Vehicle redundant power supply method, device and equipment and storage medium

Abstract

The invention provides a vehicle redundant power supply method, device and equipment and a storage medium, the device is composed of a sensor, an energy converter, a control unit, a standby capacitor and a collision detection and energy distribution module, the sensor is responsible for monitoring driving parameters such as vehicle speed, acceleration and brake force, the energy converter converts kinetic energy into electric energy when a vehicle brakes, and the control unit is used for controlling the control unit. The control unit judges the running state of the vehicle according to data provided by the sensor and determines the energy recovery proportion according to the preset energy recovery rate mapping relation, the standby capacitor serves as temporary energy storage equipment and receives and stores electric energy converted from kinetic energy, and when the collision detection module recognizes a collision event, the energy distribution module is triggered to work, and the energy recovery rate is increased. Distributing the energy stored in the standby capacitor to a key function unit of the vehicle according to a preset priority; according to the device, the basic power supply requirement of the vehicle in an emergency state is ensured through energy recovery and release, and the safety performance of the vehicle is effectively improved while the energy loss is reduced.

Description

Technical Field

[0001] The present application relates to the field of intelligent control technology, and in particular to a vehicle redundant power supply method, device, equipment and storage medium. Background Art

[0002] With the rapid development of the automobile industry and the enhancement of environmental awareness, how to effectively utilize the energy generated during vehicle driving, especially the kinetic energy wasted during braking, has become a research focus. When traditional vehicles brake, most of the kinetic energy is dissipated in the form of heat energy, which not only causes energy waste, but also increases the burden on the environment. In recent years, although some new energy vehicles have adopted regenerative braking systems to recover part of the braking energy, their recovery efficiency and application scope are still limited.

[0003] The existing vehicle power supply system mainly relies on on-board batteries or generators to provide electricity, which to a certain extent meets the needs of vehicle electrification. However, in the event of an emergency such as a collision, the conventional power supply may fail, causing the safety assistance system to fail to work properly, increasing the risk of accidents. In addition, the existing system lacks a flexible response mechanism for changes in energy demand under different driving conditions of the vehicle, making it difficult to achieve effective management and distribution of energy. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the prior art, the present application provides a vehicle redundant power supply method, device, equipment and storage medium to solve the above-mentioned technical problems.

[0005] The present application provides a redundant power supply device for a vehicle, the device comprising: a sensor for monitoring vehicle driving parameters, the vehicle driving parameters including vehicle speed, acceleration and braking force; a control unit connected to the sensor, for determining a vehicle driving state based on the vehicle driving parameters, and determining a current energy recovery rate corresponding to the current vehicle driving state according to a preset energy recovery rate mapping relationship, the energy recovery rate mapping relationship being used to characterize the relationship between the vehicle driving state and the energy recovery rate; an energy converter, for converting kinetic energy generated when the vehicle brakes into electrical energy according to the current energy recovery rate; a backup capacitor, connected to the energy converter and the control unit, for storing electrical energy obtained based on kinetic energy conversion into the backup capacitor; a collision detection module, for monitoring the occurrence of a collision event, and transmitting a collision signal generated when a collision event occurs to an energy distribution module; an energy distribution module, connected to the backup capacitor and the collision detection module, for distributing the energy in the backup capacitor to each functional unit of the vehicle according to a preset priority order when a collision signal is detected.

[0006] In one embodiment of the present application, the energy distribution module includes a neural network for predicting the operating time of each functional unit combination of the vehicle powered by the backup capacitor under different backup capacitor storage capacities and different vehicle driving conditions.

[0007] In one embodiment of the present application, the neural network includes: a data collection module for collecting working time data of different functional units under different residual energy conditions; a data preprocessing module for data cleaning, feature selection, data standardization and data segmentation; a multi-layer perceptron model, including an input layer, a hidden layer and an output layer; a training module for training the initial model using a preset loss function and optimizer to obtain a working time prediction model; an evaluation module for evaluating the prediction accuracy of the working time prediction model using a test set, and if the prediction accuracy is lower than a preset accuracy threshold, the working time prediction model is optimized until its prediction accuracy is greater than or equal to the preset accuracy threshold.

[0008] In one embodiment of the present application, the energy allocation module also includes: a priority sorting module, which is used to sort the power supply priorities of functional units according to the prediction results and preset functional priorities; an energy allocation calculation module, which is used to preferentially allocate energy to functional units with higher power supply priorities; and a real-time adjustment module, which is used to dynamically adjust the energy allocation according to the energy consumption and remaining energy monitored in real time.

