle controller to be subjected to simulation test, and the operation monitoring device has real-time performance and can observe the characteristic of a simulation test process at any time, so that the hardware-in-loop simulation test efficiency of the whole vehicle controller is improved.
Through the above, it can be found that the hardware-in-loop simulation system in the prior art is mainly applied to hardware-in-loop simulation of a single pure electric vehicle type or single extended-range vehicle type vehicle controller, and cannot be simultaneously applied to hardware-in-loop simulation of pure electric vehicles and extended-range electric vehicle controllers.
Disclosure of Invention
The invention provides a hardware-in-loop simulation system of a vehicle control unit of a pure electric vehicle and a range-extended electric vehicle, which solves the problem that a tested controller of the existing hardware-in-loop simulation system is single, can be simultaneously suitable for hardware-in-loop simulation of the vehicle control unit of the pure electric vehicle and the range-extended electric vehicle, optimizes internal resistance and effective output torque calculation of an engine in a power battery model, and improves the simulation precision of the hardware-in-loop simulation of the vehicle control unit.
The technical scheme of the invention is as follows: the utility model provides a pure electric and increase form electric automobile vehicle control unit hardware is at ring simulation system for vehicle control unit's system qualification test includes: the system comprises a real-time simulation system, an upper computer, a vehicle control unit, a hardware CAN card and a load;
the real-time simulation system is connected with the vehicle control unit through a wire harness, the real-time simulation system is connected with a load through a wire harness, the real-time simulation system is connected with an upper computer through a network cable, the real-time simulation system is used for operating a controlled object model, and the real-time simulation system monitors the vehicle control unit in real time;
the vehicle control unit is used for controlling a load;
the hardware CAN card is connected with the vehicle controller in a CAN communication mode and is connected with the upper computer through a USB interface;
the controlled object model is a core component for realizing virtual simulation of a hardware-in-the-loop system, the controlled object model operated by the real-time simulation system comprises a driver model, a virtual controller model, a range extender model and an electric vehicle body model, the virtual controller model is respectively in signal connection with the range extender model, the electric vehicle body model and the driver model, and the electric vehicle body model is in signal connection with the driver model;
the driver model is used for simulating the behavior of a driver and outputting the behavior parameters of the driver;
the virtual controller model comprises a virtual vehicle controller interface model, a virtual power battery management system model, a virtual driving motor controller model, a virtual engine controller model, a virtual generator controller model and a virtual accessory controller model which are in signal connection with the virtual vehicle controller interface model; the virtual controller model is used for simulating each controller of the electric automobile, monitoring the running data of the electric automobile and the range extender in real time, and controlling the electric automobile and the range extender according to the monitored data and the intention of a driver;
the electric automobile body model is used for simulating the operation of the whole electric automobile and comprises a power battery model, a driving motor model, a transmission system model and a vehicle longitudinal dynamics model which are sequentially connected through signals; the power battery model is used for calculating the SOC of the power battery, the voltage of the power battery and the internal resistance; the driving motor model is used for calculating the output torque and the required current of the driving motor; the transmission system model is used for calculating the torque of the output end of the transmission system and the rotating speed of the input end; the vehicle longitudinal dynamics model is used for calculating the running resistance of the whole vehicle and the speed of the whole vehicle;
the internal resistance calculation formula in the power battery model is as follows:
R＝f EOL (t,soc)*(1-soh)+f NEW (t,soc)*soh
wherein R is the internal resistance in the power battery model; t is the power cell temperature; soc is the state of remaining charge available to the power battery; soh is the power battery state of health; f. of NEW (t, SOC) data Map of battery internal resistance changing along with SOC and temperature when the power battery leaves factory; f. of EOL (t, SOC) is data Map of the change of the internal resistance of the battery along with the SOC and the temperature when the service life of the battery is ended;
the range extender model comprises an engine model, a generator model and a crankshaft model which are sequentially connected in a signal manner; the crankshaft model calculates the rotating speed of the range extender through input engine torque information, generator torque information and inertia empirical values; the generator model is internally provided with generator external characteristics maps under different voltages, and the output torque and the required current of the generator are calculated through the input target torque, the high-voltage bus voltage and the actual rotating speed of the generator; the engine model simulates the effective engine output torque for normal operating conditions and exhaust braking conditions.
Preferably, the torque calculation formula for calculating the effective output torque of the engine through simulation of the engine model is as follows:
when the exhaust brake command is invalid, T = f (n) × r + f Fri (n)；
When the exhaust brake command is effective, T = f brk (n)；
Wherein T is effective output torque of the engine, n is engine speed, r is accelerator opening, and f (n) is data Map of maximum torque of the engine changing with the speed Fri (n) is data Map, f of engine friction torque changing with rotating speed brk And (n) is data Map of engine exhaust braking torque changing along with the rotating speed.
