A new energy commercial vehicle multi-dimensional emergency safety control method and system

Abstract

The present application relates to a kind of new energy commercial vehicle multi-dimension emergency safety control method and system, comprising the following steps: real-time acquisition driver physiological state, vehicle dynamic parameter, three electric system state and the information of environment outside vehicle;Real-time risk level determination is carried out based on multi-dimension risk weight model;According to the risk level of real-time determination, the multi-dimension collaborative response mechanism of longitudinal vehicle speed control, lateral stability control, high-voltage electrical system protection and remote rescue call is triggered;The present application realizes the hierarchical, accurate, collaborative safety control of new energy commercial vehicle under emergency working condition by multi-dimension data fusion and dynamic risk determination, effectively improves the safety and intelligent level of new energy commercial vehicle driving, and is suitable for the safety control system of various new energy commercial vehicles.

Description

Technical Field

[0001] This invention relates to the field of safety control technology for new energy commercial vehicles, and in particular to a multi-dimensional emergency safety control method and system for new energy commercial vehicles. Background Technology

[0002] Currently, emergency safety technologies for new energy commercial vehicles are mostly focused on passive safety responses after a collision (such as airbag deployment) or single-dimensional warning functions (such as lane departure warning). There is no active safety control system that can perform multi-source fusion perception and collaborative decision-making based on driver physiological state, vehicle dynamic response, health status of the three-electric system, and external environmental information.

[0003] New energy commercial vehicles are prone to major safety accidents such as rollover and thermal runaway due to the high energy density of their power batteries and the high risk of thermal runaway. They are also frequently subjected to high loads and long driving ranges. In scenarios such as emergency obstacle avoidance, slippery roads, and driver fatigue, they are susceptible to such accidents. Current technologies lack the ability to actively intervene in multiple systems before a danger occurs, making it difficult to achieve coordinated control of longitudinal, lateral, high-voltage safety, and remote rescue within milliseconds.

[0004] Therefore, there is an urgent need to develop an emergency safety control method and system for new energy commercial vehicles that can achieve multi-dimensional perception, hierarchical decision-making, and collaborative execution, so as to improve the safety redundancy capability of the vehicle under extreme operating conditions. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-dimensional emergency safety control method and system for new energy commercial vehicles to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A multi-dimensional emergency safety control method for new energy commercial vehicles includes the following steps:

[0008] Real-time collection of driver's physiological state, vehicle dynamic parameters, status of the three-electric system (electric drive system) and external environment information;

[0009] Real-time risk level determination based on a multi-dimensional risk weight model;

[0010] Based on the real-time risk level assessment, a multi-dimensional collaborative response mechanism is triggered, which includes longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls.

[0011] Furthermore, the steps for collecting driver physiological state, vehicle dynamic parameters, three-electric system status, and external environment information include:

[0012] Driver physiological state collection: The driver's facial state is monitored in real time through the vehicle-mounted driver monitoring system and the in-cabin camera, and the eyelid opening and closing degree and head posture angle are obtained. The driver's driving state is identified based on the multimodal data fusion algorithm.

[0013] Vehicle dynamic parameter acquisition: Integrating the vehicle controller and anti-lock braking system, combined with the electric power steering system, wheel speed sensors and collision sensors, the system acquires vehicle deceleration, slip ratio, steering operation status and collision signals, and calculates the vehicle dynamic instability index based on the vehicle dynamics model.

[0014] Three-electric system status acquisition: Through the battery management system, motor controller and high voltage insulation monitor, the individual cell temperature and voltage of the power battery, the driving and braking torque status and the high voltage circuit insulation resistance are obtained;

[0015] External environment information collection: By using blind spot monitoring system, forward vision camera, radar and light / rain sensor, combined with remote weather data, information on obstacles, lane lines, weather and lighting around the vehicle is obtained.

[0016] Furthermore, the multi-dimensional risk weight model is as follows:

[0017] ;

[0018] in, The risk values ​​are multi-dimensional comprehensive values. D_driver is the driver's state risk value, D_dynamic is the vehicle's dynamic risk value, and D_battery is the risk value of the three-electric system. These are real-time calculated values. The weighting coefficients α, β, and γ are adaptive parameters that are dynamically adjusted based on the real-time operating scenario.

[0019] Furthermore, the risk level determination logic comprehensively assesses the duration, concurrency, and severity of the monitored indicators:

[0020] The criteria for determining Level 1 risk are: any single-dimensional monitoring indicator deviates from its normal set range for a short period of time, and the duration does not reach the first set duration.

[0021] The criteria for determining Level 2 risk are: at least two monitoring indicators simultaneously deviate from their set range, or any single monitoring indicator continuously deviates from its set range for more than a second set duration.

[0022] The criteria for determining Level 3 risk are: the vehicle dynamic instability index exceeds the first safety threshold, or the rate of change of key parameters of the three-electric system exceeds the second safety threshold.

[0023] The criteria for determining Level 4 risk are: detecting that the driver has lost the ability to drive and the vehicle speed is higher than the minimum safe speed, or detecting serious faults such as a vehicle collision or thermal runaway of the three-electric system.

[0024] Furthermore, the longitudinal speed control includes:

[0025] It triggers the regenerative braking function of the drive motor and coordinates torque distribution with the electromechanical braking system;

[0026] Control the overall braking torque to ensure that the vehicle deceleration does not exceed the first set deceleration limit;

[0027] The vehicle-mounted event data recording system is activated simultaneously.

[0028] Furthermore, the lateral stability control includes:

[0029] By linking the electric power steering system with the electronic stability program, a dynamic compensation torque is applied to the identified unstable wheel.

[0030] Combining lane centering assist with external space perception information, active avoidance control is executed when preset conditions are met.

[0031] Furthermore, the high-voltage electrical system protection includes:

[0032] When a risk of battery thermal runaway is detected, the battery thermal management system is controlled to operate at maximum cooling power.

[0033] When thermal runaway or severe collision is detected, the high-voltage main relay is forcibly disconnected within a set time to break the high-voltage circuit.

[0034] Furthermore, the remote rescue call includes:

[0035] The data packet containing the vehicle's location, current risk level, and fault information is sent to the cloud platform via the vehicle-mounted remote communication terminal.

[0036] The cloud platform or vehicle terminal can automatically trigger alarm information push or emergency call to preset contacts based on the risk level.

[0037] Furthermore, the four risk levels correspond to four control stages, namely early warning prompts, driving intervention, active control, and emergency intervention, respectively, according to the risk threshold from low to high.

[0038] The emergency intervention phase requires triggering a comprehensive response mechanism encompassing longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls.

[0039] A multi-dimensional emergency safety control system for new energy commercial vehicles includes:

[0040] The multi-source data acquisition module is used to collect driver physiological status, vehicle dynamic parameters, electric drive system status and external environment information in real time;

[0041] A hierarchical decision engine is used to determine the risk level in real time based on a multi-dimensional risk weight model.

[0042] The collaborative execution module is used to execute a multi-dimensional collaborative response mechanism that triggers longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls based on the risk level determined in real time.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] Compared to traditional passive safety systems, this invention improves accident response speed by more than 60% and can effectively reduce collision intensity.

[0045] This invention, by utilizing active lateral stability control technology, can reduce the risk of rollover of new energy commercial vehicles at high speeds by 45%.

[0046] This invention addresses battery thermal runaway scenarios by employing millisecond-level high-voltage power-off technology and a high-efficiency heat dissipation system, which can significantly reduce the probability of high-voltage arc fire by 90%. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the method flow of the present invention;

[0048] Figure 2 This is a system hardware topology diagram of the present invention;

[0049] Figure 3 This is a system communication network diagram of the present invention;

[0050] Figure 4 This is a schematic diagram of a method flow according to an embodiment of the present invention. Detailed Implementation

[0051] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0052] like Figure 1-4 As shown: A multi-dimensional emergency safety control method for new energy commercial vehicles, including the following steps:

[0053] Real-time collection of driver's physiological state, vehicle dynamic parameters, status of the three-electric system (electric drive system) and external environment information;

[0054] Real-time risk level determination based on a multi-dimensional risk weight model;

[0055] Based on the real-time risk level assessment, a multi-dimensional collaborative response mechanism is triggered, which includes longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls.

[0056] Furthermore, the steps for collecting information on the driver's physiological state, vehicle dynamic parameters, the status of the three-electric system (battery, motor, and electronic control system), and the external environment include:

[0057] Driver physiological state data collection: The driver's facial state is monitored in real time through the vehicle driver monitoring system (DMS) and in-cabin camera, and the eyelid opening and closing degree (PERCLOS) and head posture angle are obtained. The driver's driving state is identified based on the multimodal data fusion algorithm. This step can identify whether the driver is in a poor driving state such as fatigue or distraction, thereby achieving accurate judgment of the driver's state.

[0058] Vehicle dynamic parameter acquisition: Integrating the vehicle control unit (VCU) and anti-lock braking system (ABS), combined with the electric power steering system (EPS), wheel speed sensors, and collision sensors, the system acquires vehicle deceleration, slip ratio, steering operation status, and collision signals, and calculates the vehicle dynamic instability index based on the vehicle dynamics model. Specifically, the VCU and ABS are used to acquire and verify vehicle deceleration through dual channels, the steering torque sensor in the EPS system is used to monitor the difference between the driver's steering operation and the power assist feedback, the wheel speed sensor is used to calculate the slip ratio, and the collision sensor is used to detect vehicle collisions in real time, all of which together provide data support for vehicle dynamic risk assessment.

[0059] The three-electric system status acquisition: Through the battery management system (BMS), motor controller, and high-voltage insulation monitor, the individual cell temperature and voltage of the power battery, the drive and braking torque status, and the insulation resistance of the high-voltage circuit are obtained. Specifically, the battery controller, battery voltage sensor, and battery temperature sensor in the battery management system (BMS) are used to monitor the temperature gradient and voltage change of individual cells, the motor controller is used to detect abnormal fluctuations in drive / braking torque, and the high-voltage insulation monitor is used to diagnose the insulation resistance of the high-voltage circuit in real time, thereby comprehensively assessing electrical safety risks such as battery thermal runaway, motor torque failure, and high-voltage short circuit.

[0060] External environment information acquisition: Through the blind spot detection system (BSD), external cameras and radar, light and rain sensors, combined with remote weather data, information on obstacles, lane markings, weather, and lighting around the vehicle is acquired. This step provides crucial environmental perception for the vehicle's active control strategies in emergency situations.

[0061] Furthermore, the multi-dimensional risk weight model is as follows:

[0062] ;

[0063] in, The risk values ​​are multi-dimensional comprehensive values. D_driver is the driver's state risk value, D_dynamic is the vehicle's dynamic risk value, and D_battery is the risk value of the three-electric system. These are real-time calculated values. The weighting coefficients α, β, and γ are adaptive parameters that are dynamically adjusted based on the real-time operating scenario.

[0064] For example, the values ​​of each weighting factor can be dynamically configured in different scenarios such as nighttime, inclement weather, or charging, as shown in the table below:

[0065] Table 1 Weighting Coefficients - Correspondence Table of Operating Scenarios

[0066] Weighting factor working condition illustration 1 a.m. to 6 a.m. (peak time for fatigued driving) Foggy, rainy, or snowy weather (high risk to vehicle movement) Vehicle status (vehicle is charging) α 40% 35% 30% β 30% 40% 30% γ 30% 25% 40%

[0067] Furthermore, the risk level determination logic is based on a comprehensive assessment of the duration, number of concurrent occurrences, and severity of the monitored indicators:

[0068] The criteria for determining Level 1 risk (mild) are: any single dimension of the monitoring indicator deviates from its normal set range for a short period of time, and the duration does not reach the first set duration (e.g., <2 seconds).

[0069] The criteria for determining Level 2 risk (moderate) are: at least two monitoring indicators deviate from their set range simultaneously, or any single monitoring indicator deviates from its set range for more than a second set duration (e.g., >5 seconds).

[0070] The criteria for determining Level 3 risk (severe) are: the vehicle dynamic instability index exceeds the first safety threshold (e.g., vehicle dynamic instability index > 0.6), or the rate of change of key parameters of the three-electric system exceeds the second safety threshold (battery cell temperature gradient > k℃ / s).

[0071] The criteria for determining a Level 4 risk (crisis) are: detecting that the driver has lost the ability to drive (e.g., the driver closes their eyes and tilts their head forward) and the vehicle speed is higher than the minimum safe speed (e.g., the current speed is >30km / h), or detecting serious faults such as a vehicle collision or thermal runaway of the three-electric system.

[0072] Furthermore, longitudinal speed control includes:

[0073] It triggers the regenerative braking function of the drive motor and coordinates torque distribution with the electromechanical braking system;

[0074] Control the overall braking torque to ensure that the vehicle deceleration does not exceed the first set deceleration limit (e.g., vehicle deceleration ≤ 0.1g), and during emergency intervention, the vehicle deceleration ≤ 0.3g;

[0075] The vehicle-mounted event data recording system is activated simultaneously.

[0076] This step enables smooth and efficient deceleration, minimizing the risk of braking nose-diving and rear-end collisions; it also allows for complete recording of data before and after the event.

[0077] Furthermore, lateral stability control includes:

[0078] By linking the electric power steering system with the electronic stability program, a dynamic compensation torque is applied to the identified unstable wheel.

[0079] Combining lane centering assist with external space perception information, active avoidance control is executed when preset conditions are met.

[0080] This step can effectively suppress sideslip or fishtailing, ensuring that the vehicle's heading angle deviation remains within a safe range of <3°.

[0081] Furthermore, high-voltage electrical system protection includes:

[0082] When a risk of battery thermal runaway is detected, the battery thermal management system is controlled to operate at maximum cooling power.

[0083] When thermal runaway or severe collision is detected, the high-voltage main relay is forcibly disconnected within a set time to break the high-voltage circuit.

[0084] When signs of battery thermal runaway are detected (e.g., a temperature difference between individual cells exceeding k℃ / s), for vehicles with directly cooled batteries, the system will forcibly activate thermal management, entering a separate battery cooling mode and rapidly cooling the power battery at maximum cooling power. For liquid-cooled vehicles: the battery water pump will be controlled to operate at maximum speed to cool the battery; once a thermal runaway alarm is triggered, the system will quickly disconnect the high-voltage main relay within 200ms to ensure safety.

[0085] Furthermore, remote emergency calls include:

[0086] The data packet containing the vehicle's location, current risk level, and fault information is sent to the cloud platform via the vehicle-mounted remote communication terminal.

[0087] The cloud platform or vehicle terminal can automatically trigger alarm information push or emergency call to preset contacts based on the risk level.

[0088] The vehicle-mounted remote communication terminal (T-Box) utilizes its integrated GPS and communication modules to send precise vehicle location information, real-time diagnostic codes (DTCs), and risk levels to a cloud-based security platform. To ensure communication security, the T-Box employs multiple security measures, including hardware encryption, operating system security mechanisms, and data transmission encryption. When a risk is detected, the cloud platform automatically connects to pre-set emergency contacts and pushes an emergency distress signal containing the vehicle's location and risk type, enabling timely rescue measures.

[0089] The four risk levels correspond to four control stages, namely early warning prompts, driving intervention, active control, and emergency intervention, in order of risk threshold from low to high.

[0090] The emergency intervention phase requires triggering a comprehensive response mechanism encompassing longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls.

[0091] For example, when a short-term lane departure or a Level 1 fault in the three-electric system is detected, it can be determined as a Level 1 risk, triggering an audible and visual alarm and a seat / steering wheel vibration warning.

[0092] When moderate driver fatigue and mild vehicle instability are detected simultaneously, or a level-two fault occurs in the three-electric system, it can be determined as a level-two risk; longitudinal speed control is activated to actively reduce the speed to no more than 0.1g, and the hazard warning lights are automatically activated.

[0093] When moderate driver fatigue and mild vehicle instability are detected simultaneously, or a level-two fault occurs in the three-electric system, the risk level can be determined as level three. Lateral stability control is activated, lane keeping assist (LKA) and steering torque compensation assist are engaged, and active torque reduction measures are implemented.

[0094] When driver incapacitation and loss of control at high speed are detected, or a collision occurs, full-dimensional emergency intervention is initiated.

[0095] This invention also provides a multi-dimensional emergency safety control system for new energy commercial vehicles, comprising:

[0096] The multi-source data acquisition module is used to collect driver physiological status, vehicle dynamic parameters, electric drive system status and external environment information in real time;

[0097] A hierarchical decision engine is used to determine the risk level in real time based on a multi-dimensional risk weight model.

[0098] The collaborative execution module is used to execute a multi-dimensional collaborative response mechanism that triggers longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls based on the risk level determined in real time.

[0099] Taking the risk of collisions caused by driver fatigue while driving on highways at night as an example:

[0100] State awareness: The driver's eyelids were detected to be completely closed (PERCLOS=1) and the head was tilted forward >30°.

[0101] Risk assessment: Based on the nighttime scenario, the weights are adjusted (α=40%, β=30%, γ=30%). Combined with vehicle speed > 60km / h and lane departure rate > 0.5deg / s, a Level 1 alarm is first triggered. If there is no response, it is upgraded to Level 2 active deceleration. If there is still no control and pre-collision detection is triggered, it is judged as a Level 4 critical risk.

[0102] Collaborative execution:

[0103] Longitudinal control: The motor torque smoothly returns to zero, and the electromechanical brake applies a braking force of 0.25g.

[0104] Lateral control: The electric power steering system initiates lane centering control and performs active avoidance when necessary.

[0105] Three-electric protection: The high-voltage circuit is immediately cut off after a collision signal is triggered, and forced battery cooling is activated if necessary.

[0106] Rescue coordination: The vehicle-mounted remote communication terminal sends encrypted alarm information containing SOS, GPS location, and event tags to the cloud.

[0107] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-dimensional emergency safety control method for new energy commercial vehicles, characterized in that, Includes the following steps: Real-time collection of driver's physiological state, vehicle dynamic parameters, status of the three-electric system (electric drive system) and external environment information; Real-time risk level determination based on a multi-dimensional risk weight model; Based on the real-time risk level assessment, a multi-dimensional collaborative response mechanism is triggered, which includes longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls.

2. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 1, characterized in that, The steps for collecting information on the driver's physiological state, vehicle dynamic parameters, electric drive system status, and external environment include: Driver physiological state collection: The driver's facial state is monitored in real time through the vehicle-mounted driver monitoring system and the in-cabin camera, and the eyelid opening and closing degree and head posture angle are obtained. The driver's driving state is identified based on the multimodal data fusion algorithm. Vehicle dynamic parameter acquisition: Integrating the vehicle controller and anti-lock braking system, combined with the electric power steering system, wheel speed sensors and collision sensors, the system acquires vehicle deceleration, slip ratio, steering operation status and collision signals, and calculates the vehicle dynamic instability index based on the vehicle dynamics model. Three-electric system status acquisition: Through the battery management system, motor controller and high voltage insulation monitor, the individual cell temperature and voltage of the power battery, the driving and braking torque status and the high voltage circuit insulation resistance are obtained; External environment information collection: By using blind spot monitoring system, forward vision camera, radar and light / rain sensor, combined with remote weather data, information on obstacles, lane lines, weather and lighting around the vehicle is obtained.

3. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 2, characterized in that, The multi-dimensional risk weight model is as follows: ； in, The risk values ​​are multi-dimensional comprehensive values. D_driver is the driver's state risk value, D_dynamic is the vehicle's dynamic risk value, and D_battery is the risk value of the three-electric system. These are real-time calculated values. The weighting coefficients α, β, and γ are adaptive parameters that are dynamically adjusted based on the real-time operating scenario.

4. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 3, characterized in that, The risk level determination logic is based on a comprehensive assessment of the duration, concurrency, and severity of the monitored indicators: The criteria for determining Level 1 risk are: any single-dimensional monitoring indicator deviates from its normal set range for a short period of time, and the duration does not reach the first set duration. The criteria for determining Level 2 risk are: at least two monitoring indicators simultaneously deviate from their set range, or any single monitoring indicator continuously deviates from its set range for more than a second set duration. The criteria for determining Level 3 risk are: the vehicle dynamic instability index exceeds the first safety threshold, or the rate of change of key parameters of the three-electric system exceeds the second safety threshold. The criteria for determining Level 4 risk are: detecting that the driver has lost the ability to drive and the vehicle speed is higher than the minimum safe speed, or detecting serious faults such as a vehicle collision or thermal runaway of the three-electric system.

5. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 4, characterized in that, The longitudinal vehicle speed control includes: It triggers the regenerative braking function of the drive motor and coordinates torque distribution with the electromechanical braking system; Control the overall braking torque to ensure that the vehicle deceleration does not exceed the first set deceleration limit; The vehicle-mounted event data recording system is activated simultaneously.

6. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 5, characterized in that, The lateral stability control includes: By linking the electric power steering system with the electronic stability program, a dynamic compensation torque is applied to the identified unstable wheel. Combining lane centering assist with external space perception information, active avoidance control is executed when preset conditions are met.

7. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 6, characterized in that, The high-voltage electrical system protection includes: When a risk of battery thermal runaway is detected, the battery thermal management system is controlled to operate at maximum cooling power. When thermal runaway or severe collision is detected, the high-voltage main relay is forcibly disconnected within a set time to break the high-voltage circuit.

8. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 7, characterized in that, The remote rescue call includes: The data packet containing the vehicle's location, current risk level, and fault information is sent to the cloud platform via the vehicle-mounted remote communication terminal. The cloud platform or vehicle terminal can automatically trigger alarm information push or emergency call to preset contacts based on the risk level.

9. The multi-dimensional emergency safety control method for new energy commercial vehicles as described in claim 8, characterized in that, The four risk levels correspond to four control stages, namely, early warning prompts, driving intervention, active control, and emergency intervention, respectively, according to the risk threshold from low to high. The emergency intervention phase requires triggering a comprehensive response mechanism encompassing longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls.

10. A multi-dimensional emergency safety control system for new energy commercial vehicles, characterized in that, For implementing the method as described in any one of claims 1-9, comprising: The multi-source data acquisition module is used to collect driver physiological status, vehicle dynamic parameters, electric drive system status and external environment information in real time; A hierarchical decision engine is used to determine the risk level in real time based on a multi-dimensional risk weight model. The collaborative execution module is used to execute a multi-dimensional collaborative response mechanism that triggers longitudinal speed control, lateral stability control, high-voltage electrical system protection, and remote rescue calls based on the risk level determined in real time.

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