[0009] The present application provides a vehicle redundant power supply method, the method comprising: monitoring vehicle driving parameters, the vehicle driving parameters including at least vehicle speed, acceleration and braking force; comparing the vehicle driving parameters with preset vehicle driving parameter thresholds to determine the vehicle's driving state, and determining a current energy recovery rate that matches the current vehicle driving state based on a preset energy recovery rate mapping relationship, wherein the energy recovery rate mapping relationship is used to characterize the relationship between the vehicle's driving state and the energy recovery rate; converting the kinetic energy generated when the vehicle brakes into electrical energy based on the current energy recovery rate, and storing the electrical energy in a backup capacitor; monitoring the occurrence of a collision event, generating a collision signal if a collision event is detected, and transmitting the collision signal to an energy distribution module; when the energy distribution module receives the collision signal, allocating energy from the backup capacitor to each functional unit of the vehicle according to a preset priority order.

[0010] In one embodiment of the present application, before allocating energy from the backup capacitor to each functional unit of the vehicle according to a preset priority order, it also includes: obtaining the current stored power of the backup capacitor, the current driving state of the vehicle, and the target power supply time; based on a trained working time prediction model, predicting the working time of each functional unit combination powered by the backup capacitor under the current stored power and the current driving state, so as to obtain the available working time of various functional unit combinations; determining any functional unit combination whose available working time is greater than the target power supply time as a target functional unit combination, and determining each functional unit in the target functional unit combination as a target functional unit.

[0011] In one embodiment of the present application, energy is allocated from a backup capacitor to each functional unit of a vehicle according to a preset priority order, including: obtaining an importance score and an urgency score of each target functional unit, and a weight ratio of the importance and urgency; calculating the importance score and the urgency score of each target functional unit based on the weight ratio to obtain a comprehensive score of each target functional unit; sorting each target functional unit of the vehicle according to the comprehensive score to obtain a power supply priority list; obtaining a basic energy requirement of each target functional unit, the basic energy requirement being the minimum energy requirement for maintaining the startup of the functional unit; assigning a weighting coefficient to each target table functional unit based on the power supply priority list, and allocating the current stored power of the backup capacitor to each target functional unit of the vehicle based on the weighting coefficient.

[0012] In one embodiment of the present application, after allocating energy from the backup capacitor to various functional units of the vehicle, it also includes: obtaining user feedback, the user feedback including user satisfaction and user-recommended power supply priority; when the user satisfaction is lower than a preset satisfaction threshold, the user-recommended power supply priority is used as an input item to optimize the training working time prediction model.

[0013] The present application provides an electronic device, comprising a processor, a memory and a communication bus; the communication bus is used to connect the processor and the memory; the processor is used to execute a computer program stored in the memory to implement the vehicle redundant power supply method as described above.

[0014] The present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is used to enable a computer to execute the vehicle redundant power supply method as described above.

[0015] Beneficial effects of the present application: The redundant power supply device for vehicles in the present application efficiently converts the kinetic energy generated when the vehicle brakes into electrical energy through an energy converter, and stores it through a backup capacitor, thereby reducing the waste of energy during braking and providing an additional source of electricity for the vehicle; the control unit can accurately judge the driving state of the vehicle according to the driving parameters of the vehicle monitored by the sensor, and automatically adjust the storage ratio of electrical energy according to the preset energy recovery rate mapping relationship, so that the collection and storage of energy are more efficient and reasonable, and adapt to the changes in energy demand under different driving conditions; the combined use of the collision detection module and the energy distribution module can quickly respond and distribute the energy in the backup capacitor to the key functional units of the vehicle according to the preset priority in emergency situations such as collisions, ensuring that these systems can operate normally even when the main power fails, greatly improving the safety performance of the vehicle in emergency situations. In summary, the present application not only solves the shortcomings of traditional vehicles in energy recovery and management by integrating advanced sensing technology, energy conversion technology and intelligent control strategies, but also provides an effective solution for improving the overall performance and safety of the vehicle.

[0016] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0018] Figure 1 is a schematic diagram of an implementation environment of a vehicle redundant power supply method shown in an exemplary embodiment of the present application;

[0019] Figure 2 is a structural schematic diagram of a vehicle redundant power supply device shown in an exemplary embodiment of the present application;

[0020] Figure 3 is a flowchart of the implementation steps of a vehicle redundant power supply method shown in an exemplary embodiment of the present application;

[0021] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0022] The following will describe the implementation methods of the present application with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific implementation methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, not for limiting the scope of protection of the present application.

[0023] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application, and thus the drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed at will, and the component layout may also be more complicated.

[0024] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0025] Figure 1 It is a schematic diagram of an implementation environment of a vehicle redundant power supply method shown in an exemplary embodiment of the present application.