Preferably, the step of calculating the effective output torque of the engine by the engine model simulation comprises the following steps:
step one, three maps are built into an engine model, and the maps are respectively as follows: data Map of the maximum torque of the engine changing along with the rotating speed; data Map of engine friction torque changing with rotating speed; data Map of engine exhaust brake torque variation with rotation speed;
secondly, judging whether an exhaust braking instruction is effective or not;
thirdly, if the exhaust braking instruction is invalid, searching data Map based on the opening degree of an accelerator and the rotating speed of the engine, and calculating to obtain the effective output torque of the engine;
fourthly, if the exhaust braking instruction is effective, searching data Map based on the rotating speed of the engine, and calculating to obtain effective output torque of the engine;
and fifthly, limiting the torque change rate of the effective output torque of the engine, wherein the limited torque is the effective output torque of the engine obtained through final calculation.
Preferably, the calculation steps of the internal resistance in the power battery model are as follows:
step one, four maps are built in a power battery model, and the method comprises the following steps: in a charging state, when the power battery leaves a factory newly, first data Map of battery internal resistance changing along with SOC and temperature; in a discharging state, when the power battery leaves a factory newly, second data Map of the change of the internal resistance of the battery along with the SOC and the temperature; in a charging state, when the service life of the power battery is ended, third data Map of the internal resistance of the battery changing along with the SOC and the temperature; fourth data Map of the internal resistance of the battery along with the change of the SOC and the temperature when the service life of the power battery is ended in a discharging state;
secondly, judging whether the current power battery is in a charging or discharging state;
thirdly, if the current power battery is in a charging state, inquiring the first data Map and the third data Map according to the temperature and the SOC, and calculating to obtain the internal resistance in the power battery model according to the internal resistance calculation formula;
and fourthly, if the current power battery is in a discharging state, inquiring the second data Map and the fourth data Map according to the temperature and the SOC, and calculating to obtain the internal resistance in the power battery model according to the internal resistance calculation formula.
Preferably, the method for switching the work of the electric automobile body model and the range extender model in the controlled object model comprises the following steps: setting a calibration quantity in a controlled object model for enabling a range extender model, such as an engine model, a crankshaft model, a generator model, an engine controller model and a generator controller model; when the calibration quantity is invalid, the range extender model does not work, and the controlled object model is used for a pure electric vehicle type; when the calibration quantity is effective, the relevant model of the range extender model works, and the controlled object model is used for the range-extended electric vehicle type. By adopting the method, the controlled object can be switched between the pure electric mode and the range extending mode, and one system can simulate two working modes.
Preferably, the real-time simulation system is a dSPACE system, the upper computer comprises ControlDesk software, ECU Test software and INCA software, and the ControlDesk software is used for monitoring and controlling the operating data of a controlled object model in the real-time simulation system; the INCA software is used for controlling the internal parameters of the whole vehicle controller in real time and monitoring the internal operation data of the whole vehicle controller; and the ECU Test software calls a ControlDesk software interface and an INCA software interface according to the executable Test file to complete monitoring and control of external and internal data of the whole vehicle controller, so that the Test of the whole vehicle controller is realized.
Preferably, the real-time simulation system is communicated with the whole vehicle controller through a hard wire signal and a CAN communication signal, so that the stability and the speed of data transmission are improved.
Preferably, the driver behavior parameters include a key status, an accelerator opening, a brake signal and a gear signal. The most real working state at the position is simulated by adopting the parameters, so that the accuracy is improved.
Preferably, the virtual vehicle controller interface model comprises a hard-wire input interface model, a hard-wire output interface model, a CAN input interface model and a CAN output interface model, and the virtual vehicle controller interface model is used for realizing the functions of receiving and transmitting hardware signals and CAN signals.
The beneficial effects of the invention are:
1. the controlled object model comprises a range extender model and an electric vehicle body model, and modes can be switched, so that the requirement that hardware of a pure electric vehicle controller and a range extender electric vehicle controller can be simulated in a ring by one system can be met, and the simulation efficiency is improved.
2. The method for calculating the effective output torque in the engine model can calculate the output torque of the engine under the exhaust braking working condition, effectively simulate the scene that the range extender drags the engine under the exhaust braking working condition by using the generator, and improve the simulation accuracy of the range extender.
3. The method for calculating the internal resistance in the power battery model can calculate the internal resistance of the power battery under different SOH scenes, and improves the accuracy of the simulation of the internal resistance of the power battery. And then the simulation accuracy of the high-voltage loop voltage of the electric automobile is provided by combining the open-circuit voltage and the output current data of the power battery.
Drawings
Fig. 1 is a block diagram of a hardware-in-loop simulation system of a vehicle controller of a pure electric vehicle and an extended range electric vehicle according to the present invention.
Fig. 2 is a block diagram of a structure of a controlled object model of the real-time simulation system according to the present invention.
Fig. 3 is a structural block diagram of the virtual vehicle controller interface model according to the present invention.
