Vehicle control method and device

Abstract

The invention discloses a vehicle control method and device, and belongs to the field of new energy vehicles. According to the vehicle control scheme provided by the invention, the safety and reliability of vehicle operation are improved. Specifically, according to the scheme, key electrical parameters are acquired through a sensor mounted on the high-voltage system, and the parameters can reflect the insulating property of the high-voltage system and are important basis for evaluating the insulating property of the high-voltage system, so that the insulating property of the high-voltage system can be evaluated by processing and analyzing the parameters; effective and accurate evaluation of the insulation state of the high-voltage system is realized. Besides, when the high-voltage system is judged to have the problem of poor insulation performance, the scheme can perform fault processing in time and prompt the insulation risk faced by the vehicle, so that a powerful guarantee is provided for safe operation of the new energy vehicle, and the probability of occurrence of safety accidents such as personnel electric shock and vehicle damage is greatly reduced.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicles, and in particular to a vehicle control method and device. Background Art

[0002] The insulation performance of new energy vehicles is one of the important indicators to ensure the safe operation of vehicles. Among them, the automotive high-voltage system, as a key part of new energy vehicles, generally includes high-voltage battery packs, high-voltage motors, high-voltage cables, high-voltage connectors, and on-board chargers. Since the voltage of the high-voltage system is very high, once the insulation fails, safety accidents such as electric shock and vehicle damage may occur.

[0003] Therefore, in order to improve the safety and reliability of vehicle operation, how to control the vehicle to effectively evaluate the insulation performance of the automobile high-voltage system and promptly alert the insulation risks faced by the vehicle has become a focus of attention for technical personnel in this field. Summary of the invention

[0004] The embodiment of the present application provides a vehicle control method and device. The technical solution is as follows:

[0005] In one aspect, a vehicle control method is provided, the method comprising:

[0006] Acquiring key electrical parameters through sensors installed on a first electrical system of the vehicle; wherein the first electrical system refers to an electrical system whose operating voltage exceeds a safety voltage for human bodies; and the key electrical parameters are used to reflect the insulation performance of the first electrical system;

[0007] Determining an insulation state of the first electrical system based on the acquired key electrical parameters;

[0008] If the determined insulation state indicates that the first electrical system has an insulation risk, determining a risk level corresponding to the insulation risk;

[0009] According to the determined risk level, at least one of performing fault processing on the vehicle or outputting prompt information;

[0010] The prompt information includes at least one of insulation performance details, potential impact on the vehicle, or safety measures that can be taken.

[0011] In some embodiments, obtaining the key electrical parameters by means of a sensor installed on the first electrical system of the vehicle includes:

[0012] The voltage value is obtained by installing voltage sensors at different nodes of the vehicle's high-voltage circuit;

[0013] The current value is obtained by installing a current sensor on the path through which the current flows;

[0014] acquiring a temperature value through a temperature sensor installed at a first component of the first electrical system;

[0015] A humidity value is obtained by a humidity sensor installed at the second component of the first electrical system.

[0016] In some other embodiments, obtaining the key electrical parameters by means of a sensor installed on the first electrical system of the vehicle includes:

[0017] Determining a parameter acquisition frequency according to the type of the vehicle and the driving condition during the current driving process;

[0018] The key electrical parameters are obtained by obtaining a frequency according to the determined parameters through a sensor installed on the first electrical system.

[0019] In some other embodiments, determining the insulation state of the first electrical system based on the acquired key electrical parameters includes:

[0020] Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters;

[0021] Calling the constructed circuit mathematical model, and determining the value of the insulation performance index of the first electrical system based on the preprocessed key electrical parameters;

[0022] The insulation state of the first electrical system is determined according to the value of the insulation performance indicator and a preset safety threshold.

[0023] In some other embodiments, determining the risk level corresponding to the insulation risk includes:

[0024] The risk level corresponding to the insulation risk is determined according to the degree to which the insulation performance indicator deviates from the safety threshold, the speed of insulation performance change, and the insulation performance change trend.

[0025] In some other embodiments, determining the insulation state of the first electrical system based on the acquired key electrical parameters includes:

[0026] Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters;

[0027] Extracting features of the preprocessed key electrical parameters, inputting the extracted features into a constructed insulation state determination model, calling the insulation state determination model, and determining the insulation state of the first electrical system;

[0028] Wherein, the insulation state determination model is a machine learning model obtained through training based on training samples.

[0029] In some other embodiments, the training process of the insulation state determination model includes:

[0030] Acquire the training samples; wherein the training samples include key electrical parameters of samples under different insulation states;

[0031] Preprocessing the key electrical parameters of the samples included in the training samples to obtain preprocessed training samples;

[0032] Extracting features from the preprocessed training samples, inputting the extracted features into an initial machine learning model, calling the machine learning model, and predicting the insulation state corresponding to the processed training samples;

[0033] Determining the difference between the actual insulation state and the predicted insulation state corresponding to the training sample by means of the constructed loss function;

[0034] The network parameters of the machine learning model are optimized based on the determined differences until a training stop condition is met, thereby obtaining the insulation state determination model.

[0035] In some other embodiments, the output of the insulation state determination model includes an insulation failure probability; and determining a risk level corresponding to the insulation risk includes:

[0036] A risk level corresponding to the insulation risk is determined according to the insulation failure probability.