[0026] like Figure 1 As shown, the implementation environment of the vehicle redundant power supply method includes a sensor 101, an energy converter 102, a control unit 103, a backup capacitor 104, a collision detection module 105 and an energy distribution module 106. The functions of each component are described as follows:

[0027] Sensor 101: responsible for monitoring key parameters of the vehicle during driving, including at least vehicle speed, acceleration and braking force. These data are crucial for judging the current driving state of the vehicle and provide the necessary information basis for subsequent energy conversion and storage.

[0028] Energy converter 102: During the vehicle braking process, the kinetic energy generated when the vehicle decelerates can be effectively converted into electrical energy. This process not only helps to recover some of the energy that would normally be wasted in the form of heat energy, but also provides an additional source of electricity for the vehicle, thereby improving energy utilization efficiency.

[0029] Control unit 103: Receives data from sensor 101 and compares the vehicle driving parameters with preset thresholds to identify the vehicle's driving state. Based on the preset energy recovery rate mapping relationship, the control unit can determine the best energy recovery rate that matches the current driving state. This mapping relationship defines the optimal energy storage strategy under specific driving conditions, ensuring effective management and utilization of energy.

[0030] Backup capacitor 104: As a temporary storage device for electric energy, backup capacitor 104 can receive and store electric energy converted by energy converter 102 according to the energy recovery rate determined by control unit 103. In emergency situations, such as when a collision occurs, the electric energy in the backup capacitor can be quickly released to provide necessary power support for key systems of the vehicle.

[0031] Collision detection module 105: Continuously monitors the environment around the vehicle, especially being highly sensitive to possible collision events. Once a collision event is detected, a collision signal is immediately generated and sent to the energy distribution module 106. This module is designed to improve vehicle safety performance and ensure rapid response when an accident occurs.

[0032] Energy distribution module 106: After receiving the collision signal, it draws energy from the backup capacitor 104 and distributes it to different functional units of the vehicle according to the preset priority order. This process ensures that even under extreme conditions, the key systems of the vehicle can continue to operate, such as the activation of airbags and emergency communication systems, so as to maximize the safety of passengers.

[0033] In summary, the implementation environment design of the vehicle redundant power supply method fully considers the vehicle's power demand during normal driving and emergency situations, and achieves improved reliability and safety of the vehicle power supply system through efficient energy conversion, precise control logic and fast energy distribution mechanism.

[0034] Figure 2 It is a schematic structural diagram of a vehicle redundant power supply device shown in an exemplary embodiment of the present application.

[0035] like Figure 2As shown, the vehicle redundant power supply device is composed of a sensor, an energy converter, a control unit, a backup capacitor and a collision detection and energy distribution module, wherein the sensor is used to monitor the vehicle driving parameters, and the energy recovery rate vehicle driving parameters include vehicle speed, acceleration and braking force; the control unit is connected to the energy recovery rate sensor, and is used to determine the vehicle driving state based on the vehicle driving parameters, and determine the current energy recovery rate corresponding to the current vehicle driving state according to a preset energy recovery rate mapping relationship, and the energy recovery rate mapping relationship is used to characterize the relationship between the vehicle driving state and the energy recovery rate; the energy converter is used to convert the kinetic energy generated when the vehicle brakes into electrical energy according to the current energy recovery rate; the backup capacitor is connected to the energy recovery rate energy converter and the energy recovery rate control unit, and is used to store the electrical energy obtained based on the kinetic energy conversion into the backup capacitor; the collision detection module is used to monitor the occurrence state of the collision event, and transmit the collision signal generated when the collision event occurs to the energy distribution module; the energy distribution module is connected to the energy recovery rate backup capacitor and the energy recovery rate collision detection module, and is used to distribute the energy in the backup capacitor to each functional unit of the vehicle according to the preset priority order when the collision signal is detected.

[0036] In one embodiment of the present application, the energy recovery rate energy distribution module includes a neural network for predicting the working time of the combination of various functional units of the vehicle powered by the backup capacitor under different backup capacitor storage capacities and different vehicle driving conditions. Specifically, the neural network includes: a data collection module for collecting working time data of different functional units under different residual energy conditions; a data preprocessing module for data cleaning, feature selection, data standardization and data segmentation; a multi-layer perceptron model, including an input layer, a hidden layer and an output layer; a training module for training the initial model using a preset loss function and an optimizer to obtain a working time prediction model; an evaluation module for evaluating the prediction accuracy of the energy recovery rate working time prediction model using a test set. If the prediction accuracy is lower than the preset accuracy threshold, the energy recovery rate working time prediction model is optimized until its prediction accuracy is greater than or equal to the energy recovery rate preset accuracy threshold.