FIG. 4 is a flowchart of the steps for calculating the engine available output torque of the engine model of the present invention.
Fig. 5 is a flowchart of the steps for calculating the internal resistance in the power battery model according to the present invention.
In the figure: 1-a real-time simulation system, 2-a host computer, 3-a vehicle controller, 4-a hardware CAN card, 5-a load, 6-a driver model, 7-a virtual controller model, 701-a virtual vehicle controller interface model, 7011-a hard-wire input interface model, 7012-a hard-wire output interface model, 7013-a CAN input interface model, 7014-a CAN output interface model, 702-a virtual power battery management system model, 703-a virtual drive motor controller model, 704-a virtual engine controller model, 705-a virtual generator controller model, 706-a virtual accessory controller model, 8-a range extender model, 801-an engine model, 802-a generator model, 803-a crankshaft model, 9-an electric vehicle body model, 901-a power battery model, 902-a drive motor model, 903-a transmission system model, 904-a vehicle longitudinal dynamics model.
Detailed Description
The present invention will be further described with reference to the drawings and the detailed description, wherein the exemplary embodiments and the description are provided for the purpose of illustrating the invention and are not to be construed as limiting the invention.
Example 1:
as shown in fig. 1, an in-loop simulation system for hardware of a vehicle controller of a pure electric vehicle and an extended range electric vehicle includes: the system comprises a real-time simulation system 1, an upper computer 2, a vehicle control unit 3, a hardware CAN card 4 and a load 5;
the real-time simulation system 1 is connected with the vehicle control unit 3 through a wire harness, the real-time simulation system 1 is connected with a load 5 through the wire harness, the real-time simulation system 1 is connected with the upper computer 2 through a network cable, the real-time simulation system 1 is used for operating a controlled object model, and the real-time simulation system 1 monitors the vehicle control unit 3 in real time;
the vehicle control unit 3 is used for controlling a load 5;
the hardware CAN card 4 is connected with the vehicle control unit 3 in a CAN communication mode, and the hardware CAN card 4 is connected with the upper computer 2 through a USB interface;
as shown in fig. 2, the controlled object model operated by the real-time simulation system 1 includes a driver model 6, a virtual controller model 7, a range extender model 8 and an electric vehicle body model 9, the virtual controller model 7 is respectively in signal connection with the range extender model 8, the electric vehicle body model 9 and the driver model 6, and the electric vehicle body model 9 is in signal connection with the driver model 6;
the driver model 6 is used for simulating the behavior of a driver and outputting the behavior parameters of the driver;
the virtual controller model 7 comprises a virtual vehicle controller interface model 701, a virtual power battery management system model 702, a virtual driving motor controller model 703, a virtual engine controller model 704, a virtual generator controller model 705 and a virtual accessory controller model 706 which are all in signal connection with the virtual vehicle controller interface model 701; the virtual controller model 7 is used for simulating each controller of the electric automobile, monitoring the running data of the electric automobile and the range extender in real time, and controlling the electric automobile and the range extender according to the monitored data and the intention of a driver;
the electric automobile body model 9 is used for simulating the operation of the whole electric automobile, and the electric automobile body model 9 comprises a power battery model 901, a driving motor model 902, a transmission system model 903 and a vehicle longitudinal dynamics model 904 which are sequentially connected in a signal manner; the power battery model 901 is used for calculating the SOC, the voltage and the internal resistance of the power battery; the driving motor model 902 is used for calculating the output torque and the required current of the driving motor; the transmission system model 903 is used for calculating the torque of the output end of the transmission system and the rotating speed of the input end; the vehicle longitudinal dynamics model 904 is used for calculating the whole vehicle running resistance and the whole vehicle speed;
in this implementation, the internal resistance calculation formula in the power battery model 901 is as follows:
R＝f EOL (t,soc)*(1-soh)+f NEW (t,soc)*soh
in the formula, R is the internal resistance in the power battery model 901; t is the power cell temperature; soc is the available state of the residual charge of the power battery; soh is the power battery state of health; f. of NEW (t, SOC) data Map of the internal resistance of the battery changing along with SOC and temperature when the power battery leaves a factory newly; f. of EOL (t, SOC) is data Map of the change of the internal resistance of the battery along with the SOC and the temperature when the service life of the battery is ended;
the range extender model 8 comprises an engine model 801, a generator model 802 and a crankshaft model 803 which are sequentially connected through signals; the crankshaft model 803 calculates the rotational speed of the range extender by inputting engine torque information, generator torque information and inertia empirical values; the generator model 802 is internally provided with generator external characteristics Map under different voltages, and the output torque and the required current of the generator are calculated according to the input target torque, the high-voltage bus voltage and the actual rotating speed of the generator; the engine model 801 simulates the engine effective output torque for normal operating conditions and exhaust brake conditions.