[0037] In some other embodiments, the performing fault processing on the vehicle includes at least one of the following:

[0038] Controlling at least one device of the vehicle to stop working;

[0039] Setting some functions of the vehicle to a restricted use state;

[0040] Cut off the vehicle's high-voltage circuit;

[0041] Call the target number;

[0042] Sending an alarm message to the target number; wherein the alarm message includes the vehicle location and fault type;

[0043] Controlling the exterior lighting assembly of the vehicle to flash;

[0044] Controlling the loudspeaker of the vehicle to sound continuously;

[0045] The faulty device with insulation failure is controlled to stop working, and the backup device of the faulty device is started.

[0046] In another aspect, a vehicle control device is provided, the device comprising:

[0047] an acquisition module, configured to acquire key electrical parameters through a sensor installed on a first electrical system of the vehicle; wherein the first electrical system refers to an electrical system whose operating voltage exceeds a human safety voltage; and the key electrical parameters are used to reflect the insulation performance of the first electrical system;

[0048] A first determination module is configured to determine an insulation state of the first electrical system based on the acquired key electrical parameters;

[0049] A second determination module is configured to determine a risk level corresponding to the insulation risk if the determined insulation state indicates that the first electrical system has an insulation risk;

[0050] a control module configured to perform at least one of performing fault processing on the vehicle or outputting prompt information according to the determined risk level;

[0051] The prompt information includes at least one of insulation performance details, potential impact on the vehicle, or safety measures that can be taken.

[0052] In some embodiments, the acquisition module is configured to:

[0053] The voltage value is obtained by installing voltage sensors at different nodes of the vehicle's high-voltage circuit;

[0054] The current value is obtained by installing a current sensor on the path through which the current flows;

[0055] acquiring a temperature value through a temperature sensor installed at a first component of the first electrical system;

[0056] A humidity value is obtained by a humidity sensor installed at the second component of the first electrical system.

[0057] In some other embodiments, the acquisition module is configured to:

[0058] Determining a parameter acquisition frequency according to the type of the vehicle and the driving condition during the current driving process;

[0059] The key electrical parameters are obtained by obtaining a frequency according to the determined parameters through a sensor installed on the first electrical system.

[0060] In some other embodiments, the first determining module is configured to:

[0061] Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters;

[0062] Calling the constructed circuit mathematical model, and determining the value of the insulation performance index of the first electrical system based on the preprocessed key electrical parameters;

[0063] The insulation state of the first electrical system is determined according to the value of the insulation performance indicator and a preset safety threshold.

[0064] In other embodiments, the second determination module is configured to determine the risk level corresponding to the insulation risk according to the degree to which the insulation performance indicator deviates from the safety threshold, the speed of insulation performance change, and the insulation performance change trend.

[0065] In some other embodiments, the first determining module is configured to:

[0066] Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters;

[0067] Extracting features of the preprocessed key electrical parameters, inputting the extracted features into a constructed insulation state determination model, calling the insulation state determination model, and determining the insulation state of the first electrical system;

[0068] Wherein, the insulation state determination model is a machine learning model obtained through training based on training samples.

[0069] In some other embodiments, the training process of the insulation state determination model includes:

[0070] Acquire the training samples; wherein the training samples include key electrical parameters of samples under different insulation states;

[0071] Preprocessing the key electrical parameters of the samples included in the training samples to obtain preprocessed training samples;

[0072] Extracting features from the preprocessed training samples, inputting the extracted features into an initial machine learning model, calling the machine learning model, and predicting the insulation state corresponding to the processed training samples;

[0073] Determining the difference between the actual insulation state and the predicted insulation state corresponding to the training sample by means of the constructed loss function;

[0074] The network parameters of the machine learning model are optimized based on the determined differences until a training stop condition is met, thereby obtaining the insulation state determination model.

[0075] In other embodiments, the output of the insulation state determination model includes an insulation fault probability;

[0076] The second determination module is configured to determine a risk level corresponding to the insulation risk according to the insulation failure probability.

[0077] In some other embodiments, the control module is configured to perform at least one of the following:

[0078] Controlling at least one device of the vehicle to stop working;

[0079] Setting some functions of the vehicle to a restricted use state;

[0080] Cut off the vehicle's high-voltage circuit;

[0081] Call the target number;

[0082] Sending an alarm message to the target number; wherein the alarm message includes the vehicle location and fault type;

[0083] Controlling the exterior lighting assembly of the vehicle to flash;

[0084] Controlling the loudspeaker of the vehicle to sound continuously;

[0085] The faulty device with insulation failure is controlled to stop working, and the backup device of the faulty device is started.

[0086] On the other hand, a vehicle controller is provided, the device comprising a processor and a memory, the memory storing at least one program code, the at least one program code being loaded and executed by the processor to implement the above-mentioned vehicle control method.

[0087] On the other hand, a computer-readable storage medium is provided, in which at least one program code is stored. The at least one program code is loaded and executed by a processor to implement the above-mentioned vehicle control method.