[0037] In a specific embodiment of the present application, constructing a working time prediction model includes the following steps:

[0038] First, define the type of data that needs to be collected, including the energy consumption characteristics of each safety function (such as power requirements), the remaining energy level (such as the current storage capacity of the backup capacitor), and the actual working time under these conditions. Use the vehicle's sensors and data recording system to collect data under actual driving conditions, ensuring that the data set covers a variety of different driving situations and remaining energy levels, such as city driving, highway driving, emergency braking, etc. Organize the collected data into a format suitable for neural network processing, usually in a structured table format, where each row in the table represents a record, and the columns include safety function type, current energy consumption, remaining energy level, and actual working time.

[0039] Secondly, the collected data is preprocessed, including data cleaning, feature selection, data standardization and data segmentation. During the data cleaning process, outliers and noise are removed, missing data is processed, and the integrity and accuracy of the data are ensured. The features most relevant to the prediction target are selected, such as remaining energy, current energy consumption, safety function type, etc. The input data is standardized to make its mean 0 and standard deviation 1 to improve the training efficiency of the neural network, and the data set is divided into training set, validation set and test set, usually with a ratio of 70% training set, 15% validation set and 15% test set.

[0040] Then, select the Multilayer Perceptron (MLP) model as the neural network architecture. Define the number of nodes in the input layer to match the number of features, for example, 3 nodes (remaining energy, current energy consumption, safety function type). Add a hidden layer and select the Sigmoid activation function. Define the output layer to usually have only one node, using the linear activation function f(x) = xf(x) = x, representing the predicted working hours. For regression problems, select the mean square error (RMSE) as the loss function and use the Adam optimizer.

[0041] Then, initialize the weights ω and bias term b of the neural network, usually using a random initialization method. Calculate the result of the input data in the output layer after passing through the network, and use the loss function to calculate the difference between the predicted result and the true value. According to the result of the loss function, backpropagate the error through the network and calculate the gradient of each parameter. Use the Adam optimizer to update the weights and bias terms of the model according to the gradient. Repeat the above steps until the performance of the model on the validation set no longer improves. And use the test set to evaluate the prediction accuracy of the model and calculate the error between the predicted value and the true value. Use the cross-validation method to evaluate the generalization ability of the model to ensure the stability of the performance of the model on different data sets. Evaluate the performance of the model on the final test set to ensure the prediction accuracy and stability of the model.

[0042] Finally, the trained model is deployed to the actual vehicle system to ensure that the model can run in the actual environment. The model is used to predict the remaining energy and energy consumption data monitored in real time, and calculate the working time of each functional unit. According to the prediction results of the model, the energy allocation strategy is adjusted to ensure that key functional units have sufficient energy support in emergency situations. Feedback data after the model is deployed is collected, including user satisfaction and user-suggested power supply priority, and the model is further optimized based on the feedback data to improve the model's prediction accuracy and user satisfaction.

[0043] In addition, in one embodiment of the present application, the energy allocation module also includes: a priority sorting module, which is used to sort the power supply priority of the functional units according to the prediction results and the preset functional priority; an energy allocation calculation module, which is used to preferentially allocate energy to functional units with higher power supply priorities; and a real-time adjustment module, which is used to dynamically adjust the energy allocation according to the energy consumption and remaining energy monitored in real time.

[0044] like Figure 3 As shown, in an exemplary embodiment, the vehicle redundant power supply method includes at least steps S310 to S350, which are described in detail as follows:

[0045] Step S310, monitoring vehicle driving parameters through sensors, the energy recovery rate vehicle driving parameters at least include vehicle speed, acceleration and braking force.

[0046] In one embodiment of the present application, in order to achieve accurate monitoring of vehicle driving parameters, the following sensors are used to collect the vehicle driving parameters, as follows:

[0047] Vehicle speed sensor: Installed on the axle of the vehicle, used to monitor the vehicle's speed in real time. The vehicle speed sensor usually uses a Hall effect sensor or a magnetoresistive sensor, which can provide high-precision vehicle speed data.

[0048] Accelerometer: Installed at key locations on the vehicle chassis or body to monitor the longitudinal and lateral acceleration of the vehicle. Accelerometers usually use MEMS (micro-electromechanical systems) technology and have the characteristics of high sensitivity and fast response.

[0049] Brake force sensor: Installed in the vehicle's braking system to monitor the braking force applied by the driver. The brake force sensor can be a pressure sensor or a strain gauge sensor that can accurately measure the pressure changes of the brake pedal.

[0050] It should be noted that the collection of sensor data needs to have high time resolution and accuracy to ensure that the system can respond to changes in the vehicle's driving state in a timely and accurate manner. The specific implementation steps are as follows:

[0051] Data sampling frequency: Set the sampling frequency of the sensor, such as 100 times per second, to ensure the real-time and accuracy of the data.

[0052] Data transmission: The sensor transmits data to the control unit via the CAN (Controller Area Network) bus or other high-speed communication protocols. The CAN bus has the characteristics of high reliability and strong anti-interference ability, and is suitable for data transmission in the vehicle environment.