Example 2:
as shown in fig. 1, an in-loop simulation system for hardware of a vehicle control unit of a pure electric vehicle and a range-extended electric vehicle is used for testing the system qualification of the vehicle control unit 3, and includes: the system comprises a real-time simulation system 1, an upper computer 2, a vehicle control unit 3, a hardware CAN card 4 and a load 5;
the real-time simulation system 1 is connected with the vehicle control unit 3 through a wire harness, the real-time simulation system 1 is connected with a load 5 through a wire harness, the real-time simulation system 1 is connected with the upper computer 2 through a network cable, the real-time simulation system 1 is used for operating a controlled object model, and the real-time simulation system 1 monitors the vehicle control unit 3 in real time;
the vehicle control unit 3 is used for controlling a load 5;
the hardware CAN card 4 is connected with the vehicle control unit 3 in a CAN communication mode, and the hardware CAN card 4 is connected with the upper computer 2 through a USB interface;
as shown in fig. 2, the controlled object model is a core component of a hardware-in-the-loop system for implementing virtual simulation, the controlled object model run by the real-time simulation system 1 includes a driver model 6, a virtual controller model 7, a range extender model 8 and an electric vehicle body model 9, the virtual controller model 7 is respectively in signal connection with the range extender model 8, the electric vehicle body model 9 and the driver model 6, and the electric vehicle body model 9 is in signal connection with the driver model 6;
the driver model 6 is used for simulating the behavior of a driver and outputting the behavior parameters of the driver;
the virtual controller model 7 comprises a virtual vehicle controller interface model 701, and a virtual power battery management system model 702, a virtual driving motor controller model 703, a virtual engine controller model 704, a virtual generator controller model 705 and a virtual accessory controller model 706 which are in signal connection with the virtual vehicle controller interface model 701; the virtual controller model 7 is used for simulating each controller of the electric automobile, monitoring the running data of the electric automobile and the range extender in real time, and controlling the electric automobile and the range extender according to the monitored data and the intention of a driver;
the electric automobile body model 9 is used for simulating the operation of the whole electric automobile, and the electric automobile body model 9 comprises a power battery model 901, a driving motor model 902, a transmission system model 903 and a vehicle longitudinal dynamics model 904 which are sequentially connected in a signal manner; the power battery model 901 is used for calculating the SOC, the voltage and the internal resistance of the power battery; the driving motor model 902 is used for calculating the output torque and the required current of the driving motor; the transmission system model 903 is used for calculating the torque of the output end of the transmission system and the rotating speed of the input end; the vehicle longitudinal dynamics model 904 is used for calculating the whole vehicle running resistance and the whole vehicle speed;
the internal resistance calculation formula in the power battery model 901 is as follows:
R＝f EOL (t,soc)*(1-soh)+f NEW (t,soc)*soh
in the formula, R is the internal resistance in the power battery model 901; t is the power cell temperature; soc is the state of remaining charge available to the power battery; soh is the power battery state of health; f. of NEW (t, SOC) data Map of the internal resistance of the battery changing along with SOC and temperature when the power battery leaves a factory newly; f. of EOL (t, SOC) is data Map of the change of the internal resistance of the battery along with the SOC and the temperature when the service life of the battery is ended;
the range extender model 8 comprises an engine model 801, a generator model 802 and a crankshaft model 803 which are sequentially connected through signals; the crankshaft model 803 calculates the rotational speed of the range extender by inputting engine torque information, generator torque information and inertia empirical values; the generator model 802 is internally provided with generator external characteristics Map under different voltages, and the output torque and the required current of the generator are calculated through the input target torque, the high-voltage bus voltage and the actual rotating speed of the generator; the engine model 801 simulates the engine effective output torque for normal operating conditions and exhaust brake conditions.
In this embodiment, the torque calculation formula for the engine model 801 to calculate the effective output torque of the engine in a simulation mode is as follows:
when the exhaust brake command is invalid, T = f (n) × r + f Fri (n)；
When the exhaust brake command is effective, T = f brk (n)；
Wherein T is effective output torque of the engine, n is engine speed, r is accelerator opening, and f (n) is data Map of maximum torque of the engine changing with the speed Fri (n) is data Map, f of engine friction torque changing with rotating speed brk And (n) is data Map of engine exhaust braking torque changing along with the rotating speed.
As shown in fig. 4, in the present embodiment, the steps of calculating the effective engine output torque by simulating the engine model 801 are as follows:
first, three maps are built into the engine model 801, which are: data Map of the maximum torque of the engine changing with the rotating speed; data Map of engine friction torque changing along with rotating speed; data Map of engine exhaust brake torque variation with rotation speed;
secondly, judging whether an exhaust braking instruction is effective or not;
thirdly, if the exhaust braking instruction is invalid, searching data Map based on the opening degree of an accelerator and the rotating speed of the engine, and calculating to obtain the effective output torque of the engine;
fourthly, if the exhaust braking instruction is effective, searching data Map based on the rotating speed of the engine, and calculating to obtain effective output torque of the engine;
and fifthly, limiting the torque change rate of the effective output torque of the engine, wherein the limited torque is the effective output torque of the engine obtained by final calculation.
