CN115826544B - Auto-parts's production transfers system of participating in - Google Patents
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Abstract
The embodiment of the specification provides a production parameter adjusting system of an automobile part, a parameter adjusting station detects the factory vehicle condition of a sample vehicle, a state monitoring program is implanted according to the parameter of a calibration power response module of the sample vehicle, an off-site test terminal detects the vehicle condition, the calibration parameter is used according to the off-site test terminal, the use state is monitored, the off-site calibration parameter is uploaded to a sample management center, the center obtains an evolution function of the calibration parameter by using initial calibration parameters, off-site calibration parameters and regression fit of the use state for each sample, an evolution function prediction model is trained by the factory vehicle condition, on-site calibration parameters and the evolution function of the sample, the station is deployed at the parameter adjusting station, the station detects the factory vehicle condition of the sample vehicle, the calibration parameters are predicted, the evolution function of the calibration parameters is written into a chip together with the state monitoring program, and the post-factory program collects the calibration parameters after the vehicle state calculation and is automatically calibrated. The predicted evolution function can automatically realize adjustment after delivery, and the power stability, adjustment efficiency and convenience are improved.
Description
Technical Field
The application relates to the field of automobile production, in particular to a production parameter adjusting system for automobile accessories.
Background
For an automobile, a driver performs driving operation through input devices such as an accelerator, a brake, a reverse disc and the like, and the automobile can reflect what is reflected, which is the logic inside the automobile, if the automobile is expected to respond to the operation of a user, the automobile power system needs to be adjusted according to the expected output power state (such as acceleration according to the expected acceleration and steering according to the expected angle).
At present, the current mode of in-industry calibration is to detect the universal calibration parameters before the mass production vehicle leaves the factory, and then fine-tune the calibration parameters until the expected response is achieved, and after leaving the factory, the mass production vehicle does not calibrate the dynamic response parameters any more, but in fact, the performance of the vehicle is continuously changed, so that the calibration parameters before leaving the factory and the performance before leaving the factory can show the optimal response effect, and the response effect of the calibration parameters before leaving the factory can be changed along with the change of the performance of the vehicle, so that the dynamic is unstable, and if each vehicle leaves the factory to carry out 4S shop calibration, the efficiency is low and extremely inconvenient.
Therefore, it is necessary to provide a stable production parameter-adjusting system.
Disclosure of Invention
The embodiment of the specification provides a production parameter adjusting system of an automobile part, which is used for improving the stability, efficiency and convenience of adjusting power response parameters.
The embodiment of the specification provides a production parameter adjusting system of auto parts, including:
the parameter adjusting station is used for detecting factory vehicle condition information of a sample vehicle, adjusting parameters of a power response module in the sample vehicle according to the factory vehicle condition information, recording initial adjusting parameters and implanting a state monitoring program into the sample vehicle;
the off-site test terminal detects off-site vehicle condition information, adjusts parameters of a power response module in the sample vehicle according to the off-site vehicle condition information, monitors a use state, and uploads the monitored use state to a sample management center along with the off-site adjustment parameters;
the sample management center acquires initial tuning parameters recorded by the tuning station, acquires the off-plant tuning parameters and the use state information uploaded by the off-plant test terminal for many times, and carries out regression fitting on each sample vehicle by utilizing the initial tuning parameters, the off-plant tuning parameters and the use state information to obtain an evolution function of the tuning parameters;
training an evolution function prediction model by using factory vehicle condition information, factory calibration parameters and an evolution function of the sample vehicle;
the parameter adjusting station is used for deploying the evolution function prediction model, detecting the factory vehicle condition information of the in-production vehicle, adjusting the parameters of the power response module in the in-production vehicle according to the vehicle condition information, recording initial adjusting parameters, inputting the factory vehicle condition information of the in-production vehicle and the initial adjusting parameters into the evolution function prediction model, predicting the evolution function of the adjusting parameters of the in-production vehicle, writing the evolution function together with the use state monitoring program into a chip of the in-production vehicle, collecting the use state information of the vehicle by the state monitoring program after leaving the factory, and inputting the use state information into the adjusting parameters after the evolution calculation in the evolution function for automatic adjustment.