[0088] On the other hand, a computer program product or a computer program is provided, which includes a computer program code, and the computer program code is stored in a computer-readable storage medium. The processor of the vehicle controller reads the computer program code from the computer-readable storage medium, and the processor executes the computer program code, so that the vehicle controller executes the above-mentioned vehicle control method.

[0089] The vehicle control scheme provided in the embodiment of the present application improves the safety and reliability of vehicle operation. In detail, the scheme collects key electrical parameters through sensors installed on the high-voltage system. Since these parameters can reflect the insulation performance of the high-voltage system and are an important basis for evaluating the insulation performance of the high-voltage system, the insulation state of the high-voltage system can be effectively and accurately evaluated by processing and analyzing these parameters. In addition, when it is determined that the high-voltage system has a problem of poor insulation performance, the scheme can also handle the fault in a timely manner and prompt the insulation risks faced by the vehicle, which provides a strong guarantee for the safe operation of new energy vehicles and greatly reduces the probability of safety accidents such as electric shock to personnel and vehicle damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0091] Figure 1 is a schematic diagram of an implementation environment involved in a vehicle control method provided in an embodiment of the present application;

[0092] Figure 2 is a flow chart of a vehicle control method provided by an embodiment of the present application;

[0093] Figure 3 is a structural schematic diagram of a vehicle control device provided in an embodiment of the present application;

[0094] Figure 4 It is a structural schematic diagram of a vehicle controller provided in an embodiment of the present application. DETAILED DESCRIPTION

[0095] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0096] In this application, the terms "first", "second", etc. are used to distinguish the same or similar items with substantially the same role and function. It should be understood that there is no logical or temporal dependency between "first", "second", and "nth", nor is there a limitation on the quantity and execution order. It should also be understood that although the following description uses the terms first, second, etc. to describe various elements, these elements should not be limited by the terms.

[0097] These terms are only used to distinguish one element from another element. For example, without departing from the scope of various examples, a first element can be referred to as a second element, and similarly, a second element can also be referred to as a first element. Both the first element and the second element can be elements, and in some cases, can be separate and different elements.

[0098] Here, at least one means one or more than one, for example, at least one element can be one element, two elements, three elements, or any other integer greater than or equal to one. And multiple means two or more than two, for example, multiple elements can be two elements, three elements, or any other integer greater than or equal to two.

[0099] The "and / or" mentioned in this article indicates that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship.

[0100] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards in the relevant regions.

[0101] Figure 1 It is a schematic diagram of an implementation environment involved in a vehicle control method provided in an embodiment of the present application.

[0102] For example, see Figure 1 The implementation environment includes: a power battery management system 1 (BMS, Battery Management System) and a vehicle controller (VCU, Vehicle Control Unit) 2.

[0103] Among them, BMS1 includes an insulation detection unit 11, which is responsible for monitoring the insulation performance of the vehicle's high-voltage system to determine whether the vehicle's high-voltage system currently has the possibility of endangering personal and vehicle safety. As the core control unit of the vehicle, VCU2 does not directly monitor the insulation performance, but it will receive the insulation fault signal from BM1 and make a comprehensive judgment and process the insulation fault based on the vehicle's operating status and other relevant information. For example, before the vehicle starts, VCU2 will wait for BMS1 to complete the insulation test and confirm that it is correct before allowing the vehicle to enter the ready state. In addition, after receiving the insulation fault signal, VCU2 will adopt corresponding fault handling strategies according to the severity of the fault to ensure the safety of the vehicle and personnel.

[0104] The following is a brief introduction to the vehicle control solution provided in the embodiment of the present application from several aspects, including insulation detection, real-time monitoring and risk assessment, risk warning and fault handling.

[0105] 1. Insulation detection mechanism

[0106] Data acquisition: The sensors installed on the high-voltage system collect key electrical parameters of the high-voltage circuit, such as voltage and current. These parameters are an important basis for evaluating the insulation performance of the high-voltage system.

[0107] Data processing: By processing and analyzing the collected sensor data, the insulation resistance value or other related insulation performance indicators of the high-voltage system can be determined.

[0108] For example, when performing data processing and analysis, circuit mathematical models, machine learning algorithms, or signal processing techniques may be used to ensure the accuracy and reliability of the calculations, which is not limited in this application.

[0109] 2. Real-time monitoring and risk assessment

[0110] Real-time monitoring: This solution can continuously monitor the insulation status of the high-voltage system while the vehicle is driving, which helps to promptly detect changes in insulation performance.

[0111] Risk assessment: This solution can conduct a risk assessment on the current insulation status of the high-voltage system based on the collected sensor data. If the insulation performance is poor, the solution will determine that the high-voltage system has a risk of low insulation value.

[0112] 3. Risk Warning and Troubleshooting

[0113] Risk warning: When it is determined that the high-voltage system has a risk of low insulation value, a risk warning can be output through the instrument panel, sound prompts or vehicle information system.

[0114] Exemplarily, the content of the risk warning includes at least one of the specific degree of low insulation value, possible impact or recommended measures, etc., which is not limited in this application.

[0115] Fault handling: While outputting risk warnings, the solution can also take corresponding fault handling measures according to the preset fault handling process. For example, high-voltage accessory equipment (such as air-conditioning compressor) can be controlled to stop working to reduce the risks that may be caused by low insulation value. In addition, if the problem of low insulation value persists or worsens further, more stringent fault handling measures may be taken, such as cutting off all high-voltage circuits and issuing emergency alarms.