As shown in fig. 5, in this embodiment, the steps of calculating the internal resistance in the power battery model 901 include:
first, four maps are built into the power battery model 901, which are respectively: in a charging state, when the power battery leaves a factory newly, first data Map of the internal resistance of the battery changing along with the SOC and the temperature; in a discharging state, when the power battery leaves a factory newly, second data Map of the change of the internal resistance of the battery along with the SOC and the temperature; in a charging state, when the service life of the power battery is ended, third data Map of the internal resistance of the battery changing along with the SOC and the temperature; in a discharging state, when the service life of the power battery is ended, fourth data Map of the internal resistance of the battery changing along with the SOC and the temperature;
secondly, judging whether the current power battery is in a charging or discharging state;
thirdly, if the current power battery is in a charging state, inquiring the first data Map and the third data Map according to the temperature and the SOC, and calculating to obtain the internal resistance in the power battery model 901 according to the internal resistance calculation formula;
and step four, if the current power battery is in a discharging state, querying the second data Map and the fourth data Map according to the temperature and the SOC, and calculating to obtain the internal resistance in the power battery model 901 according to the internal resistance calculation formula.
In this embodiment, the method for switching the work of the electric vehicle body model 9 and the range extender model 8 in the controlled object model includes: in the controlled object model, a calibration amount is set for enabling the range extender model 8, such as an engine model 801, a crankshaft model 803, a generator model 802, an engine controller model, and a generator controller model; when the calibration quantity is invalid, the range extender model 8 does not work, and the controlled object model is used for a pure electric vehicle type; when the calibration quantity is effective, the relevant model of the range extender model 8 works, and the controlled object model is used for the range-extended electric vehicle type. By adopting the method, the controlled object can be switched between the pure electric mode and the range extending mode, and one system can simulate two working modes.
As shown in fig. 1, in this embodiment, the real-time simulation system 1 is a dSPACE system, the upper computer 2 includes a ControlDesk software, an ECU Test software, and an INCA software, and the ControlDesk software is used to monitor and control the operating data of the controlled object model in the real-time simulation system 1; the INCA software is used for controlling the internal parameters of the vehicle controller 3 in real time and monitoring the internal operation data of the vehicle controller 3; the ECU Test software calls a ControlDesk software interface and an INCA software interface according to an executable Test file to complete monitoring and control of external and internal data of the whole vehicle controller 3, and further Test of the whole vehicle controller 3 is achieved.
In this embodiment, the real-time simulation system 1 communicates with the vehicle control unit 3 through a hard-wired signal and a CAN communication signal, so as to improve the stability and speed of data transmission.
In this embodiment, the driver behavior parameters include a key state, an accelerator opening, a brake signal, and a gear signal. The most real working state is simulated by adopting the parameters, so that the accuracy is improved.
As shown in fig. 3, in this embodiment, the virtual vehicle controller interface model 701 includes a hard-wired input interface model 7011, a hard-wired output interface model 7012, a CAN input interface model 7013, and a CAN output interface model 7014, and the virtual vehicle controller interface model 701 is configured to implement a function of receiving and transmitting a hardware signal and a CAN signal.
In this embodiment, in the charging state, when the power battery leaves the factory newly, the first data Map of the internal resistance of the battery changing along with the SOC and the temperature is as follows:
in a discharging state, when the power battery leaves a factory newly, second data Map of the internal resistance of the battery along with the change of the SOC and the temperature is as follows:
in the charging state, when the service life of the power battery is ended, the third data of the internal resistance of the battery along with the change of the SOC and the temperature are as follows:
in a discharging state, when the service life of the power battery is ended, the fourth data Map of the internal resistance of the battery along with the change of the SOC and the temperature is as follows:
specifically, according to an internal resistance calculation formula in the power battery model 901:
R＝f EOL (t,soc)*(1-soh)+f NEW (t,soc)*soh
in a discharging state, if the SOH of the power battery is 95%, the temperature is 25degC and the SOC is 80%, the corresponding single battery internal resistance is 0.95 × 46+ (1-0.95) × 246=56mOhn
The corresponding data Map of the effective output torque of the engine is three, and f (n) is the data Map of the maximum torque of the engine changing along with the rotating speed, f Fri (n) is data Map, f of friction torque of engine varying with rotation speed brk (n) is data Map of exhaust brake torque of the engine as a function of rotation speed, which is shown in the following table:
| rotating speed (rpm) | 0 | 20 | 1000 | 1200 | 1400 | 1600 | 1800 | 2000 | 2200 | 2400 | 2600 |
| Torque (Nm) | 0 | 0 | 477 | 514 | 518 | 515 | 520 | 518 | 487 | 455 | 419 |
| Friction Torque (Nm) | 0 | 0 | -12.6 | -12.6 | -12.8 | -13 | -13.3 | -13.9 | -14.5 | -15.5 | -16.3 |
| Exhaust brake torque (Nm) | 0 | 0 | -286.5 | -238.75 | -204.643 | -179.063 | -159.167 | -143.25 | -130.227 | -119.375 | -110.192 |
Specifically, for example, when the exhaust brake command is invalid, if the accelerator opening is 50% and the engine speed is 1000rpm, the Map is searched and substituted into the formula T = f (n) × r + f Fri (n), then the corresponding effective output torque is 477 × 0.5-12.6=225.9nm.