Optionally, the inputting the usage state information into the evolution function calculates the evolving tuning parameters, including:
and inputting the accumulated driving time after leaving the factory into the evolution function to calculate the evolutionary adjustment parameters.
Optionally, the adjusting the parameter of the power response module in the production vehicle according to the vehicle condition information includes:
constructing a calibration strategy search space according to the attribute of parameters in the power response module, constructing an incident space according to the attribute of operation information of various input devices in the production vehicle, constructing a projection space according to the attribute of the output state of the power system, and mapping coordinate points in the incident space into coordinates of the projection space after responding according to the calibration strategy of coordinate points in the calibration strategy search space;
recursion starts from the origin of the incident space: selecting an incident point according to a direction away from an original point and a preset step length, determining multi-dimensional input information corresponding to coordinates of the incident point, selecting a plurality of search points in the adjustment strategy search space, moving the search points in the search space, determining an adjustment strategy at the moved search points, providing parameters of the adjustment strategy to a power response module, controlling various input devices of the on-board vehicle to move by using the multi-dimensional input information, collecting the output state of a power system of the on-board vehicle, calculating the reward value of the output state of the power system by using a preconfigured reward function, and moving the search points;
and continuing to execute the recursion step, summing the reward values obtained in the moving process of the single search point to obtain a plurality of accumulated reward values, determining the coordinate sequence of the search point corresponding to the largest accumulated reward value, and assigning values to the variables of the power response module in the production vehicle according to the adjustment strategy sequence corresponding to the coordinate sequence.
Optionally, the multidimensional input information includes:
gear information, steering wheel angle signal, steering wheel rotational speed signal, steering wheel rotational direction signal, throttle position signal, clutch position, clutch movement speed signal, brake position signal, brake change speed signal and brake change direction signal.
Optionally, the selecting a plurality of search points in the tuning strategy search space includes:
dividing the adjustment strategy search space into areas, and selecting a plurality of search points in the adjustment strategy search space according to the area where the search points of the historical production vehicles are located.
Optionally, the inputting the usage state information into the evolution function to calculate the evolving tuning parameters, and performing automatic tuning includes:
when the usage state information meets the threshold value, the usage state information is input into the evolution function to calculate the evolved tuning parameters, and automatic tuning is performed.
Optionally, the usage status information is one of a time length of a factory time interval current time and an accumulated start time.
Optionally, the inputting the usage state information into the evolution function to calculate the evolving tuning parameters when the usage state information meets a threshold, including:
and periodically inputting the acquired use state information into the evolution function to calculate the evolved tuning parameters.
Optionally, the parameter tuning station is further configured to: and constructing a reward function according to the smoothness, the oil consumption degree and the acuity of the output state of the power system.
According to the technical schemes provided by the embodiments of the specification, the factory vehicle condition of a sample vehicle is detected through a parameter adjusting station, a state monitoring program is implanted, an off-site test terminal detects the vehicle condition according to the parameter of a power response module, the use state is monitored according to the adjustment parameter of the off-site test terminal, the off-site test terminal is uploaded to a sample management center together with the off-site adjustment parameter, the center obtains an evolution function of the adjustment parameter by using initial adjustment parameters, the off-site adjustment parameter and state regression fit for each sample, the factory vehicle condition of the sample, the on-site adjustment parameter and the evolution function are used for training an evolution function prediction model, the station is deployed at the parameter adjusting station, the station detects the factory vehicle condition of the vehicle, the adjustment parameter and predicts the evolution function of the adjustment parameter, the state monitoring program is written into a chip, and the post-factory program collects the adjustment parameter after the vehicle state calculation and evolution. The predicted evolution function can automatically realize adjustment after delivery, and the power stability, adjustment efficiency and convenience are improved.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 is a schematic structural diagram of a production parameter adjusting system for an automobile part according to an embodiment of the present disclosure.
Description of the embodiments
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals in the drawings denote the same or similar elements, components or portions, and thus a repetitive description thereof will be omitted.
The features, structures, characteristics or other details described in a particular embodiment do not exclude that may be combined in one or more other embodiments in a suitable manner, without departing from the technical idea of the invention.