[0053] Data verification: Verify the received data in the control unit to ensure the integrity and accuracy of the data. Common verification methods include parity check, CRC (cyclic redundancy check), etc.

[0054] In step S320, the control unit compares the energy recovery rate vehicle driving parameter with a preset vehicle driving parameter threshold to determine the driving state of the vehicle, and determines the current energy recovery rate that matches the current vehicle driving state based on a preset energy recovery rate mapping relationship, wherein the energy recovery rate mapping relationship defines the correspondence between the vehicle driving state and the energy recovery rate.

[0055] In one embodiment of the present application, when the control unit receives the sensor data, it will immediately process and monitor the status of the data in real time to evaluate the driving condition of the vehicle (i.e., the driving state of the vehicle). The specific implementation process includes first performing data analysis, that is, the control unit will extract key parameters such as vehicle speed, acceleration, and braking force from the received raw data. Subsequently, in the state judgment stage, based on the data obtained from the above analysis, the control unit can determine the current driving state of the vehicle. For example, if the acceleration is displayed as a positive value and exceeds the set threshold, it is considered that the vehicle is in an accelerating state; if the acceleration is a negative value and is lower than a certain threshold, it indicates that the vehicle is decelerating; when the acceleration is close to zero, it can be judged that the vehicle is traveling at a constant speed; and once the braking force exceeds the preset threshold, it means that the vehicle is performing a braking operation. Through this series of steps, the dynamic behavior of the vehicle can be effectively monitored and analyzed.

[0056] Step S330, using an energy converter, converting the kinetic energy generated when the vehicle brakes into electrical energy according to the energy recovery rate and the current energy recovery rate, and storing the electrical energy converted from the kinetic energy in a backup capacitor.

[0057] In one embodiment of the present application, the working state of the energy converter, that is, the kinetic energy recovery rate, is dynamically adjusted according to the driving state of the vehicle to optimize the energy recovery efficiency. The details are as follows:

[0058] First, define a mapping function f to convert the braking force into the recovery power of the energy converter:

[0059] Prec =k1·F brake +k2 Formula (1)

[0060] Among them, P rec is the kinetic energy recovery rate, F brake is the braking force, k1 is the slope coefficient, and k2 is the intercept.

[0061] It should be noted that the slope coefficient and intercept in formula (1) can be calibrated according to experimental data, and the present application does not impose any restrictions on the calibration method and its specific values.

[0062] In addition, in order to avoid excessive load on the vehicle's drive system, the maximum regenerative power is limited as follows:

[0063] P rec =min(P max ,f(F brake )) Formula (2)

[0064] Among them, P rec is the kinetic energy recovery rate, P max is the maximum kinetic energy recovery rate, F brake It's the braking force.

[0065] Then, a PID controller is used to adjust the working state of the energy converter to ensure the optimal energy recovery efficiency, as follows:

[0066]

[0067] Among them, K p , K i , K d They are proportional, integral and differential gains respectively, and E(t) is the error in braking force.

[0068] Step S340, the collision detection module monitors the occurrence of the collision event in real time. If a collision event is detected, a collision signal is generated and the energy recovery rate collision signal is transmitted to the energy distribution module.

[0069] In one embodiment of the present application, in order to monitor the occurrence of a collision event in real time, a collision sensor, a signal processor and a communication module are used. The collision sensor is installed at key positions such as the front and rear bumpers, sides and bottom of the vehicle to detect the impact force on the vehicle. These sensors usually use acceleration sensors or piezoelectric sensors, which can sensitively capture the acceleration changes or pressure changes during a collision. The signal processor is responsible for processing the data collected by the collision sensor to determine whether a collision event has occurred. The communication module is used to transmit the collision signal to the energy distribution module, and can use CAN bus, LIN bus or wireless communication.

[0070] The working process of the collision detection module is as follows: First, the collision sensor collects acceleration or pressure data of various parts of the vehicle in real time at a high frequency (for example, 1000 times per second) to ensure the real-time and accuracy of the data. Then, the signal processor filters, amplifies and digitizes the received raw data to eliminate noise and improve the signal-to-noise ratio. The signal processor determines whether a collision event has occurred based on the processed data. Commonly used judgment methods include acceleration threshold method, shock waveform analysis and multi-sensor fusion. When the acceleration in a certain direction exceeds the preset threshold, or a shock waveform unique to the collision is detected, the signal processor believes that a collision has occurred. Once a collision event is detected, the signal processor immediately generates a collision signal and transmits the collision signal to the energy distribution module through a communication module (such as a CAN bus).