When the exhaust brake command is effective, if the engine speed is 1000rpm, inquiring the Map, and substituting the equation T = f brk (n) the engine available output torque is-286.5 Nm.
Claims (6)
1. The utility model provides a pure electric reaches extended range formula electric automobile vehicle control unit hardware is at ring simulation system which characterized in that includes: the system comprises a real-time simulation system (1), an upper computer (2), a whole vehicle controller (3), a hardware CAN card (4) and a load (5);
the real-time simulation system (1) is connected with the vehicle control unit (3) through a wire harness, the real-time simulation system (1) is connected with a load (5) through the wire harness, the real-time simulation system (1) is connected with the upper computer (2) through a network cable, the real-time simulation system (1) is used for operating a controlled object model, and the real-time simulation system (1) monitors the vehicle control unit (3) in real time;
the vehicle control unit (3) is used for controlling a load (5);
the hardware CAN card (4) is connected with the whole vehicle controller (3) in a CAN communication mode, and the hardware CAN card (4) is connected with the upper computer (2) through a USB interface;
the controlled object model operated by the real-time simulation system (1) comprises a driver model (6), a virtual controller model (7), a range extender model (8) and an electric vehicle body model (9), wherein the virtual controller model (7) is in signal connection with the range extender model (8), the electric vehicle body model (9) and the driver model (6) respectively, and the electric vehicle body model (9) is in signal connection with the driver model (6);
the driver model (6) is used for simulating the behavior of a driver and outputting the behavior parameters of the driver;
the virtual controller model (7) comprises a virtual vehicle controller interface model (701), and a virtual power battery management system model (702), a virtual driving motor controller model (703), a virtual engine controller model (704), a virtual generator controller model (705) and a virtual accessory controller model (706) which are in signal connection with the virtual vehicle controller interface model (701); the virtual controller model (7) is used for simulating each controller of the electric automobile, monitoring the running data of the electric automobile and the range extender in real time, and controlling the electric automobile and the range extender according to the monitored data and the intention of a driver;
the electric automobile body model (9) is used for simulating the operation of the whole electric automobile, and the electric automobile body model (9) comprises a power battery model (901), a driving motor model (902), a transmission system model (903) and a vehicle longitudinal dynamics model (904) which are sequentially connected in a signal manner; the power battery model (901) is used for calculating the SOC of the power battery, the voltage of the power battery and the internal resistance; the driving motor model (902) is used for calculating the output torque and the required current of the driving motor; the transmission system model (903) is used for calculating the torque of the output end of the transmission system and the rotating speed of the input end; the vehicle longitudinal dynamics model (904) is used for calculating the whole vehicle running resistance and the whole vehicle speed;
the internal resistance calculation formula in the power battery model (901) is as follows:
R＝f EOL (t,soc)*(1-soh)+f NEW (t,soc)*soh
wherein R is the internal resistance in the power battery model (901); t is the power cell temperature; soc is the state of remaining charge available to the power cell; soh is the power battery state of health; f. of NEW (t, SOC) data Map of the internal resistance of the battery changing along with SOC and temperature when the power battery leaves a factory newly; f. of EOL (t, SOC) is data Map of the change of the internal resistance of the battery along with the SOC and the temperature when the service life of the battery is ended;
the range extender model (8) comprises an engine model (801), a generator model (802) and a crankshaft model (803) which are sequentially connected through signals; the crankshaft model (803) calculates the rotating speed of the range extender through input engine torque information, generator torque information and inertia empirical values; the generator model (802) is internally provided with generator external characteristics Map under different voltages, and the output torque and the required current of the generator are calculated through the input target torque, the high-voltage bus voltage and the actual rotating speed of the generator; an engine model (801) simulates effective output torque of an engine under a normal operation condition and an exhaust braking condition;
the torque calculation formula for simulating and calculating the effective output torque of the engine by the engine model (801) is as follows:
when the exhaust brake command is invalid, T = f (n) × r + f Fri (n)；
When the exhaust brake command is effective, T = f brk (n)；
Where T is engine efficientOutput torque, n is engine speed, r is throttle opening, f (n) is data Map, f of maximum engine torque changing with speed Fri (n) is data Map, f of engine friction torque changing with rotating speed brk And (n) is data Map of engine exhaust braking torque variation with rotating speed.