In the description of specific embodiments, features, structures, characteristics, or other details described in the present invention are provided to enable one skilled in the art to fully understand the embodiments. However, it is not excluded that one skilled in the art may practice the present invention without one or more of the specific features, structures, characteristics, or other details.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the order of actual execution may be changed according to actual situations.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Fig. 1 is a schematic structural diagram of a parameter adjusting system for producing automobile parts according to an embodiment of the present disclosure, where the method may include:
the parameter adjusting station 101 is used for detecting factory vehicle condition information of a sample vehicle, adjusting parameters of a power response module in the sample vehicle according to the factory vehicle condition information, recording initial adjustment parameters and implanting a state monitoring program into the sample vehicle;
the off-site test terminal 102 detects off-site vehicle condition information, adjusts parameters of a power response module in the sample vehicle according to the off-site vehicle condition information, monitors a use state, and uploads the monitored use state to the sample management center 103 together with the off-site adjustment parameters;
the sample management center acquires initial tuning parameters recorded by the tuning station, acquires the off-plant tuning parameters and the use state information uploaded by the off-plant test terminal for many times, and carries out regression fitting on each sample vehicle by utilizing the initial tuning parameters, the off-plant tuning parameters and the use state information to obtain an evolution function of the tuning parameters;
training an evolution function prediction model by using factory vehicle condition information, factory calibration parameters and an evolution function of the sample vehicle;
the parameter adjusting station is used for deploying the evolution function prediction model, detecting the factory vehicle condition information of the in-production vehicle, adjusting the parameters of the power response module in the in-production vehicle according to the vehicle condition information, recording initial adjusting parameters, inputting the factory vehicle condition information of the in-production vehicle and the initial adjusting parameters into the evolution function prediction model, predicting the evolution function of the adjusting parameters of the in-production vehicle, writing the evolution function together with the use state monitoring program into a chip of the in-production vehicle, collecting the use state information of the vehicle by the state monitoring program after leaving the factory, and inputting the use state information into the adjusting parameters after the evolution calculation in the evolution function for automatic adjustment.
The parameter adjustment station 101 may be located in a whole vehicle factory, the vehicle condition information may refer to an output state of the vehicle to the driver input action, the factory vehicle condition information is detected in the factory before factory delivery, and for convenience of distinguishing, the parameter adjusted at this time may be called an initial adjustment parameter.
The sample vehicle can be randomly selected from mass production vehicles.
The calibrated parameter is a parameter of the power response module. The process of response is actually a process of mapping according to a certain rule, and can be regarded as a process of calculating a function value from an argument.
The state monitoring program can be used for monitoring the use state of the vehicle, and the program is activated after leaving the factory so as to monitor and record.
The usage state may be the cumulative driving time after delivery or the time length of the current time of the delivery time interval.
Thus, in the embodiment of the present specification, the inputting the usage state information into the evolution function to calculate the evolving tuning parameters may include:
and inputting the accumulated driving time after leaving the factory into the evolution function to calculate the evolutionary adjustment parameters.
For sample vehicles, vehicle condition information can be detected in a 4S store, so that the vehicle condition information can be called as out-of-factory vehicle condition information for convenience of distinguishing, and detection can be performed at a plurality of time points, so that each sample vehicle is provided with a plurality of out-of-factory vehicle condition information and corresponding use state information to form a sequence.
The sample management center can acquire various information of the sample vehicle, including various vehicle condition information, calibration parameters and subsequently collected using state information.
So that the sample vehicle can be processed.
Firstly, regression fitting can be carried out on each sample vehicle by utilizing initial adjustment parameters, off-plant adjustment parameters and using state information to obtain an evolution function of the adjustment parameters, so as to obtain an evolution rule of the adjustment parameters of the sample vehicle.
Then, the evolution function of the calibration parameters of the sample vehicle is used as a training target, factory vehicle condition information and factory calibration parameters of the sample vehicle are used for training, and internal relations between the evolution rule of the calibration parameters and the individual conditions of the vehicles can be mined, so that the evolution rule of the calibration parameters of each vehicle can be predicted in a factory according to the individual characteristics of each vehicle, actual measurement is carried out after a period of factory use is not needed, and convenience and efficiency are high.
