Body contact type safety warning system based on vehicle state

Abstract

The invention discloses a body contact type safety warning system based on a vehicle state, which relates to the technical field of vehicle safety early warning and comprises a data acquisition module, a data processing module, a vibration prompt module and a man-machine interaction module, the data acquisition module comprises a whole vehicle data acquisition unit, a motor data acquisition unit and a battery data acquisition unit and is used for acquiring system data; the data processing module comprises a whole vehicle data calculation unit, a motor data calculation unit and a battery data calculation unit, and is used for calculating a whole vehicle motion characteristic index, motor stability, excess discharge frequency, a hydrogen concentration rising rate and a battery temperature index; the vibration prompt module comprises a judgment unit and a prompt execution unit and is used for carrying out early warning judgment and carrying out graded vibration prompt on a driver according to an early warning judgment result; the man-machine interaction module comprises an interaction unit and a storage unit and is used for providing an operation interface for a user, receiving a user operation instruction, providing visual feedback and storing system data.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle safety warning, and in particular to a body-contact safety warning system based on vehicle status. Background Art

[0002] In recent years, thanks to the rapid development of fields such as sensing technology, communication technology, and control technology, intelligent assisted driving has become a new trend in the intelligent connected vehicle market, and the popularization degree of functions such as automatic parking, conditional driving assistance, and adaptive cruise has increased rapidly. Considering that there is still a possibility of encountering complex road conditions or abnormal situations during assisted driving or autonomous driving, it is of great significance for the vehicle to automatically give warning prompts to the driver. At the same time, as intelligent driving technology becomes more mature, it is foreseeable that the driver will concentrate on using mobile phones, relaxing, or communicating with passengers without manual driving, and it is easy to ignore the warning to the driver through traditional sound and light prompts. In addition, the assisted driving / intelligent driving of intelligent connected vehicles depends on the perception of the vehicle's external environment, and there is a possibility of missed warning when external sensors such as high-definition cameras, lidar, or millimeter-wave radars malfunction. Therefore, during vehicle driving, focusing on the vehicle's own internal state and warning the driver against potential risk situations through mandatory body-contact reminders is a technical method with application prospects.

[0003] Currently, Chinese Patent Application No. CN202410940079.X discloses a vehicle collision warning method, a vehicle controller, and a vehicle. The application includes: the warning method includes obtaining the current first relative distance and first relative speed between the vehicle and an obstacle; judging whether the braking system performs active braking according to the first relative distance and the first relative speed; when the braking system does not perform active braking, obtaining the first target deceleration of the vehicle; when the first target deceleration is greater than a first preset threshold, controlling the human-machine interaction system to send a reminder message to the driver; when no deceleration operation of the driver is detected within a first preset time period, obtaining the second target deceleration of the vehicle; the second target deceleration and the first target deceleration are the decelerations required for the vehicle to avoid colliding with the obstacle at different times; when the second target deceleration is greater than the first preset threshold, controlling the suspension system to perform lifting movement to vibrate the vehicle in the height direction, reducing the risk of secondary accidents and improving driving safety. This solution focuses on obtaining information data from the external environment through sensors such as lidar, millimeter-wave radar, and cameras. Under harsh weather conditions such as heavy rain, heavy snow, and thick fog, or complex electromagnetic environment conditions, the accuracy of external information data will be significantly negatively affected. At the same time, there is also the problem that the driver's attention is not concentrated during vehicle autonomous driving, and traditional sound and light reminders are easily ignored. Summary of the Invention

[0004] The technical problem solved by the present invention is that traditional methods focus on obtaining information data from the external environment through sensors such as lidar, millimeter-wave radar, and cameras when warning and reminding drivers. Under harsh weather conditions such as heavy rain, heavy snow, and thick fog, or complex electromagnetic environment conditions, the accuracy of the collected external information data is significantly reduced. At the same time, when the vehicle is in intelligent driving, the driver's attention is often not concentrated on the road conditions. When it is necessary to manually take over and switch to manual driving, traditional acoustic and optical warnings are easily ignored by the driver.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: A body contact type safety warning system based on vehicle status, including: a data acquisition module, a data processing module, a vibration prompt module, and a human-computer interaction module; The data acquisition module includes a vehicle data acquisition unit, a motor data acquisition unit, a battery data acquisition unit, and an intelligent driving data acquisition unit, which are used to collect the first data set, the second data set, and the third data set through sensors; The data processing module includes a vehicle data calculation unit, a motor data calculation unit, and a battery data calculation unit, which are used to calculate vehicle motion characteristic indicators, motor stability, over-discharge frequency, hydrogen concentration rise rate, and battery temperature indicators; The vibration prompt module includes a judgment unit and a reminder execution unit, which are used to perform warning discrimination to obtain a warning rating result and perform hierarchical warning reminders to the driver; The human-computer interaction module includes an interaction unit and a storage unit, which are used to provide an operation interface to the user, receive user operation instructions, provide visual feedback, and store historical data.

[0006] As a preferred solution of the body contact type safety warning system based on vehicle status of the present invention, wherein: the vehicle data acquisition unit is used to collect data on the overall motion state of the target vehicle during driving to obtain the first data set, and the first data set includes wheel speed data, longitudinal acceleration data, lateral acceleration data, yaw angular velocity, and lateral braking torque. The wheel speed data is measured by a wheel speed sensor, the longitudinal acceleration data and lateral acceleration data of the target vehicle are measured by an accelerometer, the yaw angular velocity of the target vehicle is measured by a gyroscope, and the lateral braking torque is measured by a torque sensor; The motor data acquisition unit is used to collect data from the set of motor operating states during the driving of the target vehicle to obtain a second data set, where the second data set includes three-phase current data, three-phase voltage data, motor rotor displacement angle data, and motor speed data. The three-phase current data is obtained by measuring the motor circuit through a current transformer, the three-phase voltage data is obtained by measuring the motor circuit through a voltage transformer, the motor rotor displacement angle data is obtained by measuring the motor rotor through an inductance sensor, and the motor speed data is obtained by measuring the motor rotor through a resolver. The battery data acquisition unit is used to collect data from the set of battery operating states during the driving of the target vehicle to obtain a third data set, where the third data set includes battery output current data, hydrogen concentration data, and a battery pack temperature data set. The battery output current data is measured through a battery current sensor, the hydrogen concentration data is measured for the battery compartment environment through a hydrogen sensor, and the battery pack temperature data set is measured for each battery cell in the battery pack through a temperature sensor. The intelligent driving data acquisition unit is used to monitor the intelligent driving system during the driving of the target vehicle to obtain a fourth data set, where the fourth data set includes an assisted / autonomous driving service failure signal, an assisted / autonomous driving service degradation signal, a takeover detection failure signal, and a network anomaly signal.

[0007] As a preferred embodiment of the body contact-based safety warning system based on vehicle status according to the present invention, the vehicle data calculation unit is used to calculate a first characteristic index based on the first data set to obtain a vehicle prediction characteristic index. The logic of the first characteristic index calculation includes: calculating the longitudinal speed by multiplying the wheel speed data and the wheel circumference, calculating the lateral speed by integrating the yaw angular velocity and the lateral acceleration, and establishing a prediction longitudinal speed difference equation based on the longitudinal speed, longitudinal acceleration, lateral speed, lateral acceleration, and yaw angular velocity. Establishing a prediction yaw angular velocity difference equation based on the yaw angular velocity, lateral turning moment, and lateral moment of inertia, and establishing a prediction vehicle side force difference equation based on the lateral acceleration in the first data set. Establishing a system state equation based on the prediction yaw angular velocity difference equation, the prediction longitudinal speed difference equation, and the prediction vehicle side force difference equation, performing a Ud transformation on the system state equation through a nonlinear Kalman filter algorithm to obtain Sigma prediction sample points, calculating a predicted system state value, a predicted system state covariance matrix, a measurement predicted value, and a measurement predicted covariance matrix based on the Sigma prediction sample points, calculating a cross-correlation covariance matrix based on the predicted system state value and the measurement predicted value, calculating a Kalman gain based on the cross-correlation covariance matrix and the measurement predicted covariance matrix, and calculating a predicted yaw angular velocity, a predicted longitudinal speed, and a predicted vehicle side force based on the Kalman gain, the predicted system state value, and the measurement predicted value. The vehicle motion characteristic index is calculated based on vehicle mass, predicted yaw rate, predicted longitudinal speed, and predicted vehicle side force; Its calculation expression is: ; ; ; ; wherein, represents the longitudinal speed at the (k + 1)-th sampling moment, represents the longitudinal speed at the k-th sampling moment, represents the lateral speed at the k-th sampling moment, represents the longitudinal acceleration at the k-th sampling moment, represents the yaw rate at the k-th sampling moment, represents the yaw rate at the (k + 1)-th sampling moment, represents the lateral moment of inertia, represents the lateral turning moment at the k-th sampling moment, represents the vehicle side force at the (k + 1)-th sampling moment, represents the lateral acceleration at the k-th sampling moment, PF represents the maximum force value parameter, DC represents the wind resistance parameter, CF represents the wheel curvature parameter, represents the sine function, arctan represents the arctangent function, WMS represents the vehicle motion characteristic index, represents the predicted longitudinal speed, represents the predicted longitudinal speed weight, represents the predicted yaw rate, represents the predicted yaw rate weight, represents the predicted vehicle side force, represents the predicted vehicle side force weight, represents the sampling interval of the vehicle data acquisition unit, m represents the vehicle mass, represents the unit time with a value of 1.

[0008] As a preferred solution of the body contact type safety warning system based on vehicle state according to the present invention, wherein: the motor data calculation unit is used to calculate the motor stability according to the second data set, and the logic of the second characteristic index calculation includes: calculating the motor power through the three-phase current data and the three-phase voltage data, calculating the magnetic flux linkage value of the motor stator winding through the three-phase current data and the electromagnetic mutual inductance coefficient, calculating the motor electromagnetic deflection torque based on the magnetic flux linkage value, the three-phase current data, the motor rotor displacement angle data, and the total number of motor magnetic poles, and calculating the motor stability based on the motor electromagnetic deflection torque, the motor power, and the motor speed data, and its calculation expression is: ; ; Among them, EMT represents the electromagnetic deflection torque of the motor, PPC represents the total number of motor magnetic poles, represents taking the partial derivative, represents the displacement angle of the motor rotor, represents the three-phase current, T represents the transpose, MFL represents the magnetic flux linkage value, CVM represents the motor stability, represents taking the absolute value, represents the sampling interval of the battery data acquisition unit, represents the torque power weight, ΔEMT represents the change in the electromagnetic deflection torque of the motor, ΔPOM represents the change in the motor power, represents the reference motor power change amount with a value of 1, represents the torque speed weight, ΔSOM represents the change in the motor speed, represents the reference motor speed change amount with a value of 1. [[ID=?]] [[ID=?]]

[0009] As a preferred solution of the body contact type safety warning system based on vehicle status according to the present invention, among them: the battery data calculation unit is used to calculate the battery characteristic index according to the third data set, and the logic of the third characteristic index calculation includes: discretely sampling the battery output current data to obtain the battery output current sequence, smoothing the battery output current sequence through low-pass filtering and Lagrange interpolation method to obtain the updated battery output current sequence, statistically obtaining the number of excess current pulses based on the updated battery output current sequence and the rated current threshold value, and calculating the battery over-discharge frequency based on the number of excess current pulses and the preset time window; [[ID=3?]]Calculating the hydrogen concentration rising rate based on the hydrogen concentration data; Calculating the average battery pack temperature based on the battery pack temperature data set, sorting the battery pack temperature data set from high to low to obtain the maximum single cell temperature, and calculating the battery temperature index based on the average battery pack temperature and the maximum single cell temperature, and its calculation expression is: ; ; Among them, FOC represents the battery over-discharge frequency, NCP represents the number of excess current pulses within the preset time window, represents the preset time window duration, BTI represents the battery temperature index, AOT represents the average battery pack temperature, MIT represents the maximum single cell temperature; Among them, the rated current threshold value and the preset time window duration are system parameters preset by the user. It should be noted that there are some tags like and

[0009] in the original text which seem to be incomplete in terms of the content description. The translation is done as accurately as possible based on the available information.

[0010] As a preferred solution of the vehicle state-based physical contact safety warning system described in the present invention, wherein: the judgment unit is used to perform early warning discrimination to obtain an early warning rating result, and the early warning rating result includes no early warning, primary early warning, and advanced early warning.

[0011] As a preferred solution of the vehicle state-based physical contact safety warning system described in the present invention, wherein: the logic of the early warning discrimination includes: When the vehicle motion characteristic index is less than the first vehicle threshold, the early warning rating result is no early warning; When the vehicle motion characteristic index is greater than or equal to the first vehicle threshold and less than the second vehicle threshold, the early warning rating result is primary early warning; When the vehicle motion characteristic index is greater than or equal to the second vehicle threshold, the early warning rating result is advanced early warning; When the motor stability is less than the first motor threshold, the early warning rating result is no early warning; When the motor stability is greater than or equal to the first motor threshold and less than the second motor threshold, the early warning rating result is primary early warning; When the motor stability is greater than or equal to the second motor threshold, the early warning rating result is advanced early warning; When the over-discharge frequency is less than the discharge frequency threshold, the early warning rating result is no early warning; When the over-discharge frequency is greater than or equal to the discharge frequency threshold, the early warning rating result is advanced early warning; When the hydrogen concentration rising rate is less than the concentration rising rate threshold, the early warning rating result is no early warning; When the hydrogen concentration rising rate is greater than or equal to the concentration rising rate threshold, the early warning rating result is advanced early warning; When the battery temperature index is less than the battery temperature threshold, the early warning rating result is no early warning; When the battery temperature index is greater than or equal to the battery temperature threshold, the early warning rating result is advanced early warning; When the fourth data set is an empty set, the early warning rating result is no early warning; When the fourth data set is a non-empty set, the early warning rating result is advanced early warning.

[0012] As a preferred solution of the vehicle state-based physical contact safety warning system described in the present invention, wherein: the execution reminder unit is used to receive the early warning rating result data sent by the judgment unit, and perform hierarchical early warning reminders to the driver according to the early warning rating result.

[0013] As a preferred solution of the vehicle state-based physical contact safety warning system described in the present invention, wherein: the logic of the hierarchical early warning reminder includes: When the warning rating result is no warning required, the execution reminder unit remains in the standby state; When the warning rating result is a primary warning, the execution reminder unit is activated, causing the driver's seat belt to tighten intermittently with a preset first force, and causing the vibration belt on the target vehicle's seat belt or the headrest part of the driver's seat to vibrate intermittently with a preset normal vibration intensity and a preset normal vibration frequency. The vibration belt stops vibrating after seconds. Each second is recorded as one time. After repeating the cycle K times and then stopping, the execution reminder unit enters the standby state;

[0014] As a preferred solution of the vehicle state-based physical contact safety warning system described in the present invention, wherein: the interaction unit is used to provide an operation interface for the user, receive user operation instructions, and provide visual feedback. The user operation instructions include a system on / off instruction, a vibration off instruction, a system parameter preset instruction, and a historical record data query instruction; The system parameters in the system parameter preset instruction include vehicle mass, wheel circumference, lateral moment of inertia, electromagnetic mutual inductance coefficient, total number of motor magnetic poles, rated current threshold value, and preset time window duration; The storage unit is used to store the output data of the data acquisition module, the output data of the data processing module, the output data of the vibration prompt module, user operation instruction data, and historical record data.

[0015] Advantages of the present invention: Data collection is performed on the internal state information of the vehicle, such as the overall motion state, motor state, and battery state, without relying on the external environment, which is beneficial to reducing the interference of factors such as bad weather and complex traffic environments, and can stably provide data on the vehicle's own state information, with strong reliability. Calculating the motion prediction feature index is beneficial to improving the advance and accuracy of early warning, and enhancing the safety level of the vehicle. Calculating the motor stability can comprehensively and multi-dimensionally evaluate the operating state of the motor, which is beneficial to promptly detecting motor abnormalities. Calculating the rising rate of the hydrogen concentration in the air of the battery compartment is beneficial to accurately reflecting the hydrogen situation. At the same time, calculating the battery over-discharge frequency and battery temperature index is beneficial to warning the driver at the initial stage of battery failure. Warning discrimination is performed according to different preset thresholds to obtain three types of results: no warning, primary warning, and advanced warning, which is beneficial to accurately reflecting the actual situation of the vehicle and avoiding the problems of over-warning or under-warning. At the same time, the physical vibration of the seat belt can effectively attract the driver's attention and avoid the problem that the acoustic and optical warnings are easily ignored. The warning vibration modes are classified. The conventional intermittent vibration of the primary warning prompts the driver to pay attention to the vehicle state and road conditions, and the strong continuous vibration of the advanced warning prompts the driver to stop and check immediately, which is beneficial to reducing the time for the driver to judge the abnormal degree of the vehicle state and improving the driver's reaction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 FIG. is a schematic diagram of the basic framework of a body contact type safety warning system based on vehicle state provided by an embodiment of the present invention; Figure 2 FIG. is a schematic diagram of the processing flow of a body contact type safety warning system based on vehicle state provided by an embodiment of the present invention; Figure 3 FIG. is a schematic diagram of the processing flow of a data processing module provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention is made in conjunction with the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments.

[0018] Referring to Figures 1-3 , an embodiment of the present invention provides a body contact type safety warning system based on vehicle state, including: a data collection module, a data processing module, a vibration prompt module, and a human-machine interaction module; The data collection module includes a vehicle data collection unit, a motor data collection unit, a battery data collection unit, and an intelligent driving data collection unit, and is used to collect the first data set, the second data set, and the third data set through sensors; The data processing module includes a vehicle data calculation unit, a motor data calculation unit, and a battery data calculation unit, which are used to calculate vehicle motion characteristic indicators, motor stability, excessive discharge frequency, hydrogen concentration rise rate, and battery temperature indicators; The vibration prompt module includes a judgment unit and a reminder execution unit, which are used to perform early warning discrimination to obtain an early warning rating result and give a hierarchical early warning reminder to the driver; The human-machine interaction module includes an interaction unit and a storage unit, which are used to provide an operation interface for the user, receive user operation instructions, provide visual feedback, and store historical data.

[0019] In this embodiment, the vehicle data acquisition unit is used to acquire data on the overall motion state of the target vehicle during driving to obtain a first data set. The first data set includes wheel speed data, longitudinal acceleration data, lateral acceleration data, yaw angular velocity, and lateral turning torque. The wheel speed data is measured by a wheel speed sensor, the longitudinal acceleration data and lateral acceleration data of the target vehicle are measured by an accelerometer, the yaw angular velocity of the target vehicle is measured by a gyroscope, and the lateral braking torque is measured by a torque sensor; The motor data acquisition unit is used to acquire data on the motor operation state set of the target vehicle during driving to obtain a second data set. The second data set includes three-phase current data, three-phase voltage data, motor rotor displacement angle data, and motor speed data. The three-phase current data is measured by a current transformer for the motor circuit, the three-phase voltage data is measured by a voltage transformer for the motor circuit, the motor rotor displacement angle data is measured by an inductive sensor for the motor rotor, and the motor speed data is measured by a resolver for the motor rotor; The battery data acquisition unit is used to acquire data on the battery operation state set of the target vehicle during driving to obtain a third data set. The third data set includes battery output current data, hydrogen concentration data, and battery pack temperature data set. The battery output current data is measured by a battery current sensor, the hydrogen concentration data is measured by a hydrogen sensor for the battery compartment environment, and the battery pack temperature data set is measured by a temperature sensor for each battery cell in the battery pack; The intelligent driving data acquisition unit is used to monitor the intelligent driving system of the target vehicle during driving to obtain a fourth data set. The fourth data set includes auxiliary / automatic driving service failure signals, auxiliary / automatic driving service degradation signals, takeover detection failure signals, and network anomaly signals.

[0020] In this embodiment, the vehicle data calculation unit is used to calculate the vehicle prediction characteristic index according to the first data set. The logic of the first characteristic index calculation includes: calculating the longitudinal speed by multiplying the wheel speed data and the wheel circumference, calculating the lateral speed by integrating the yaw angular velocity and the lateral acceleration, and establishing a prediction longitudinal speed difference equation based on the longitudinal speed, longitudinal acceleration, lateral speed, lateral acceleration and yaw angular velocity; establishing a prediction yaw angular velocity difference equation based on the yaw angular velocity, lateral turning moment and lateral moment of inertia, and establishing a prediction vehicle side force difference equation based on the lateral acceleration in the first data set; establishing a system state equation based on the prediction yaw angular velocity difference equation, prediction longitudinal speed difference equation and prediction vehicle side force difference equation, performing Ud transformation on the system state equation through the nonlinear Kalman filter algorithm to obtain Sigma prediction sample points, calculating the predicted system state value, predicted system state covariance matrix, measurement predicted value and measurement predicted covariance matrix based on the Sigma prediction sample points, calculating the cross-correlation covariance matrix based on the predicted system state value and the measurement predicted value, calculating the Kalman gain based on the cross-correlation covariance matrix and the measurement predicted covariance matrix, and calculating the predicted yaw angular velocity, predicted longitudinal speed and predicted vehicle side force based on the Kalman gain, predicted system state value and measurement predicted value; calculating the vehicle motion characteristic index based on the vehicle mass, predicted yaw angular velocity, predicted longitudinal speed and predicted vehicle side force; Its calculation expression is: ; ; ; ; where, represents the longitudinal speed at the (k + 1) sampling moment, represents the longitudinal speed at the k sampling moment, represents the lateral speed at the k sampling moment, represents the longitudinal acceleration at the k sampling moment, represents the yaw angular velocity at the k sampling moment, represents the yaw angular velocity at the (k + 1) sampling moment, represents the lateral moment of inertia, represents the lateral turning moment at the k sampling moment, represents the vehicle side force at the (k + 1) sampling moment, represents the lateral acceleration at the k sampling moment, PF represents the maximum force value parameter, DC represents the wind resistance parameter, CF represents the wheel curvature parameter, sin represents the sine function, arctan represents the arctangent function, and WMS represents the vehicle motion characteristic index. represents the predicted longitudinal speed. represents the weight value of the predicted longitudinal speed. represents the predicted yaw rate. represents the weight value of the predicted yaw rate. represents the predicted lateral force of the vehicle. represents the weight value of the predicted lateral force of the vehicle. represents the sampling interval of the vehicle data acquisition unit, and m represents the vehicle mass. represents the unit time with a value of 1.

[0021] Among them, the vehicle mass, wheel circumference, and lateral moment of inertia are system parameters set by the user according to the target vehicle.

[0022] Among them, the overall vehicle motion state is the most intuitive and significant reaction index during vehicle operation. Considering that it is difficult for the overall vehicle motion state to change immediately under the action of inertia, a reaction time needs to be reserved for the driver. Calculating the motion prediction characteristic index is beneficial to improving the advance and accuracy of early warning, and improving the safety level of the vehicle.

[0023] In this embodiment, the motor data calculation unit is used to calculate the motor stability according to the second data set. The logic of the second characteristic index calculation includes: calculating the motor power through the three-phase current data and three-phase voltage data, calculating the magnetic flux linkage value of the motor stator winding through the three-phase current data and the electromagnetic mutual inductance coefficient, calculating the motor electromagnetic deflection torque based on the magnetic flux linkage value, three-phase current data, motor rotor displacement angle data, and the total number of motor poles, and calculating the motor stability based on the motor electromagnetic deflection torque, motor power, and motor speed data. Its calculation expression is: ; ; Among them, EMT represents the motor electromagnetic deflection torque, and PPC represents the total number of motor poles. represents taking the partial derivative. represents the motor rotor displacement angle. represents the three-phase current, T represents the transpose, MFL represents the magnetic flux linkage value, and CVM represents the motor stability. represents taking the absolute value. represents the sampling interval of the battery data acquisition unit. represents the torque power weight value, ΔEMT represents the change in the motor electromagnetic deflection torque, and ΔPOM represents the change in the motor power. represents the reference motor power change amount with a value of 1. represents the torque - speed weight value, and ΔSOM represents the change in motor speed. It represents the reference change in motor speed with a value of 1. Among them, the electromagnetic mutual - inductance coefficient and the total number of motor magnetic poles are system parameters preset by the user in advance.

[0024] Among them, the electromagnetic mutual - inductance coefficient and the total number of motor magnetic poles are system parameters preset by the user according to the target vehicle. By calculating the motor stability, the operating state of the motor can be evaluated comprehensively and multi - dimensionally, which is conducive to detecting motor abnormalities in a timely manner.

[0025] Among them, the common battery types currently used in intelligent network - connected vehicles include ternary lithium batteries and lithium iron phosphate batteries. When ternary lithium batteries and lithium iron phosphate batteries malfunction and get out of control, hydrogen will be generated. Considering the characteristics of hydrogen, such as light mass, easy escape, and short residual time, the method of measuring the absolute concentration is prone to misjudgment. Calculating the rising rate of hydrogen concentration in the battery compartment environment air is conducive to accurately reflecting the hydrogen situation. At the same time, calculating the battery over - discharge frequency and the battery temperature index is conducive to warning the driver in the initial stage of battery failure.

[0026] In this embodiment, the judgment unit is used to obtain the warning rating result through warning discrimination, and the warning rating result includes no warning, primary warning, and high - level warning.

[0027] In this embodiment, the logic of warning discrimination includes: When the vehicle motion characteristic index is less than the first vehicle threshold, the warning rating result is no warning; When the vehicle motion characteristic index is greater than or equal to the first vehicle threshold and less than the second vehicle threshold, the warning rating result is primary warning; When the vehicle motion characteristic index is greater than or equal to the second vehicle threshold, the warning rating result is high - level warning; When the motor stability is less than the first motor threshold, the warning rating result is no warning; When the motor stability is greater than or equal to the first motor threshold and less than the second motor threshold, the warning rating result is primary warning; When the motor stability is greater than or equal to the second motor threshold, the warning rating result is high - level warning; When the over - discharge frequency is less than the discharge frequency threshold, the warning rating result is no warning; When the over - discharge frequency is greater than or equal to the discharge frequency threshold, the warning rating result is high - level warning; When the rising rate of hydrogen concentration is less than the concentration rising rate threshold, the warning rating result is no warning; When the rising rate of hydrogen concentration is greater than or equal to the concentration rising rate threshold, the warning rating result is high - level warning; When the battery temperature index is less than the battery temperature threshold, the early warning rating result is no early warning required; When the battery temperature index is greater than or equal to the battery temperature threshold, the early warning rating result is high-level early warning; When the fourth data set is an empty set, the early warning rating result is no early warning required; When the fourth data set is a non-empty set, the early warning rating result is high-level early warning.

[0028] In this embodiment, the execution reminder unit is used to receive the early warning rating result data sent by the judgment unit, and perform a hierarchical early warning reminder for the driver according to the early warning rating result.

[0029] In this embodiment, the logic of the hierarchical early warning reminder includes: When the early warning rating result is no early warning required, the execution reminder unit remains in the standby state; When the early warning rating result is primary early warning, the execution reminder unit is activated, causing the driver's seat belt to tighten intermittently with a preset first force, and causing the vibration belt on the safety belt of the target vehicle or on the headrest part of the driver's seat to vibrate intermittently with a preset normal vibration intensity and a preset normal vibration frequency. The vibration belt stops vibrating after seconds seconds is recorded as one time, and after repeating and cycling K times and then stopping, the execution reminder unit enters the standby state; Among them, through the vibration belt on the safety belt of the above reminder device or on the headrest part of the driver's seat, one of them, or a synchronous combination reminder method, a physical contact reminder warning is carried out; In the case of primary early warning, a speaker can also be arranged at the headrest of the driver's seat to play a prompt sound to enrich the synchronous combination reminder.

[0030] When the early warning rating result is high-level early warning, the execution reminder unit is activated, causing the vibration belt on the safety belt of the target vehicle to vibrate continuously with a preset maximum vibration intensity and a preset maximum vibration frequency, and at the same time causing the driver's seat of the target vehicle to vibrate continuously with a preset seat vibration intensity and a preset seat vibration frequency. The full-seat safety belt remains tightened with a preset second force until the driver manually turns off the early warning and then stops, and the execution reminder unit enters the standby state.

[0031] Among them, three types of results, no early warning required, primary early warning, and high-level early warning, are obtained through early warning discrimination according to different preset thresholds. Through this hierarchical early warning mechanism, it is beneficial to accurately reflect the actual situation of the vehicle and avoid the problems of over-early warning or insufficient early warning. At the same time, this application mainly uses contact-type early warning. The physical vibration of the safety belt, seat or headrest can effectively attract the driver's attention, avoiding the problem that the sound and light early warning is easily ignored, and is beneficial to reminding the driver to pay attention to the vehicle state without affecting the driver's normal driving.

[0032] During the primary warning, simultaneous reminders from the headrest, seat, and seatbelt are likely to cause redundant interference. Automobile manufacturers can flexibly arrange vibration bands on the seatbelt or headrest according to the vehicle model. In the case of a high-level warning when the situation is urgent, the sound reminder is cancelled, and only contact-based warnings with faster response and less interference are adopted.

[0033] By grading the warning vibration patterns to adapt to different levels of urgency, the driver is reminded of the vehicle status and road conditions through the regular intermittent vibration of the primary warning, and is prompted to immediately stop and check through the strong continuous vibration of the high-level warning. This helps reduce the time for the driver to judge the abnormal degree of the vehicle status and improves the driver's reaction efficiency.

[0034] In this embodiment, the interaction unit is used to provide an operation interface to the user, receive user operation instructions, and provide visual feedback. The user operation instructions include a system switch instruction, a vibration-off instruction, a system parameter presetting instruction, and a historical record data query instruction. The system parameters in the system parameter presetting instruction include vehicle mass, wheel circumference, lateral moment of inertia, electromagnetic mutual inductance coefficient, total number of motor magnetic poles, rated current threshold, and preset time window duration. The storage unit is used to store the output data of the data acquisition module, the output data of the data processing module, the output data of the vibration reminder module, user operation instruction data, and historical record data.

[0035] Those skilled in the art should understand that the embodiments of the present invention may provide a method, a system or a computer program product. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media that contain computer-usable program code. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, abbreviated as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, abbreviated as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, abbreviated as EPROM), programmable read-only memory (Programmable Red-Only Memory, abbreviated as PROM), read-only memory (Read-Only Memory, abbreviated as ROM), magnetic memory, flash memory, magnetic disk or optical disc. These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured article including an instruction device, and the instruction device implements the process Figure 1 in one process or multiple processes and / or Figure 1 the functions specified in one block or multiple blocks.

[0036] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A body contact type safety warning system based on vehicle status, characterized in that It includes: a data acquisition module, a data processing module, a vibration prompt module, and a human-machine interaction module; The data acquisition module includes a vehicle data acquisition unit, a motor data acquisition unit, a battery data acquisition unit, and an intelligent driving data acquisition unit, which are used to collect the first data set, the second data set, and the third data set through sensors; The data processing module includes a vehicle data calculation unit, a motor data calculation unit, and a battery data calculation unit, which are used to calculate vehicle motion characteristic indicators, motor stability, excessive discharge frequency, hydrogen concentration rise rate, and battery temperature indicators; The vibration prompt module includes a judgment unit and a reminder execution unit, which are used to perform early warning discrimination to obtain an early warning rating result and give a hierarchical early warning reminder to the driver; The human-machine interaction module includes an interaction unit and a storage unit, which are used to provide an operation interface for users, receive user operation instructions, provide visual feedback, and store historical data.

2. The body contact type safety warning system based on vehicle state according to claim 1, characterized in that: The vehicle data acquisition unit is used to collect data on the overall motion state of the target vehicle during driving to obtain a first data set. The first data set includes wheel speed data, longitudinal acceleration data, lateral acceleration data, yaw angular velocity, and lateral turning torque. The wheel speed data is measured by a wheel speed sensor, the longitudinal acceleration data and lateral acceleration data of the target vehicle are measured by an accelerometer, the yaw angular velocity of the target vehicle is measured by a gyroscope, and the lateral braking torque is measured by a torque sensor; The motor data acquisition unit is used to collect data on the motor operation state set of the target vehicle during driving to obtain a second data set. The second data set includes three-phase current data, three-phase voltage data, motor rotor displacement angle data, and motor speed data. The three-phase current data is measured by a current transformer for the motor circuit, the three-phase voltage data is measured by a voltage transformer for the motor circuit, the motor rotor displacement angle data is measured by an inductive sensor for the motor rotor, and the motor speed data is measured by a resolver for the motor rotor; The battery data acquisition unit is used to collect data on the battery operation state set of the target vehicle during driving to obtain a third data set. The third data set includes battery output current data, hydrogen concentration data, and battery pack temperature data set. The battery output current data is measured by a battery current sensor, the hydrogen concentration data is measured by a hydrogen sensor for the battery compartment environment, and the battery pack temperature data set is measured by a temperature sensor for each battery cell in the battery pack; The intelligent driving data acquisition unit is used to monitor the intelligent driving system of the target vehicle during driving to obtain a fourth data set. The fourth data set includes auxiliary / automatic driving service failure signals, auxiliary / automatic driving service degradation signals, takeover detection failure signals, and network anomaly signals.

3. The body contact type safety warning system based on vehicle state according to claim 1, characterized in that: The vehicle data calculation unit is used to calculate the vehicle prediction characteristic index according to the first data set. The logic of the first characteristic index calculation includes: calculating the longitudinal speed by multiplying the wheel speed data and the wheel circumference, calculating the lateral speed by integrating the yaw angular velocity and the lateral acceleration, and establishing a prediction longitudinal speed difference equation based on the longitudinal speed, longitudinal acceleration, lateral speed, lateral acceleration and yaw angular velocity; establishing a prediction yaw angular velocity difference equation based on the yaw angular velocity, lateral turning moment and lateral moment of inertia, and establishing a prediction vehicle side force difference equation based on the lateral acceleration in the first data set; establishing a system state equation based on the prediction yaw angular velocity difference equation, prediction longitudinal speed difference equation and prediction vehicle side force difference equation, performing Ud transformation on the system state equation through the non-linear Kalman filtering algorithm to obtain Sigma prediction sample points, calculating the prediction system state value, prediction system state covariance matrix, measurement prediction value and measurement prediction covariance matrix based on the Sigma prediction sample points, calculating the cross-correlation covariance matrix based on the prediction system state value and the measurement prediction value, calculating the Kalman gain based on the cross-correlation covariance matrix and the measurement prediction covariance matrix, and calculating the prediction yaw angular velocity, prediction longitudinal speed and prediction vehicle side force based on the Kalman gain, prediction system state value and measurement prediction value; calculating the vehicle motion characteristic index based on the vehicle mass, prediction yaw angular velocity, prediction longitudinal speed and prediction vehicle side force; The calculation expression is: ; ; ; ； Among them, represents the longitudinal speed at the (k + 1)-th sampling moment, represents the longitudinal speed at the k-th sampling moment, represents the lateral speed at the k-th sampling moment, represents the longitudinal acceleration at the k-th sampling moment, represents the yaw rate at the k-th sampling moment, represents the yaw rate at the (k + 1)-th sampling moment, represents the lateral moment of inertia, represents the lateral torque at the k-th sampling moment, represents the lateral force of the vehicle at the (k + 1)-th sampling moment, represents the lateral acceleration at the k-th sampling moment, PF represents the maximum force value parameter, DC represents the air resistance parameter, CF represents the wheel curvature parameter, represents the sine function, arctan represents the arctangent function, WMS represents the vehicle motion characteristic index, represents the predicted longitudinal speed, represents the weight of the predicted longitudinal speed, represents the predicted yaw rate, represents the weight of the predicted yaw rate, represents the predicted lateral force of the vehicle, represents the weight of the predicted lateral force of the vehicle, represents the sampling interval of the vehicle data acquisition unit, m represents the vehicle mass, represents the unit time with a value of 1.

4. The body contact type safety warning system based on vehicle state according to claim 1, wherein: The motor data calculation unit is used to calculate the motor stability according to the second data set. The logic of the second characteristic index calculation includes: calculating the motor power by the three-phase current data and the three-phase voltage data, calculating the magnetic flux linkage value of the motor stator winding by the three-phase current data and the electromagnetic mutual inductance coefficient, calculating the motor electromagnetic deflection torque based on the magnetic flux linkage value, three-phase current data, motor rotor displacement angle data and the total number of motor magnetic poles, and calculating the motor stability based on the motor electromagnetic deflection torque, motor power and motor speed data. The calculation expression is: ； ； Among them, EMT represents the electromagnetic deflection torque of the motor, and PPC represents the total number of motor poles. represents taking the partial derivative. represents the displacement angle of the motor rotor. represents the three-phase current, T represents the transpose, MFL represents the value of the magnetic flux linkage, and CVM represents the motor stability. represents taking the absolute value. represents the sampling interval of the battery data acquisition unit. represents the torque power weight, ΔEMT represents the change in the electromagnetic deflection torque of the motor, and ΔPOM represents the change in the motor power. represents the reference motor power change with a value of 1. represents the torque speed weight, and ΔSOM represents the change in the motor speed. represents the reference motor speed change with a value of 1.