[0071] After receiving the collision signal, the energy distribution module immediately starts the emergency procedure. It quickly evaluates the current working status and remaining power of the supercapacitor and determines the available energy resources. According to the preset safety function priority list, the energy distribution module determines which functions need to be allocated energy first. The common priority order is: the highest priority is the door unlocking system and the emergency warning light; the highest priority is the vehicle positioning system and the interior lighting; the medium priority is the vehicle communication system; the low priority is the entertainment system. The energy distribution module first meets the basic energy requirements of each safety function, and then calculates the weighted coefficient of each function according to the importance and urgency of the safety function to distribute energy. At the same time, the energy distribution module dynamically adjusts the energy distribution according to the real-time monitored energy consumption and remaining energy to ensure that all key functions can obtain sufficient energy. Finally, the calculated energy distribution results are implemented into the system to ensure that each safety function can work properly. After implementation, the energy consumption and system status of each function are continuously monitored to ensure the effectiveness of the energy distribution strategy. If the system status changes, or the actual energy consumption is significantly different from the forecast, the energy distribution is dynamically adjusted according to the real-time data to ensure that all key functions can operate normally in an emergency.

[0072] It can be understood that through the above embodiments, the vehicle redundant power supply method proposed in this application can monitor the occurrence of collision events in real time, and when a collision event is detected, quickly generate a collision signal and transmit it to the energy distribution module. The energy distribution module distributes the energy in the supercapacitor to key safety functions according to a preset priority order to ensure the normal operation of important vehicle systems in emergency situations, thereby improving the safety performance of the vehicle and providing more safety protection for passengers.

[0073] Step S350 , when the energy distribution module receives the collision signal, it distributes energy from the backup capacitor to each functional unit of the vehicle according to a preset priority order.

[0074] In one embodiment of the present application, before allocating energy from the backup capacitor to each functional unit of the vehicle according to a preset priority order, it also includes: obtaining the current stored power of the backup capacitor, the current driving state of the vehicle, and the target power supply time; based on a trained working time prediction model, predicting the working time of each functional unit combination powered by the backup capacitor under the current stored power and the current driving state, so as to obtain the available working time of various functional unit combinations; determining any functional unit combination whose available working time is greater than the target power supply time as a target functional unit combination, and determining each functional unit in the energy recovery rate target functional unit combination as a target functional unit.

[0075] In a specific embodiment of the present application, before distributing energy from the backup capacitor to each functional unit of the vehicle according to a preset priority order, the system first monitors the current stored power of the backup capacitor in real time through a built-in power detection circuit, which collects the voltage and current data of the backup capacitor with high precision and high frequency (for example, 100 times per second) to calculate the current stored power. At the same time, the vehicle's driving parameters, including vehicle speed, acceleration and braking force, are monitored in real time through sensors (such as vehicle speed sensors, acceleration sensors and brake force sensors). The control unit determines the current driving state of the vehicle based on these parameters, such as acceleration, deceleration, constant speed or stillness. The system also presets a target power supply duration. According to the current driving state and safety requirements of the vehicle, for example, after a collision, the target power supply duration can be set to 30 seconds to ensure that key safety functions can operate normally in a short time.

[0076] Next, the system uses a pre-trained neural network model to predict the operating time of each functional unit combination powered by the backup capacitor based on the current stored power and the current driving status. The input of the model includes the current stored power, the current driving status and the energy consumption characteristics of each functional unit, and the output is the operating time of each functional unit combination. The model training data includes the actual operating time of different functional units under different residual energy conditions, and is trained through a large amount of actual driving data to improve the accuracy of the prediction.

[0077] According to the prediction results, the system screens out all functional unit combinations whose available working time is greater than the target power supply time. The specific steps are as follows: the current stored power and the current driving state are input into the working time prediction model, the working time of each functional unit combination is calculated, and then all functional unit combinations whose working time is greater than the target power supply time are screened out to form a candidate target functional unit combination. From the candidate target functional unit combinations, one or more combinations are selected as the final target functional unit combination, and the selection criteria can be a comprehensive consideration of the importance and urgency of the functional units, as well as the overall working time of the combination. For example, assuming that the two target functional unit combinations screened out are combination A (door unlocking system, emergency warning light) and combination B (door unlocking system, emergency warning light, interior lighting), the system can select combination A as the final target functional unit combination because it has a longer working time and contains the highest priority functional unit. In addition, among the candidate target functional unit combinations, selecting one or more combinations as the final target functional unit combination can also be based on user preferences, and this application does not limit its selection method in any way.

[0078] Finally, each functional unit in the target functional unit combination is determined as a target functional unit. The energy allocation module allocates the energy in the backup capacitor to these target functional units based on the determined target functional unit combination to ensure that they can work normally in an emergency. During the allocation process, the system will continuously monitor the energy consumption of each functional unit and the remaining power of the backup capacitor, and dynamically adjust the energy allocation strategy to ensure that all key functional units can obtain sufficient energy.