2. The hardware-in-loop simulation system of a vehicle control unit of a pure electric and extended range electric vehicle according to claim 1, wherein the step of calculating the internal resistance in the power battery model (901) is as follows:
the first step, four maps are built in a power battery model (901), and the maps are respectively as follows: in a charging state, when the power battery leaves a factory newly, first data Map of battery internal resistance changing along with SOC and temperature; in a discharging state, when the power battery leaves a factory newly, second data Map of the change of the internal resistance of the battery along with the SOC and the temperature; in a charging state, when the service life of the power battery is ended, third data Map of the internal resistance of the battery changing along with the SOC and the temperature; in a discharging state, when the service life of the power battery is ended, fourth data Map of the internal resistance of the battery changing along with the SOC and the temperature;
secondly, judging whether the current power battery is in a charging or discharging state;
thirdly, if the current power battery is in a charging state, inquiring the first data Map and the third data Map according to the temperature and the SOC, and calculating to obtain the internal resistance in the power battery model (901) according to the internal resistance calculation formula;
and fourthly, if the current power battery is in a discharging state, inquiring the second data Map and the fourth data Map according to the temperature and the SOC, and calculating the internal resistance in the power battery model (901) according to the internal resistance calculation formula.
3. The hardware-in-the-loop simulation system of the vehicle control unit of the pure electric and extended range electric vehicle according to claim 1, characterized in that: the real-time simulation system (1) is a dSPACE HIL system, the upper computer (2) comprises ControlDesk software, ECU Test software and INCA software, and the ControlDesk software is used for monitoring and controlling the running data of a controlled object model in the real-time simulation system (1); the INCA software is used for controlling the internal parameters of the vehicle controller (3) in real time and monitoring the internal operation data of the vehicle controller (3); and the ECU Test software calls a ControlDesk software interface and an INCA software interface according to the executable Test file to complete monitoring and control of external and internal data of the whole vehicle controller (3), so that the Test of the whole vehicle controller (3) is realized.
4. The hardware-in-the-loop simulation system of the vehicle control unit of the pure electric and extended range electric vehicle according to claim 1, characterized in that: the real-time simulation system (1) is communicated with the whole vehicle controller (3) through a hard wire signal and a CAN communication signal.
5. The hardware-in-the-loop simulation system of the vehicle controller of the pure electric and extended range electric vehicle according to claim 1, wherein: the driver behavior parameters include a key state, an accelerator opening, a brake signal and a gear signal.
6. The hardware-in-the-loop simulation system of the vehicle control unit of the pure electric and extended range electric vehicle according to claim 1, characterized in that: the virtual vehicle controller interface model (701) comprises a hard-wire input interface model (7011), a hard-wire output interface model (7012), a CAN input interface model (7013) and a CAN output interface model (7014), and the virtual vehicle controller interface model (701) is used for realizing the functions of receiving and transmitting hardware signals and CAN signals.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011471319.4A CN112650078B (en) | 2020-12-14 | 2020-12-14 | Hardware-in-loop simulation system for vehicle control unit of pure electric vehicle and extended range electric vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011471319.4A CN112650078B (en) | 2020-12-14 | 2020-12-14 | Hardware-in-loop simulation system for vehicle control unit of pure electric vehicle and extended range electric vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112650078A CN112650078A (en) | 2021-04-13 |
| CN112650078B true CN112650078B (en) | 2022-12-09 |
Family
ID=75354441
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011471319.4A Active CN112650078B (en) | 2020-12-14 | 2020-12-14 | Hardware-in-loop simulation system for vehicle control unit of pure electric vehicle and extended range electric vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112650078B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113267347B (en) * | 2021-05-17 | 2024-08-13 | 阳光电源股份有限公司 | Method, device and system for testing auxiliary function of electric automobile in parking slope |
| CN113485298A (en) * | 2021-07-15 | 2021-10-08 | 广州南洋理工职业学院 | Electric automobile torque active distribution system control strategy test platform |
| CN114356760B (en) * | 2021-12-27 | 2024-11-26 | 重庆长安汽车股份有限公司 | A CANFD controller software remote upgrade test method and system based on L3 vehicle architecture |