5. The body contact type safety warning system based on vehicle state according to claim 1, characterized in that: The battery data calculation unit is used to calculate the battery characteristic index according to the third data set. The logic of the third characteristic index calculation includes: discretely sampling the battery output current data to obtain a battery output current sequence, smoothing the battery output current sequence through low-pass filtering and Lagrange interpolation method to obtain a battery output current updated sequence, statistically obtaining the number of excess current pulses based on the battery output current updated sequence and the rated current threshold value, and calculating the battery over-discharge frequency based on the number of excess current pulses and the preset time window; calculating the hydrogen concentration rising rate based on the hydrogen concentration data; calculating the average battery pack temperature based on the battery pack temperature data set, sorting the battery pack temperature data set from high to low to obtain the maximum single cell temperature, and calculating the battery temperature index based on the average battery pack temperature and the maximum single cell temperature. The calculation expression is: ； ； Among them, FOC represents the frequency of excessive battery discharge, NCP represents the number of excessive current pulses within a preset time window, represents the duration of the preset time window, BTI represents the battery temperature index, AOT represents the average battery pack temperature, and MIT represents the maximum single cell temperature; Among them, the rated current threshold value and the preset time window duration are system parameters preset by the user.

6. The body contact type safety warning system based on vehicle state according to claim 1, characterized in that: The judgment unit is used to perform early warning discrimination to obtain an early warning rating result, and the early warning rating result includes no early warning, primary early warning, and advanced early warning.

7. The body contact type safety warning system based on vehicle state according to claim 6, wherein: The logic of the early warning discrimination includes: When the vehicle motion characteristic index is less than the first vehicle threshold, the early warning rating result is no early warning; When the vehicle motion characteristic index is greater than or equal to the first vehicle threshold and less than the second vehicle threshold, the early warning rating result is primary early warning; When the vehicle motion characteristic index is greater than or equal to the second vehicle threshold, the early warning rating result is advanced early warning; When the motor stability is less than the first motor threshold, the early warning rating result is no early warning; When the motor stability is greater than or equal to the first motor threshold and less than the second motor threshold, the early warning rating result is primary early warning; When the motor stability is greater than or equal to the second motor threshold, the early warning rating result is advanced early warning; When the excessive discharge frequency is less than the discharge frequency threshold, the early warning rating result is no early warning; When the excessive discharge frequency is greater than or equal to the discharge frequency threshold, the early warning rating result is advanced early warning; When the hydrogen concentration rising rate is less than the concentration rising rate threshold, the early warning rating result is no early warning; When the hydrogen concentration rising rate is greater than or equal to the concentration rising rate threshold, the early warning rating result is advanced early warning; When the battery temperature index is less than the battery temperature threshold, the early warning rating result is no early warning; When the battery temperature index is greater than or equal to the battery temperature threshold, the early warning rating result is advanced early warning; When the fourth data set is an empty set, the early warning rating result is no early warning; When the fourth data set is a non-empty set, the early warning rating result is advanced early warning.

8. The body contact type safety warning system based on vehicle state according to claim 1, characterized in that: The execution reminder unit is used to receive the early warning rating result data sent by the judgment unit and perform hierarchical early warning reminders for the driver according to the early warning rating result.

9. The body contact type safety warning system based on vehicle state according to claim 8, characterized in that: The logic of the hierarchical early warning reminder includes: When the early warning rating result is no early warning, the execution reminder unit remains in the standby state; When the early warning rating result is a primary early warning, the reminder unit is activated, the driver's seat belt is tightened at intervals with a preset first force, and the vibration belt on the seat belt of the target vehicle or on the headrest part of the driver's seat vibrates intermittently with a preset conventional vibration intensity and a preset conventional vibration frequency. After the vibration belt vibrates continuously for seconds, it stops seconds is recorded as one time, and after repeating the cycle K times and then stopping, the reminder unit enters the standby state; When the early warning rating result is advanced early warning, the execution reminder unit is activated, causing the vibration belt on the safety belt of the target vehicle to vibrate continuously at the preset maximum vibration intensity and preset maximum vibration frequency, and at the same time causing the driver's seat of the target vehicle to vibrate continuously at the preset seat vibration intensity and preset seat vibration frequency. The full-seat safety belt remains tightened with the preset second force until the driver manually turns off the early warning and then stops. The execution reminder unit enters the standby state.

10. The body contact type safety warning system based on vehicle status according to claim 1, wherein: The interaction unit is used to provide an operation interface for the user, receive user operation instructions, and provide visual feedback. The user operation instructions include a system on / off instruction, a vibration off instruction, a system parameter preset instruction, and a historical record data query instruction; The system parameters in the system parameter preset instruction include vehicle mass, wheel circumference, lateral moment of inertia, electromagnetic mutual inductance coefficient, total number of motor magnetic poles, rated current threshold value, and preset time window duration; The storage unit is used to store the output data of the data acquisition module, the output data of the data processing module, the output data of the vibration prompt module, user operation instruction data, and historical record data.

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