Thus, the evolution-function prediction model may be deployed into a call site.
In order to facilitate the determination of what tuning parameters should be used for individual characteristics of the vehicle after a certain point in time after shipment, a usage status monitoring program needs to be written into the chip of the production vehicle for monitoring.
Here, the time monitoring may be, for example, once a month.
In one application scenario, a vehicle detects that the individual response of the vehicle has changed at month 2, possibly because the vehicle has just passed the break-in period, and then is recalibrated, and later, the vehicle has a driving life of 3 years, indicating that the vehicle has experienced an aging period, and many parts have worn out, and therefore, it is also necessary to recalibrate, which is typical of both evolution modes.
In order to obtain a better tuning effect, the search space can be established for the tuning strategy by combining the idea of reinforcement learning, so that a plurality of tuning strategies can be provided for comparison.
For the operation of various input devices in a vehicle, each operation is required, and each operation is actually traversed, so we can also create a space for it, which can be called the incident space because it represents an input.
For the power system output state, we can also construct a space for it, which can be called the projection space.
In this way, after the coordinate points (may be referred to as the incident points) in the incident space respond according to the adjustment strategy that the coordinate points (may be referred to as the search points) in the adjustment strategy search space, the coordinate points (may be referred to as the output states) in the projection space can be mapped.
In an embodiment of the present disclosure, the adjusting the parameter of the power response module in the production vehicle according to the vehicle condition information includes:
constructing a calibration strategy search space according to the attribute of parameters in the power response module, constructing an incident space according to the attribute of operation information of various input devices in the production vehicle, constructing a projection space according to the attribute of the output state of the power system, and mapping coordinate points in the incident space into coordinates of the projection space after responding according to the calibration strategy of coordinate points in the calibration strategy search space;
recursion is started from the origin of the incident space in a direction away from the origin: selecting an incident point according to a preset step length, determining multi-dimensional input information corresponding to the coordinate of the incident point, selecting a plurality of search points in the adjustment strategy search space, moving the search points in the search space, determining an adjustment strategy at the moved search points, providing parameters of the adjustment strategy to a power response module, controlling the movement of various input devices of the on-board vehicle by using the multi-dimensional input information, collecting the output state of a power system of the on-board vehicle, calculating the rewarding value of the output state of the power system by using a preconfigured rewarding function, and moving the search points;
and continuing to execute the recursion step, summing the reward values obtained in the moving process of the single search point to obtain a plurality of accumulated reward values, determining the coordinate sequence of the search point corresponding to the largest accumulated reward value, and assigning values to the variables of the power response module in the production vehicle according to the adjustment strategy sequence corresponding to the coordinate sequence.
The attribute of the operation information of the various input devices in the vehicle may refer to various actions of the driver, such as jerking the accelerator and slamming the steering wheel, and of course, only qualitative indication is needed for the specific implementation.
Various actions of the driver may be represented by signals sensed by the sensors.
Thus, in the embodiment of the present specification, the multidimensional input information may include:
gear information, steering wheel angle signal, steering wheel rotational speed signal, steering wheel rotational direction signal, throttle position signal, clutch position, clutch movement speed signal, brake position signal, brake change speed signal and brake change direction signal.
Since various actions of the driver are input and need to be traversed, the iteration can be performed from the origin of the incident space.
The parameters are provided to the power response module by using the assumption to know what output state is generated by the power system for the parameter adjustment according to the strategy so as to evaluate by using the reward function.
Because the calibration is continuous, only one incident point is assumed at a time, only one calibration effect is obtained, and the final calibration effect is considered, so that the total calibration effect is better, the prize value which is pushed out each time is added and summed to be used as the total calibration effect, and different total calibration effects are compared, so that which strategy series is better can be judged.
The recursion process is that the search points are moved, the adjustment strategy is determined, the power response module is provided for making assumption, the next incident point is used for controlling the vehicle, the state of the output of the power system is obtained after the vehicle responds, the advantages and disadvantages of each adjustment strategy are evaluated, and as the search points are moved for a plurality of times, each search point forms a track, and the track can be exactly used as an adjustment strategy sequence for traversing and adjusting the input, so that the refinement is realized.