[0116] For example, an emergency alarm may be issued in the following ways: an emergency alarm signal may be issued through a vehicle speaker, hazard warning lights, and vehicle information system. For example, the speaker may continue to sound and the hazard warning lights may continue to flash to indicate to surrounding vehicles and pedestrians that an emergency situation has occurred in the vehicle. In addition, the vehicle information system may also send a distress message containing key information such as the vehicle location or fault type to a customer service center, rescue agency, or preset emergency contact, so that relevant personnel can rush to the scene in time for rescue and handling, which is not limited in this application.

[0117] 4. Improve system stability and reliability

[0118] Redundant design: In order to improve the stability and reliability of the high-voltage system, redundant design can also be adopted. For example, backup devices are set up for key components or important links of the high-voltage system so that when the main device fails to work normally, the backup device can quickly take over the work.

[0119] Self-protection mechanism: The high-voltage system also has a self-protection mechanism, for example, it automatically cuts off the high-voltage circuit when an abnormality related to insulation performance is detected to prevent the fault from further expanding.

[0120] It should be noted that in the event of an insulation fault in the high-voltage system, the embodiment of the present application can also locate the fault position in the following manner: first, control the high-voltage system to remain in the high-voltage circuit state for a period of time, and obtain the real-time insulation fault code during this period. Next, based on the obtained real-time high-voltage circuit state and real-time insulation fault code, the specific location of the insulation fault in the high-voltage system is located through a specific algorithm. This fault location method effectively improves the accuracy of locating the insulation fault of the high-voltage system, and helps to promptly discover and solve the problem of low insulation during driving.

[0121] Figure 2 is a flow chart of a vehicle control method provided in an embodiment of the present application. The execution subject of the method is a vehicle. Exemplarily, the method is jointly executed by the BMS and the VCU, which is not limited in the present application. Figure 2 The method flow includes:

[0122] 201. The vehicle obtains key electrical parameters by installing sensors on the first electrical system; the first electrical system refers to an electrical system whose operating voltage exceeds the safety voltage for the human body; the key electrical parameters are used to reflect the insulation performance of the first electrical system.

[0123] In the embodiments of the present application, the first electrical system is generally referred to as a high-voltage system. Exemplarily, the high-voltage system includes, but is not limited to: a power battery, a drive motor, a motor controller, an inverter, a high-voltage distribution box, an electric compressor, a DC-DC converter, an on-board charger, a PTC heater or a high-voltage cable, etc., which is not limited in the present application. In addition, the electrical parameters collected by the sensor are generally transmitted via wired communication, such as transmission using a CAN (Controller Area Network) bus, which is also not limited in the present application.

[0124] In some embodiments, the electrical parameters used to measure the insulation performance of the high-voltage system include parameters such as temperature and humidity in addition to current and voltage, which are not limited in this application. Accordingly, the key electrical parameters are obtained through sensors installed on the high-voltage system of the vehicle, including:

[0125] 1. Obtain voltage values ​​through voltage sensors installed at different nodes of the vehicle's high-voltage circuit.

[0126] Exemplarily, the above-mentioned node may be the output end of a power battery, the input end of a drive motor, the connection point of a high-voltage cable, etc., which is not limited in the present application.

[0127] 2. Obtain the current value by installing a current sensor on the path where the current flows.

[0128] For example, the current sensor can be connected in series in the high-voltage cable to accurately measure the current value passing through. In addition, the current sensor can be a Hall effect current sensor, which uses the Hall effect principle to generate a corresponding Hall voltage when current passes through, thereby achieving accurate measurement of the current. In addition, the range of the current sensor can be set according to the maximum operating current of the vehicle high-voltage system, which is not limited in this application.

[0129] 3. Obtain a temperature value through a temperature sensor installed at the first component of the high-voltage system.

[0130] Since excessively high temperatures may affect the performance of insulating materials, leading to problems such as a decrease in insulation resistance, the temperature can also be monitored by a temperature sensor. Exemplarily, the first component refers to a high-voltage component, such as a power battery or a drive motor, etc., which is not limited in this application. For example, the temperature sensor is installed on the surface of the drive motor or a key heating part inside.

[0131] 4. Obtain the humidity value through the humidity sensor installed at the second component of the high-voltage system.

[0132] Since moisture may invade the high-voltage system when the vehicle is driving in a humid environment, thereby affecting the insulation performance of the high-voltage system, the humidity can also be monitored by a humidity sensor. Among them, the second component also refers to the high-voltage component. It should be noted that the first component and the second component can be the same or different. In other words, the installation position of the humidity sensor and the installation position of the temperature sensor can be completely the same, partially the same, or completely different, and this application does not limit this.

[0133] During the driving process of the vehicle, the vehicle monitors the insulation status of the high-voltage system continuously and uninterruptedly. Generally speaking, the monitoring frequency can reach several times per second or even higher. In other embodiments, the embodiments of the present application will also determine the monitoring frequency in the following ways, and then control the above-mentioned sensors to collect electrical parameters according to the determined monitoring frequency: determine the parameter acquisition frequency according to the type of vehicle and the driving conditions during the current driving process; obtain key electrical parameters according to the determined parameter acquisition frequency through sensors installed on the high-voltage system.