| CN114248637B (en) * | 2021-12-29 | 2024-06-07 | 东风重工（十堰）有限公司 | Energy-saving environment-friendly extended-range heavy truck |
| CN114675626B (en) * | 2022-03-30 | 2024-08-09 | 东风汽车集团股份有限公司 | Vehicle-mounted controller test platform and test method |
| CN115127830A (en) * | 2022-06-29 | 2022-09-30 | 重庆长安新能源汽车科技有限公司 | Range extender rack test system and reliability test method |
| CN115291587B (en) * | 2022-07-18 | 2024-07-23 | 重庆长安汽车股份有限公司 | Platform software model architecture based on multi-HIL test system, automobile, computer readable storage medium and electronic equipment |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4023625B2 (en) * | 2005-10-28 | 2007-12-19 | 本田技研工業株式会社 | Control device for hybrid vehicle |
| DE102008062205A1 (en) * | 2008-12-13 | 2009-09-17 | Daimler Ag | Battery state of charge identifying method for motor vehicle, involves determining current state of charge under consideration of impedance of battery, and using transient internal resistance of battery as impedance of battery |
| WO2011045853A1 (en) * | 2009-10-14 | 2011-04-21 | 株式会社 日立製作所 | Battery control device and motor drive system |
| JP6033155B2 (en) * | 2013-03-29 | 2016-11-30 | 日立オートモティブシステムズ株式会社 | Battery control device |
| CN104699070B (en) * | 2015-01-12 | 2016-04-20 | 湖南大学 | A hardware-in-the-loop simulation system for electrical matching of pure electric vehicles |
| WO2017199629A1 (en) * | 2016-05-18 | 2017-11-23 | 日立オートモティブシステムズ株式会社 | Battery control device |
| WO2018189891A1 (en) * | 2017-04-14 | 2018-10-18 | 日産自動車株式会社 | Hybrid vehicle control method and hybrid vehicle control device |
| JP6996400B2 (en) * | 2018-04-06 | 2022-01-17 | トヨタ自動車株式会社 | Vehicle system |
| JP6965866B2 (en) * | 2018-11-29 | 2021-11-10 | マツダ株式会社 | Vehicle control device |
| CN111650925B (en) * | 2020-06-18 | 2022-01-28 | 中车青岛四方车辆研究所有限公司 | dSPACE-based hybrid electric vehicle hardware-in-loop simulation system construction method |
| CN111930100A (en) * | 2020-07-31 | 2020-11-13 | 广西玉柴机器股份有限公司 | Semi-physical simulation test system and simulation test method for range extender controller |
| CN111983933B (en) * | 2020-07-31 | 2024-11-19 | 广西玉柴机器股份有限公司 | A hardware-in-the-loop simulation system for range extender controller |
-
2020
- 2020-12-14 CN CN202011471319.4A patent/CN112650078B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN112650078A (en) | 2021-04-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112650078B (en) | Hardware-in-loop simulation system for vehicle control unit of pure electric vehicle and extended range electric vehicle | |
| CN109375611B (en) | A hardware-in-the-loop test system for a complete vehicle controller of a new energy vehicle | |
| Lei et al. | Dynamic energy management for a novel hybrid electric system based on driving pattern recognition | |
| DE102017119547A1 (en) | DISTRIBUTION OF RECOVERED BRAKING POWER | |
| CN111983933B (en) | A hardware-in-the-loop simulation system for range extender controller | |
| DE102016102507A1 (en) | Preparation for vehicle battery charging for power generation after the driving time | |
| CN104298123A (en) | In-loop simulation test system and test method for vehicle management system | |
| CN206162185U (en) | Vehicle control unit is at ring emulation test system | |
| CN105115737A (en) | Electric automobile complete vehicle simulation on-load test system | |
| CN113074952A (en) | Energy consumption testing rack, system and method for power system of plug-in hybrid electric vehicle | |
| DE102020133508A1 (en) | Vehicle, vehicle control system, and vehicle control method | |
| DE10339630A1 (en) | Electric motor controlling system for hybrid electric vehicle, has strategies within controller to determine maximum energy amount and motor power assist value before motor temperature and motor is raised to maximum temperature | |
| CN109062174B (en) | A performance test bench system for extended-range hybrid power system | |
| CN205015162U (en) | Electric automobile carries testing system in whole car simulation area | |
| DE102020133295A1 (en) | Vehicle, vehicle control system, and vehicle control method | |
| DE102020130388A1 (en) | BATTERY CAPACITY ESTIMATE SYSTEM AND METHOD FOR A HYBRID ELECTRIC VEHICLE | |
| CN1246679C (en) | Bench testing method for operating circulation and dynamic circulation of vehicle drive system | |
| DE102020133294A1 (en) | Vehicle, vehicle control system, and vehicle control method | |
| DE102013210418A1 (en) | A method and apparatus for controlling a high voltage electrical system for a multiple mode transmission | |
| EP4180828A1 (en) | Deterioration diagnosis apparatus of battery and deterioration diagnosis method of battery | |
| CN213987201U (en) | In-loop simulation system for controller hardware of range extender | |
| CN115857463A (en) | Control method, device and equipment for vehicle hybrid power assembly performance test | |
| CN113341908A (en) | Pure electric vehicle control strategy simulation verification system and manufacturing method thereof | |
| CN114184875A (en) | Test system and method for whole vehicle and test bench | |
| CN116331186A (en) | Method and device for determining optimal economic working point of hybrid vehicle, medium and equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |