CN-119527319-B - Vehicle weight determining method and device, storage medium and vehicle

CN119527319BCN 119527319 BCN119527319 BCN 119527319BCN-119527319-B

Abstract

The disclosure relates to a vehicle weight determining method, a vehicle weight determining device, a storage medium and a vehicle, and relates to the field of vehicles, so as to quickly and accurately calculate the vehicle weight. The vehicle weight determining method comprises the steps of determining a running mode according to running state data of a vehicle, determining environment data of the environment where the vehicle is located and the vehicle weight determined by the vehicle in an accelerating mode when the running mode is a sliding mode, determining a vehicle weight correction parameter according to the environment data, the running state data and the vehicle weight, wherein the vehicle weight correction parameter is used for representing deviation between the vehicle weight determined by the vehicle weight determining method and the actual vehicle weight, determining the environment data of the environment where the vehicle is located and the vehicle weight determined when the vehicle is in the accelerating mode last time when the running mode of the vehicle is the accelerating mode, and determining the vehicle weight of the vehicle according to the environment data, the running state data, the vehicle weight determined when the vehicle is in the accelerating mode last time and the vehicle weight correction parameter determined when the vehicle is in the sliding mode.

Inventors

WANG YONGFENG
GUAN HONGYU

Assignees

北汽福田汽车股份有限公司

Dates

Publication Date: 20260508
Application Date: 20230828

Claims (9)

1. A vehicle weight determination method, comprising: Determining a driving mode according to the driving state data of the vehicle; When the driving mode is a sliding mode, determining environmental data of the environment where the vehicle is located and a vehicle weight determined by the vehicle in an accelerating mode, and determining a vehicle weight correction parameter according to the environmental data, the driving state data and the vehicle weight, wherein the vehicle weight correction parameter is used for representing deviation between the vehicle weight determined by the vehicle weight determination method and an actual vehicle weight, and the determining the vehicle weight correction parameter according to the environmental data, the driving state data and the vehicle weight comprises the following steps: determining an actual windage of the vehicle according to the environmental data and the driving state data; determining a calculated wind resistance of the vehicle according to the driving state data and the vehicle weight; Determining the vehicle weight correction parameter according to the actual wind resistance and the calculated wind resistance; When the vehicle running mode is the acceleration mode, determining environmental data of the environment where the vehicle is located and the vehicle weight determined when the vehicle is in the acceleration mode last time, and determining the vehicle weight of the vehicle according to the environmental data, the running state data, the vehicle weight determined when the vehicle is in the acceleration mode last time and the vehicle weight correction parameter determined when the vehicle is in the sliding mode.
2. The method according to claim 1, wherein the method further comprises: If the vehicle does not enter the sliding mode before entering the accelerating mode and does not enter the accelerating mode for the first time, acquiring a preset vehicle weight correction parameter, and determining the vehicle weight of the vehicle according to the environment data, the driving state data, the preset vehicle weight correction parameter and the vehicle weight determined when the vehicle is in the accelerating mode last time; if the vehicle enters the acceleration mode for the first time and does not enter the sliding mode before entering the acceleration mode, acquiring a preset vehicle weight correction parameter and a preset vehicle weight, and determining the vehicle weight of the vehicle according to the environment data, the driving state data, the preset vehicle weight correction parameter and the preset vehicle weight.
3. The method of claim 1, wherein the determining a weight correction parameter based on the environmental data, the driving status data, and the weight comprises: according to the environment data, the driving state data and the vehicle weight, determining a correction parameter as an initial target correction parameter, and circularly executing the following processes: Re-acquiring running state data of the vehicle as first target data and re-acquiring environment data of the environment where the vehicle is located as second target data; Determining a new correction parameter according to the first target data, the second target data and the vehicle weight, adding the new correction parameter to the target correction parameter to obtain the new target correction parameter, and taking the target correction parameter determined in the last cycle process as the vehicle weight correction parameter until the vehicle exits the sliding mode.
4. A method according to any one of claims 1-3, wherein determining the vehicle weight from the environmental data, the driving status data, the vehicle weight determined last time the vehicle was in the acceleration mode, and the vehicle weight correction parameter determined by the vehicle in the coasting mode, comprises: determining a target weight value according to the sampling time of the driving state data and the environment data and the vehicle weight correction parameter determined by the vehicle in the sliding mode, wherein the target weight value is inversely proportional to the vehicle weight correction parameter; and determining the weight of the vehicle based on a recursive least square method according to the target weight value, the environment data, the driving state data and the weight determined when the vehicle is in the acceleration mode last time.
5. The method of claim 4, wherein the determining the weight of the vehicle based on the recursive least squares method based on the target weight value, the environmental data, the travel state data, and the weight determined last time the vehicle was in the acceleration mode, comprises: According to the target weight value, the environment data, the running state data and the vehicle weight determined when the vehicle is in the acceleration mode last time, determining that the vehicle weight is the initial target vehicle weight, and executing the following processes in a circulating way: Re-acquiring the running state data of the vehicle as third target data and re-acquiring the environment data of the environment where the vehicle is located as fourth target data; And determining a new target vehicle weight according to the third target data, the fourth target data, the target weight value and the target vehicle weight until the vehicle exits the acceleration mode, and taking the target vehicle weight determined in the last cycle process as the vehicle weight of the vehicle.
6. A method according to any one of claims 1-3, wherein said determining a driving pattern based on driving status data of the vehicle comprises: When the vehicle meets any one of the following judging conditions, determining a running mode to be an acceleration mode, wherein the first judging condition is that an accelerator pedal of the vehicle is in an activated state, a drive train of the vehicle is in a combined state and the acceleration of the vehicle is greater than a preset acceleration threshold value, the second judging condition is that a cruise system of the vehicle is in an activated state and the acceleration of the vehicle is greater than the preset acceleration threshold value, and the third judging condition is that an intelligent driving system of the vehicle is in an activated state and the acceleration of the vehicle is greater than the preset acceleration threshold value; and when the vehicle meets all the conditions that an accelerator pedal of the vehicle is in an unactivated state, a brake system of the vehicle is in an unactivated state, a cruise system of the vehicle is in an unactivated state, and the speed of the vehicle is greater than a preset speed threshold value, determining that the running mode is a sliding mode.
7. A vehicle weight determination apparatus, characterized in that the apparatus comprises: The first determining module is used for determining a driving mode according to the driving state data of the vehicle; The second determining module is used for determining environmental data of the environment where the vehicle is located and the weight of the vehicle determined by the vehicle in an acceleration mode when the running mode is a sliding mode, and determining the actual windage of the vehicle according to the environmental data and the running state data; And the third determining module is used for determining environmental data of the environment where the vehicle is located and the vehicle weight determined when the vehicle is in the accelerating mode last time when the vehicle is in the accelerating mode, and determining the vehicle weight of the vehicle according to the environmental data, the driving state data, the vehicle weight determined when the vehicle is in the accelerating mode last time and the vehicle weight correction parameter determined when the vehicle is in the sliding mode.
8. A non-transitory computer storage medium having stored thereon a computer program, characterized in that the program when executed by a processor realizes the steps of the method according to any of claims 1-6.
9. A vehicle, characterized in that the vehicle comprises: A processor and a memory storing machine executable instructions executable by the processor for executing the machine executable instructions to implement the weight determination method of any one of claims 1-6.

Description

Vehicle weight determining method and device, storage medium and vehicle Technical Field The present disclosure relates to the field of vehicles, and in particular, to a vehicle weight determining method, a device, a storage medium, and a vehicle. Background In the related art, a common vehicle weight determining method is based on a dynamics equation in the running process of a vehicle, and the vehicle weight is finally estimated by performing iterative calculation on the vehicle weight by acquiring information such as real-time torque, acceleration, gradient and the like of the vehicle. However, in the iterative calculation process, due to the unbiased estimation characteristic of the algorithm, deviation often exists between a calculation result and an actual situation, so that a pathological ambiguity exists in the vehicle weight information matrix. The sick information matrix may cause slow convergence speed of the calculation result, and even falls into the vehicle weight data with larger deviation, namely, the locally optimal trap, so that the vehicle weight cannot be accurately and rapidly calculated. Disclosure of Invention In order to overcome the problems in the related art, the present disclosure provides a vehicle weight determination method, apparatus, storage medium, and vehicle. According to a first aspect of an embodiment of the present disclosure, there is provided a vehicle weight determining method, including: Determining a driving mode according to the driving state data of the vehicle; When the running mode is a sliding mode, determining environment data of the environment where the vehicle is located and the vehicle weight determined by the vehicle in an accelerating mode, and determining a vehicle weight correction parameter according to the environment data, the running state data and the vehicle weight, wherein the vehicle weight correction parameter is used for representing the deviation between the vehicle weight determined by the vehicle weight determination method and the actual vehicle weight; When the vehicle running mode is the acceleration mode, determining environmental data of the environment where the vehicle is located and the vehicle weight determined when the vehicle is in the acceleration mode last time, and determining the vehicle weight of the vehicle according to the environmental data, the running state data, the vehicle weight determined when the vehicle is in the acceleration mode last time and the vehicle weight correction parameter determined when the vehicle is in the sliding mode. Optionally, the method further comprises: If the vehicle does not enter the sliding mode before entering the accelerating mode and does not enter the accelerating mode for the first time, acquiring a preset vehicle weight correction parameter, and determining the vehicle weight of the vehicle according to the environment data, the driving state data, the preset vehicle weight correction parameter and the vehicle weight determined when the vehicle is in the accelerating mode last time; if the vehicle enters the acceleration mode for the first time and does not enter the sliding mode before entering the acceleration mode, acquiring a preset vehicle weight correction parameter and a preset vehicle weight, and determining the vehicle weight of the vehicle according to the environment data, the driving state data, the preset vehicle weight correction parameter and the preset vehicle weight. Optionally, the determining a vehicle weight correction parameter according to the environmental data, the driving state data and the vehicle weight includes: according to the environment data, the driving state data and the vehicle weight, determining a correction parameter as an initial target correction parameter, and circularly executing the following processes: Re-acquiring running state data of the vehicle as first target data and re-acquiring environment data of the environment where the vehicle is located as second target data; Determining a new correction parameter according to the first target data, the second target data and the vehicle weight, adding the new correction parameter to the target correction parameter to obtain the new target correction parameter, and taking the target correction parameter determined in the last cycle process as the vehicle weight correction parameter until the vehicle exits the sliding mode. Optionally, the determining a vehicle weight correction parameter according to the environmental data, the driving state data and the vehicle weight includes: determining an actual windage of the vehicle according to the environmental data and the driving state data; determining a calculated wind resistance of the vehicle according to the driving state data and the vehicle weight; and determining the vehicle weight correction parameter according to the actual wind resistance and the calculated wind resistance. Optionally, determining the vehicle weight of the vehicle acc