Vehicle energy consumption and driving range simulation method and system and vehicle

Abstract

The invention provides a vehicle energy consumption and driving range simulation method and system and a vehicle. The method comprises: obtaining vehicle parameters and the circulation working condition of the vehicle; obtaining the required power and the required torque of the vehicle according to the whole vehicle parameters and the circulation working condition; obtaining recovery torque and recovery power of the vehicle according to the required power and the required torque; obtaining instantaneous current of the motor according to the required power, the required torque, the recovery power and the recovery torque; obtaining instantaneous charging and discharging current and instantaneous charging and discharging power of the power battery according to the required power, the requiredtorque, the recovery power, the recovery torque, the instantaneous current and the power battery parameters; and performing simulation calculation according to the instantaneous charging and discharging current and the instantaneous charging and discharging power to obtain the energy consumption and SOC change condition of the power battery. According to the method, the vehicle energy consumptionand the driving range can be accurately and effectively simulated, the openness of the simulation process is good, the simulation calculation logic can be conveniently changed and adjusted, and the adjustment mode is simple and easy to operate.

Description

technical field [0001] The invention relates to the technical field of vehicles, in particular to a method, system and vehicle for simulating energy consumption and mileage of a vehicle. Background technique [0002] At present, most of the simulation methods for vehicle energy consumption and fuel consumption, such as AVL Cruise and GT Power, do not have flexible energy / power control strategy settings, or it is difficult to monitor the energy flow and simulation status of each node during the simulation process. It is difficult to adapt to the performance simulation of electric vehicles with different energy recovery strategies, and the following shortcomings are common: [0003] 1. The control strategy is a black box, and simulation engineers cannot view / modify the node settings or calculation logic of the control strategy (such as AVL Cruise, most of which require DLL packet control logic, showing a black box state, and it is difficult to set monitoring nodes in the black...

AI Technical Summary

Problems solved by technology

[0002] At present, most of the simulation methods for vehicle energy consumption and fuel consumption, such as AVL Cruise and GT Power, do not have flexible energy / power control strategy settings, or it is difficult to monitor the energy flow and simulation status of each node during the simulation process. It is difficult to adapt to the performance simulation of electric vehicles with different energy recovery strategies, and the following shortcomings are common:

[0003] 1. The control strategy is a black box, and simulation engineers cannot view / modify the node settings or calculation logic of the control strategy (such as AVL Cruise, most of which require DLL packet control logic, showing a black box state, and it is difficult to set monitoring nodes in the black box)

[0004] 2. The control strategy setting is too simple to reflect the details of the strategy (for example, when GT Power is recycling, the strategy setting parameters only have the minimum recycling speed / recycling ratio, which cannot reflect the actual vehicle status)

[0005] 3. The simulation speed is slow (such as GT Power, it takes too much time to complete a simulation)

[0006] 4. Most of them need to carry out co-simulation and package the control strategy. Once the recycling technology route is replaced, the control strategy must be newly designed (such as AVL Cruise+interface)

[0007] 5. During the simulation process, the energy flow and status of each node cannot be monitored, which is not conducive to the adjustment of control strategies (such problems exist in all simulation software)

[0008] 6. Some parameter interfaces of the simulation model are missing, resulting in a large difference from the actual situation (such as battery cell parameters, motor parameters and temperature parameters in GT Power are difficult to set)

[0009] 7. The openness of the simulation model is poor, and the logic and parameters cannot be changed according to the wishes of the engineer (this problem exists in all simulation software)

[0010] 8. If a simple formula is used for calculation, the calculation error is too large and the calculation amount is too large

[0011] In addition, most of the current simulation methods are based on the idea of ​​forward simulation, that is, the selection of battery motors in the early stage of model development, so it is not convenient to use

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