[0079] It can be understood that through the above embodiments, the present invention can intelligently predict and determine the optimal combination of functional units based on the current stored power of the backup capacitor, the current driving status of the vehicle and the target power supply duration, so as to maximize the utilization of the energy in the backup capacitor in an emergency situation, ensure the normal operation of the vehicle's key safety functions, and improve the safety performance of the vehicle.

[0080] In one embodiment of the present application, energy is allocated from a backup capacitor to each functional unit of a vehicle according to a preset priority order, including: obtaining an importance score and an urgency score of each target functional unit, and a weight ratio of the importance and urgency; calculating the importance score and the urgency score of each target functional unit based on the energy recovery rate weight ratio to obtain a comprehensive score of each target functional unit; sorting each target functional unit of the vehicle according to the comprehensive energy recovery rate score to obtain a power supply priority list; obtaining a basic energy requirement of each target functional unit, the energy recovery rate basic energy requirement being the minimum energy requirement for maintaining the startup of the functional unit; allocating a weighting coefficient to each target table functional unit based on the energy recovery rate power supply priority list, and allocating the current stored power of the backup capacitor to each target functional unit of the vehicle based on the energy recovery rate weighting coefficient.

[0081] In a specific embodiment of the present application, in an emergency, in order to maximize the use of energy in the backup capacitor and ensure the safety of the vehicle and its occupants, the system will allocate energy from the backup capacitor to each functional unit of the vehicle according to a preset priority order. First, the system obtains the importance score and urgency score of each target functional unit, which respectively reflect the importance of the functional unit to vehicle safety and passenger life, and the necessity of immediate activation in an emergency. For example, the importance and urgency scores of the door unlocking system are 0.9 and 0.8 respectively, while the scores of the emergency warning light are 0.85 and 0.9.

[0082] Next, the system will calculate the comprehensive score of each target functional unit based on the preset weight ratio of importance and urgency (for example, the importance weight α is set to 0.6 and the urgency weight 1-α is set to 0.4). This comprehensive score is calculated using the following formula:

[0083] S i =αW i +(1-α)·E i Formula (4)

[0084] Among them, W i and E i are the importance score and urgency score of the i-th functional unit, S i For the comprehensive rating.

[0085] In this embodiment, based on this method, the emergency warning light has the highest comprehensive score of 0.87, followed by the door unlocking system with 0.86, etc.

[0086] Then, the target functional units of the vehicle are sorted according to the comprehensive score to form a power supply priority list. For example, the emergency warning light has the highest priority, followed by the door unlocking system, and so on. The system also obtains the basic energy demand of each functional unit, that is, the minimum energy required to keep the functional unit started. For example, the basic energy demand of the emergency warning light is 15 units.

[0087] Next, the system assigns a weighting coefficient proportional to the comprehensive score to each target functional unit. Assuming the total energy is 100 units, the weighting coefficient of the emergency warning light is set to 1, and the weighting coefficients of other functional units are allocated in proportion to their comprehensive scores. Based on these weighting coefficients and basic energy requirements, the system calculates the energy allocation for each functional unit to ensure that key functional units can obtain sufficient energy support in emergency situations.

[0088] Finally, the system implements energy distribution and continuously monitors the energy consumption of each functional unit and the remaining power of the backup capacitor in order to dynamically adjust the energy distribution strategy to ensure that all key functional units can operate normally in an emergency. This approach not only improves the safety performance of the vehicle in an emergency, but also demonstrates how to improve resource utilization efficiency through intelligent management.

[0089] It can be understood that through the above embodiments, the present invention can intelligently calculate and determine the comprehensive score of each functional unit according to the importance score and urgency score of each target functional unit, as well as the weight ratio of importance and urgency, and then generate a power supply priority list. Based on the priority list, the system can reasonably allocate the energy in the backup capacitor to ensure the normal operation of the vehicle's key safety functions in an emergency and improve the safety performance of the vehicle.

[0090] In one embodiment of the present application, after allocating energy from the backup capacitor to various functional units of the vehicle, it also includes: obtaining user feedback, the energy recovery rate user feedback includes user satisfaction and user-recommended power supply priority; when the energy recovery rate user satisfaction is lower than a preset satisfaction threshold, the energy recovery rate user-recommended power supply priority is used as an input item to optimize the training working time prediction model.

[0091] In a specific embodiment of the present application, after distributing energy from the backup capacitor to various functional units of the vehicle, the system further includes a step of obtaining user feedback to further optimize the energy distribution strategy. The specific implementation steps are as follows:

[0092] The system collects feedback from users through the in-vehicle infotainment system or mobile applications. User feedback includes user satisfaction and the power supply priority suggested by the user. User satisfaction can be obtained through questionnaires, scoring systems or direct input, and the power supply priority suggested by the user can be obtained by the user manually adjusting the priority order of functional units. The system presets a satisfaction threshold, such as 70%. When the user's satisfaction is lower than this preset threshold, the system will consider that the current energy allocation strategy needs to be optimized. For example, if the user is not satisfied with the current energy allocation, it may be because some key functional units have failed to obtain enough energy, or non-critical functional units have occupied too much energy.