[0134] The types of vehicles include, but are not limited to, private cars, electric buses, electric trucks, electric engineering vehicles, or electric sanitation vehicles, etc., which are not limited in this application. In addition, the driving conditions include acceleration, deceleration, uneven roads, frequent starts and stops, climbing a slope with full load, or driving in harsh environments (such as water accumulation, dust, high temperature or humidity, etc.), which are also not limited in this application.

[0135] It should be noted that the more severe the vehicle's current driving conditions, the more likely the vehicle type is to be in complex road conditions or driving environments, and the heavier the vehicle load, the greater the monitoring frequency value.

[0136] 202. The vehicle determines an insulation state of the first electrical system based on the acquired key electrical parameters.

[0137] As an example, the insulation state of the high-voltage system can be determined by either a circuit mathematical model or a machine learning model, which is not limited in this application.

[0138] 2021. Taking the determination of the insulation state of a high-voltage system through a circuit mathematical model as an example, the insulation state assessment includes but is not limited to the following steps:

[0139] The acquired key electrical parameters are preprocessed to obtain the preprocessed key electrical parameters; the constructed circuit mathematical model is called to determine the values ​​of the insulation performance indicators of the high-voltage system based on the preprocessed key electrical parameters; the insulation state of the high-voltage system is determined according to the determined values ​​of the insulation performance indicators and the preset safety threshold.

[0140] Exemplarily, the preprocessing includes, but is not limited to, filtering processing to remove unnecessary high-frequency noise or low-frequency interference signals and extract effective signal components reflecting insulation performance.

[0141] In addition, the circuit mathematical model may be an equivalent circuit analysis model, which is not limited in this application.

[0142] In addition, the insulation performance index includes the insulation resistance value, and accordingly, the preset safety threshold includes the insulation resistance safety threshold. Of course, in addition to the insulation resistance, other key indicators for measuring the insulation performance of the high voltage system may also be included, such as partial discharge, which is not limited in this application.

[0143] 2022. Taking the determination of the insulation status of a high-voltage system through a machine learning model as an example, the insulation status assessment includes but is not limited to the following steps:

[0144] The acquired key electrical parameters are preprocessed to obtain the preprocessed key electrical parameters; the preprocessed key electrical parameters are feature extracted, and the extracted features are input into the constructed insulation state determination model, and the insulation state determination model is called to determine the insulation state of the high voltage system.

[0145] For example, when extracting features of key electrical parameters after preprocessing, features such as amplitude, frequency, phase or waveform change rate can be extracted, and then the relationship between these features and insulation performance can be analyzed through a machine learning model.

[0146] In addition, the output of the insulation status determination model includes but is not limited to the value of the insulation performance index and the insulation failure probability, which is not limited in this application.

[0147] The insulation state determination model is a machine learning model obtained through training based on training samples. In some embodiments, the training process of the insulation state determination model includes:

[0148] First, a training sample is obtained, which includes the key electrical parameters of samples under different insulation states; then, the key electrical parameters of the samples included in the training sample are preprocessed to obtain the preprocessed training sample; next, the feature extraction of the preprocessed training sample is performed, and the extracted features are input into the initial machine learning model, and then the machine learning model is called to predict the insulation state corresponding to the processed training sample. Then, the difference between the actual insulation state and the predicted insulation state corresponding to the training sample is determined through the constructed loss function; then, the network parameters of the machine learning model are optimized based on the determined difference until the training stop condition is met, and the insulation state determination model is obtained.

[0149] Exemplarily, the above loss function may be a cross entropy loss function, and the above training stop condition may be that the number of iterations reaches a preset number, or that the determined difference is less than a preset value, which is not limited in the present application.

[0150] 203. If the determined insulation state indicates that there is an insulation risk in the first electrical system, the vehicle determines a risk level corresponding to the insulation risk in the first electrical system.

[0151] In some embodiments, taking the method of determining the insulation state of a high voltage system by a circuit mathematical model as an example, determining the risk level corresponding to the insulation risk includes but is not limited to the following steps:

[0152] The risk level corresponding to the insulation risk in the high-voltage system is determined based on the degree to which the insulation performance indicators deviate from the safety threshold, the speed of insulation performance change, and the insulation performance change trend.

[0153] As an example, taking the insulation resistance value as an example, assuming that the insulation resistance value is less than the preset insulation resistance safety threshold, it is determined that there is an insulation risk in the high-voltage system, and the risk level will be further divided. For example, based on factors such as the degree to which the insulation resistance value deviates from the insulation resistance safety threshold, the speed of change of the insulation resistance, and the change trend of the insulation resistance, the risk level is divided into three levels: low, medium, and high. If the insulation resistance value is slightly lower than the insulation resistance safety threshold, and the change speed is relatively slow, and the change trend is relatively gentle, it may be judged as a low risk. If the insulation resistance value is much lower than the insulation resistance safety threshold, and the decline is large, and there is a trend of rapid decline, it may be judged as a high risk.

[0154] In other embodiments, taking the example of determining the insulation state of a high-voltage system through a machine learning model, the risk level corresponding to the insulation risk is determined, including but not limited to the following steps: determining the insulation failure probability output by the model based on the insulation state, and determining the risk level corresponding to the insulation risk existing in the high-voltage system.

[0155] 204. The vehicle performs at least one of fault processing or outputs prompt information according to the determined risk level; wherein the prompt information includes at least one of insulation performance details, potential impact on the vehicle, or safety measures that can be taken.

[0156] In the embodiment of the present application, the prompt information can be output through the instrument panel, the speaker or the vehicle information system, and the present application does not limit this. Among them, the insulation performance details refer to the specific degree of low insulation value, the potential impact on the vehicle refers to the actual impact that the low insulation value may bring to the vehicle, and the safety measures that can be taken refer to reasonable suggestions based on the specific degree of low insulation value.

[0157] It should be noted that if the determined risk level is low, only a prompt message may be output without performing fault handling, and this application does not limit this.

[0158] In some embodiments, performing fault processing on a vehicle includes at least one of the following:

[0159] 1. At least one device controlling the vehicle stops working.

[0160] For example, some non-critical but relatively energy-intensive high-voltage accessory devices that may cause greater failures due to insulation problems are controlled to stop running. Taking the mobilization of the compressor as an example, stopping its operation can reduce the current in the high-voltage circuit and reduce the risks of leakage, short circuit, etc. that may be caused by low insulation value. At the same time, high-voltage accessory devices such as PTC heaters may also be shut down, which is not limited in this application.

[0161] 2. Set some functions of the vehicle to restricted use.

[0162] In addition to shutting down high-voltage accessory equipment, some vehicle functions will also be restricted. For example, the maximum speed limit of the vehicle will be appropriately reduced to prevent the high-voltage system from being overloaded and further exacerbating insulation problems; or the fast charging function of the vehicle will be restricted to avoid charging accidents caused by low insulation values ​​during the charging process.

[0163] 3. Cut off the vehicle’s high-voltage circuit.

[0164] 4. Call the target number.

[0165] Exemplarily, the target number may be a customer service center number, a rescue agency number, or a contact number pre-set by the vehicle owner, and this application does not limit this.

[0166] 5. Send an alarm message to the target number; illustratively, the alarm message includes the vehicle location and fault type.

[0167] 6. Control the vehicle's external lighting components to flash.

[0168] 7. The vehicle's speakers are controlled to sound continuously.

[0169] 8. Control the faulty equipment with insulation failure to stop working and start the backup equipment of the faulty equipment.

[0170] In summary, the vehicle control scheme provided by the embodiment of the present application improves the safety and reliability of vehicle operation. In detail, the scheme collects key electrical parameters through sensors installed on the high-voltage system. Since these parameters can reflect the insulation performance of the high-voltage system and are an important basis for evaluating the insulation performance of the high-voltage system, the insulation state of the high-voltage system can be effectively and accurately evaluated by processing and analyzing these parameters. In addition, when it is determined that the high-voltage system has a problem of poor insulation performance, the scheme can also promptly handle the fault and prompt the insulation risks faced by the vehicle, which provides a strong guarantee for the safe operation of new energy vehicles and greatly reduces the probability of safety accidents such as electric shock to personnel and vehicle damage.

[0171] Figure 3 is a schematic diagram of the structure of a vehicle control device provided in an embodiment of the present application. Figure 3 , the device comprises:

[0172] The acquisition module 301 is configured to acquire key electrical parameters through a sensor installed on a first electrical system of the vehicle; wherein the first electrical system refers to an electrical system whose operating voltage exceeds a human safety voltage; and the key electrical parameters are used to reflect the insulation performance of the first electrical system;

[0173] A first determination module 302 is configured to determine an insulation state of the first electrical system based on the acquired key electrical parameters;

[0174] A second determination module 303 is configured to determine a risk level corresponding to the insulation risk if the determined insulation state indicates that the first electrical system has an insulation risk;

[0175] The control module 304 is configured to perform at least one of fault processing on the vehicle or outputting prompt information according to the determined risk level;

[0176] The prompt information includes at least one of insulation performance details, potential impact on the vehicle, or safety measures that can be taken.

[0177] The vehicle control scheme provided in the embodiment of the present application improves the safety and reliability of vehicle operation. In detail, the scheme collects key electrical parameters through sensors installed on the high-voltage system. Since these parameters can reflect the insulation performance of the high-voltage system and are an important basis for evaluating the insulation performance of the high-voltage system, the insulation state of the high-voltage system can be effectively and accurately evaluated by processing and analyzing these parameters. In addition, when it is determined that the high-voltage system has a problem of poor insulation performance, the scheme can also handle the fault in a timely manner and prompt the insulation risks faced by the vehicle, which provides a strong guarantee for the safe operation of new energy vehicles and greatly reduces the probability of safety accidents such as electric shock to personnel and vehicle damage.

[0178] In some embodiments, the acquisition module 301 is configured to:

[0179] The voltage value is obtained by installing voltage sensors at different nodes of the vehicle's high-voltage circuit;

[0180] The current value is obtained by installing a current sensor on the path through which the current flows;

[0181] acquiring a temperature value through a temperature sensor installed at a first component of the first electrical system;

[0182] A humidity value is obtained by a humidity sensor installed at the second component of the first electrical system.

[0183] In some other embodiments, the acquisition module 301 is configured to:

[0184] Determining a parameter acquisition frequency according to the type of the vehicle and the driving condition during the current driving process;

[0185] The key electrical parameters are obtained by obtaining a frequency according to the determined parameters through a sensor installed on the first electrical system.

[0186] In some other embodiments, the first determining module 302 is configured to:

[0187] Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters;

[0188] Calling the constructed circuit mathematical model, and determining the value of the insulation performance index of the first electrical system based on the preprocessed key electrical parameters;

[0189] The insulation state of the first electrical system is determined according to the value of the insulation performance indicator and a preset safety threshold.

[0190] In other embodiments, the second determination module 303 is configured to determine the risk level corresponding to the insulation risk according to the degree to which the insulation performance indicator deviates from the safety threshold, the speed of insulation performance change, and the insulation performance change trend.

[0191] In some other embodiments, the first determining module 302 is configured to:

[0192] Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters;

[0193] Extracting features of the preprocessed key electrical parameters, inputting the extracted features into a constructed insulation state determination model, calling the insulation state determination model, and determining the insulation state of the first electrical system;

[0194] Wherein, the insulation state determination model is a machine learning model obtained through training based on training samples.

[0195] In some other embodiments, the training process of the insulation state determination model includes:

[0196] Acquire the training samples; wherein the training samples include key electrical parameters of samples under different insulation states;

[0197] Preprocessing the key electrical parameters of the samples included in the training samples to obtain preprocessed training samples;

[0198] Extracting features from the preprocessed training samples, inputting the extracted features into an initial machine learning model, calling the machine learning model, and predicting the insulation state corresponding to the processed training samples;

[0199] Determining the difference between the actual insulation state and the predicted insulation state corresponding to the training sample by means of the constructed loss function;

[0200] The network parameters of the machine learning model are optimized based on the determined differences until a training stop condition is met, thereby obtaining the insulation state determination model.

[0201] In other embodiments, the output of the insulation state determination model includes the value of the insulation performance index and the insulation failure probability;

[0202] The second determination module 303 is configured to determine the risk level corresponding to the insulation risk according to the value of the insulation performance indicator and the insulation failure probability.

[0203] In some other embodiments, the control module 304 is configured to perform at least one of the following:

[0204] Controlling at least one device of the vehicle to stop working;

[0205] Setting some functions of the vehicle to a restricted use state;

[0206] Cut off the vehicle's high-voltage circuit;

[0207] Call the target number;

[0208] Sending an alarm message to the target number; wherein the alarm message includes the vehicle location and fault type;

[0209] Controlling the exterior lighting assembly of the vehicle to flash;

[0210] Controlling the loudspeaker of the vehicle to sound continuously;

[0211] The faulty device with insulation failure is controlled to stop working, and the backup device of the faulty device is started.

[0212] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present application, which will not be described one by one here.

[0213] It should be noted that: the vehicle control device provided in the above embodiment only uses the division of the above functional modules as an example when performing vehicle control. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the vehicle control device provided in the above embodiment and the vehicle control method embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0214] Figure 4 It is a structural schematic diagram of a vehicle controller provided according to an embodiment of the present application.

[0215] Typically, the vehicle controller 400 includes: a main control module 401, a CAN interface 402, a hard-wire input interface 403, and a hard-wire output interface 404. The main control module 401 is connected to the CAN interface 402, the hard-wire input interface 403, and the hard-wire output interface 404, respectively.

[0216] The main control module 401 generally includes a processor and a memory. Among them, the processor may include one or more processing cores, such as a 4-core processor, a 4-core processor, etc. The processor may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the vehicle display screen. In some embodiments, the processor may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning. The memory may include one or more computer-readable storage media, which may be non-transitory. The memory may also include a high-speed random access memory and a non-volatile memory, such as one or more disk storage devices and flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory is used to store at least one computer program, and the at least one computer program is used to be executed by the processor to implement the vehicle control method provided by the method embodiment of the present application.

[0217] The CAN interface 402 may include a power CAN interface, a motor CAN interface, and a diagnostic CAN interface, wherein the power CAN interface is used to communicate with a power system module of the vehicle, the motor CAN interface is used to communicate with a motor controller of the vehicle, and the diagnostic CAN interface is used to communicate with a diagnostic device.

[0218] The hard-wire input interface 403 is used to receive hard-wire control signals. The hard-wire output interface 404 is used to send control instructions to the electronic control components of the vehicle so that the electronic control components of the vehicle perform corresponding actions. The electronic control components of the vehicle include a power management system, a motor controller, an on-board charger, a body control system, etc.

[0219] The main control module 401 can communicate with the vehicle's power system module, motor controller and diagnostic equipment through the CAN interface 402, and generate control instructions based on the hard-wired control signal received by the hard-wired input interface 403 to send control instructions to the vehicle's electronic control components through the hard-wired output interface 404.

[0220] Those skilled in the art will understand that Figure 4 The structure shown in the figure does not constitute a limitation on the vehicle controller 400, and may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0221] In an exemplary embodiment, a computer-readable storage medium is also provided, such as a memory including a program code, and the program code can be executed by a processor in a vehicle controller to complete the vehicle control method. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device.

[0222] In an exemplary embodiment, a computer program product or a computer program is also provided, which includes a computer program code, which is stored in a computer-readable storage medium. The processor of the vehicle controller reads the computer program code from the computer-readable storage medium, and the processor executes the computer program code, so that the vehicle controller executes the above-mentioned vehicle control method.

[0223] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0224] The above description is only an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A vehicle control method, characterized in that: The method comprises: Acquiring key electrical parameters through sensors installed on a first electrical system of the vehicle; wherein the first electrical system refers to an electrical system whose operating voltage exceeds a safety voltage for human bodies; and the key electrical parameters are used to reflect the insulation performance of the first electrical system; Determining an insulation state of the first electrical system based on the acquired key electrical parameters; If the determined insulation state indicates that the first electrical system has an insulation risk, determining a risk level corresponding to the insulation risk; According to the determined risk level, at least one of performing fault processing on the vehicle or outputting prompt information; The prompt information includes at least one of insulation performance details, potential impact on the vehicle, or safety measures that can be taken.

2. The method according to claim 1, characterized in that The step of obtaining key electrical parameters by using a sensor installed on a first electrical system of the vehicle includes: The voltage value is obtained by installing voltage sensors at different nodes of the vehicle's high-voltage circuit; The current value is obtained by installing a current sensor on the path through which the current flows; acquiring a temperature value through a temperature sensor installed at a first component of the first electrical system; A humidity value is obtained by a humidity sensor installed at the second component of the first electrical system.

3. The method according to claim 1, characterized in that The step of obtaining key electrical parameters by using a sensor installed on a first electrical system of the vehicle includes: Determining a parameter acquisition frequency according to the type of the vehicle and the driving condition during the current driving process; The key electrical parameters are obtained by obtaining a frequency according to the determined parameters through a sensor installed on the first electrical system.

4. The method according to claim 1, characterized in that: The determining the insulation state of the first electrical system based on the acquired key electrical parameters includes: Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters; Calling the constructed circuit mathematical model, and determining the value of the insulation performance index of the first electrical system based on the preprocessed key electrical parameters; The insulation state of the first electrical system is determined according to the value of the insulation performance indicator and a preset safety threshold.

5. The method according to claim 4, characterized in that Determining the risk level corresponding to the insulation risk includes: The risk level corresponding to the insulation risk is determined according to the degree to which the insulation performance indicator deviates from the safety threshold, the speed of insulation performance change, and the insulation performance change trend.

6. The method according to claim 1, characterized in that The determining the insulation state of the first electrical system based on the acquired key electrical parameters includes: Preprocessing the acquired key electrical parameters to obtain preprocessed key electrical parameters; Extracting features of the preprocessed key electrical parameters, inputting the extracted features into a constructed insulation state determination model, calling the insulation state determination model, and determining the insulation state of the first electrical system; Wherein, the insulation state determination model is a machine learning model obtained through training based on training samples.

7. The method according to claim 6, characterized in that The training process of the insulation state determination model includes: Acquire the training samples; wherein the training samples include key electrical parameters of samples under different insulation states; Preprocessing the key electrical parameters of the samples included in the training samples to obtain preprocessed training samples; Extracting features from the preprocessed training samples, inputting the extracted features into an initial machine learning model, calling the machine learning model, and predicting the insulation state corresponding to the processed training samples; Determining the difference between the actual insulation state and the predicted insulation state corresponding to the training sample by means of the constructed loss function; The network parameters of the machine learning model are optimized based on the determined differences until a training stop condition is met, thereby obtaining the insulation state determination model.

8. The method according to claim 6, characterized in that The output of the insulation state determination model includes an insulation failure probability; and the risk level corresponding to the insulation risk is determined, including: A risk level corresponding to the insulation risk is determined according to the insulation failure probability.

9. The method according to any one of claims 1 to 8, characterized in that The performing fault processing on the vehicle includes at least one of the following: Controlling at least one device of the vehicle to stop working; Setting some functions of the vehicle to a restricted use state; Cut off the vehicle's high-voltage circuit; Call the target number; Sending an alarm message to the target number; wherein the alarm message includes the vehicle location and fault type; Controlling the exterior lighting assembly of the vehicle to flash; Controlling the loudspeaker of the vehicle to sound continuously; The faulty device with insulation failure is controlled to stop working, and the backup device of the faulty device is started.

10. A vehicle control device, characterized in that: The device comprises: an acquisition module, configured to acquire key electrical parameters through a sensor installed on a first electrical system of the vehicle; wherein the first electrical system refers to an electrical system whose operating voltage exceeds a human safety voltage; and the key electrical parameters are used to reflect the insulation performance of the first electrical system; A first determination module is configured to determine an insulation state of the first electrical system based on the acquired key electrical parameters; A second determination module is configured to determine a risk level corresponding to the insulation risk if the determined insulation state indicates that the first electrical system has an insulation risk; a control module configured to perform at least one of performing fault processing on the vehicle or outputting prompt information according to the determined risk level; The prompt information includes at least one of insulation performance details, potential impact on the vehicle, or safety measures that can be taken.

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