In an embodiment of the present disclosure, the selecting a plurality of search points in the tuning strategy search space includes:
dividing the adjustment strategy search space into areas, and selecting a plurality of search points in the adjustment strategy search space according to the area where the search points of the historical production vehicles are located.
Thus, the previous experience can be used for reference, and the efficiency is improved.
This may indicate in a practical application scenario that the response of the car to the driver operation is relatively gentle and less sensitive at the beginning, so that a region where the relatively gentle education parameters are located may be selected, for example, the response of the brake stepping to the last car is greater.
In an embodiment of the present disclosure, the inputting the usage state information into the evolution function to calculate the evolving tuning parameter, and performing automatic tuning includes:
when the usage state information meets the threshold value, the usage state information is input into the evolution function to calculate the evolved tuning parameters, and automatic tuning is performed.
Thus, efficiency and convenience are improved.
In this embodiment of the present disclosure, the usage status information is one of a time length of a factory time interval current time and an accumulated start time.
In an embodiment of the present disclosure, the inputting the usage state information into the evolution function when the usage state information meets a threshold value, and calculating the evolving tuning parameter includes:
and periodically inputting the acquired use state information into the evolution function to calculate the evolved tuning parameters.
In the embodiment of the present specification, the parameter tuning station is further configured to: and constructing a reward function according to the smoothness, the oil consumption degree and the acuity of the output state of the power system.
The stability may be whether a curve formed between the tuning parameters is smooth or whether the higher derivative is continuous. The fuel consumption and the power performance are mutually tied, and balance needs to be performed therein, and the specific fuel consumption is not explained, and the acuity can refer to the slope of a curve formed between the tuning parameters.
The system detects the factory vehicle condition of a sample vehicle through a parameter adjusting station, a state monitoring program is implanted, an off-site test terminal detects the vehicle condition according to the parameter of a power response adjusting module, the use state is monitored according to the adjustment parameter, the off-site adjustment parameter is uploaded to a sample management center, the center obtains an evolution function of the adjustment parameter by utilizing initial adjustment parameters, off-site adjustment parameters and regression fit of the use state on each sample, the factory vehicle condition of the sample, the on-site adjustment parameters and the evolution function are used for training an evolution function prediction model, the station is deployed at the parameter adjusting station, the station detects the factory vehicle condition of the product vehicle, the adjustment parameters and predicts the evolution function of the adjustment parameters, the station is written into a chip together with the state monitoring program, and the post-factory program collects the adjustment parameters after the vehicle state calculation and evolution. The predicted evolution function can automatically realize adjustment after delivery, and the power stability, adjustment efficiency and convenience are improved.
The above-described specific embodiments further describe the objects, technical solutions and advantageous effects of the present invention in detail, and it should be understood that the present invention is not inherently related to any particular computer, virtual device or electronic apparatus, and various general-purpose devices may also implement the present invention. The foregoing description of the embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (9)
1. A system for adjusting parameters in the production of automotive parts, comprising:
the parameter adjusting station is used for detecting factory vehicle condition information of a sample vehicle, adjusting parameters of a power response module in the sample vehicle according to the factory vehicle condition information, recording initial adjusting parameters and implanting a state monitoring program into the sample vehicle;
the off-site test terminal detects off-site vehicle condition information, adjusts parameters of a power response module in the sample vehicle according to the off-site vehicle condition information, monitors a use state, and uploads the monitored use state to a sample management center along with the off-site adjustment parameters;
the sample management center acquires initial tuning parameters recorded by the tuning station, acquires the off-plant tuning parameters and the use state information uploaded by the off-plant test terminal for many times, and carries out regression fitting on each sample vehicle by utilizing the initial tuning parameters, the off-plant tuning parameters and the use state information to obtain an evolution function of the tuning parameters;
training an evolution function prediction model by using factory vehicle condition information, factory calibration parameters and an evolution function of the sample vehicle;
the parameter adjusting station is used for deploying the evolution function prediction model, detecting the factory vehicle condition information of the in-production vehicle, adjusting the parameters of the power response module in the in-production vehicle according to the vehicle condition information, recording initial adjusting parameters, inputting the factory vehicle condition information of the in-production vehicle and the initial adjusting parameters into the evolution function prediction model, predicting the evolution function of the adjusting parameters of the in-production vehicle, writing the evolution function together with the state monitoring program into a chip of the in-production vehicle, collecting the use state information of the vehicle by the state monitoring program after leaving the factory, inputting the use state information into the evolving parameter calculated by the evolution function, and performing automatic adjustment.
2. The system of claim 1, wherein said inputting said usage state information into said evolution function to calculate an evolving tuning parameter comprises:
and inputting the accumulated driving time after leaving the factory into the evolution function to calculate the evolutionary adjustment parameters.
3. The system of claim 1, wherein the adjusting parameters of the power response module in the production vehicle based on the vehicle condition information comprises:
constructing a calibration strategy search space according to the attribute of parameters in the power response module, constructing an incident space according to the attribute of operation information of various input devices in the production vehicle, constructing a projection space according to the attribute of the output state of the power system, and mapping coordinate points in the incident space into coordinates of the projection space after responding according to the calibration strategy at the coordinate points in the calibration strategy search space;
recursion is performed from an origin of the incident space in a direction away from the origin: selecting an incident point according to a preset step length, determining multi-dimensional input information corresponding to coordinates at the incident point, selecting a plurality of search points in the adjustment strategy search space, moving the search points in the search space, determining an adjustment strategy at the moved search points, providing parameters of the adjustment strategy to a power response module, controlling the movement of various input devices of the on-board vehicle by using the multi-dimensional input information, collecting the output state of a power system of the on-board vehicle, calculating the rewarding value of the output state of the power system by using a preconfigured rewarding function, and moving the search points;
and continuing to execute the recursion step, summing the reward values obtained in the moving process of the single search point to obtain a plurality of accumulated reward values, determining the coordinate sequence of the search point corresponding to the largest accumulated reward value, and assigning values to the variables of the power response module in the production vehicle according to the adjustment strategy sequence corresponding to the coordinate sequence.
4. The system of claim 3, wherein the multi-dimensional input information comprises:
gear information, steering wheel angle signal, steering wheel rotational speed signal, steering wheel rotational direction signal, throttle position signal, clutch position, clutch movement speed signal, brake position signal, brake change speed signal and brake change direction signal.
5. The system of claim 3, wherein the selecting a plurality of search points in the tuning strategy search space comprises:
dividing the adjustment strategy search space into areas, and selecting a plurality of search points in the adjustment strategy search space according to the area where the search points of the historical production vehicles are located.
6. The system of claim 1, wherein said inputting said usage state information into said evolution function to calculate an evolving tuning parameter, performing an automatic tuning, comprises:
when the usage state information meets the threshold value, the usage state information is input into the evolution function to calculate the evolved tuning parameters, and automatic tuning is performed.
7. The system of claim 6, wherein the usage status information is one of a length of time and a cumulative driving time of a factory time interval current time.
8. The system of claim 7, wherein said inputting said usage state information into said evolution function to calculate an evolving tuning parameter when it meets a threshold, comprises:
and periodically inputting the acquired use state information into the evolution function to calculate the evolved tuning parameters.
9. The system of claim 1, wherein the call-in site is further configured to: and constructing a reward function according to the smoothness, the oil consumption degree and the acuity of the output state of the power system.
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| DE102021206880A1 (en) * | 2021-06-30 | 2023-01-05 | Robert Bosch Gesellschaft mit beschränkter Haftung | Method and device for the optimal parameterization of a driving dynamics control system for vehicles |
| CN113468674B (en) * | 2021-07-23 | 2022-03-04 | 上海紫荆桃李科技有限公司 | Automotive interior spare surface sound production timing system based on neural network |
| CN114604255A (en) * | 2022-04-20 | 2022-06-10 | 沐风电子科技(广州)有限公司 | Vehicle control method, vehicle control device, computer device, and storage medium |
| CN114969986A (en) * | 2022-06-24 | 2022-08-30 | 上海帆一尚行科技有限公司 | Method and device for calibrating vehicle power parameters and electronic equipment |
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