[0093] When user satisfaction is lower than the preset threshold, the system uses the power supply priority suggested by the user as a new input item to optimize the training working time prediction model. The specific steps are as follows: The system records detailed information of user feedback, including user satisfaction score and power supply priority suggested by the user, and saves these data in the system database for subsequent model optimization. The collected user feedback data is preprocessed, including data cleaning, feature selection and data standardization. Data cleaning is used to remove outliers and noise, feature selection is used to select the features most relevant to the prediction target, and data standardization is used to convert input data into a format with a mean of 0 and a standard deviation of 1 to improve the efficiency of model training. The power supply priority suggested by the user is used as a new input feature to retrain the working time prediction model. During the model training process, user feedback data is used to adjust the parameters of the model to improve the prediction accuracy of the model and user satisfaction. Common model training methods include gradient descent, random forest and neural network. Use the validation set to evaluate the performance of the optimized model. The validation set contains a part of the data that is not involved in the training, which is used to evaluate the performance of the model on new data. By comparing the model performance before and after optimization, it is ensured that the optimized model has a significant improvement in predicting working time. The optimized model is deployed to the actual vehicle system to replace the original model. The system will use the new model to predict the working hours of each functional unit and dynamically adjust the energy allocation strategy based on the prediction results.

[0094] The system will continue to collect user feedback, regularly evaluate user satisfaction, and continuously optimize the working time prediction model based on the power supply priority suggested by users. Through continuous feedback and optimization, the system can gradually improve the accuracy of energy distribution and user satisfaction.

[0095] It can be understood that through the above embodiments, after allocating energy from the backup capacitor to various functional units of the vehicle, the present invention further optimizes the energy allocation strategy by obtaining user feedback, including user satisfaction and user-suggested power supply priority. When user satisfaction is lower than the preset threshold, the system uses the user-suggested power supply priority as a new input item to optimize the training working time prediction model. This process ensures that the system can continuously improve the energy allocation strategy according to the actual needs and feedback of users, and improve the safety performance and user experience of the vehicle in emergency situations through data collection, preprocessing, model optimization, verification and application.

[0096] Finally, it should be emphasized that the vehicle redundant power supply method, by integrating advanced sensor technology, energy conversion technology, intelligent control strategy and energy distribution algorithm, realizes the efficient recovery and intelligent management of vehicle kinetic energy, which has the effect of improving energy utilization efficiency and enhancing vehicle safety. Specifically:

[0097] In terms of improving energy efficiency, the kinetic energy generated by the vehicle during braking is efficiently converted into electrical energy through the energy converter and stored in the supercapacitor, which not only reduces the energy waste during braking, but also provides an additional source of electricity for the vehicle, which helps to reduce fuel consumption and emissions, and is in line with the development trend of green environmental protection. The vehicle's driving parameters (such as speed, acceleration and braking force) are monitored in real time through sensors, and the working state of the energy converter is dynamically adjusted according to these parameters to optimize the energy recovery efficiency. This energy management method makes energy collection and storage more efficient and reasonable, and adapts to changes in energy demand under different driving conditions.

[0098] In terms of improving vehicle safety, the system monitors the occurrence of collision events in real time through the collision monitoring module. Once a collision event is detected, the system immediately starts the emergency procedure and prioritizes the energy in the supercapacitor to key safety functions, such as the door unlocking system, emergency warning lights, etc., to ensure that these systems can operate normally even when the main power fails, greatly improving the safety performance of the vehicle in emergency situations. The system intelligently allocates energy in the supercapacitor according to the preset priority order and user feedback. By calculating the comprehensive score and basic energy requirements of each functional unit, the system can reasonably allocate energy to ensure that key functional units receive sufficient energy support in emergency situations.

[0099] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the electronic device implements the vehicle redundant power supply method provided in the above-mentioned embodiments.

[0100] Figure 4The structure diagram of the computer system suitable for implementing the electronic device of the embodiment of the present application is shown. It should be noted that: Figure 4 The computer system 400 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0101] like Figure 4 As shown, the computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. In the RAM 403, various programs and data required for system operation are also stored. The CPU 401, ROM 402 and RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0102] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0103] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 409, and / or installed from a removable medium 411. When the computer program is executed by a central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0104] It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0105] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0106] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0107] Another aspect of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor of a computer, causes the computer to execute the vehicle redundant power supply method as described above. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0108] Another aspect of the present application also provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the vehicle redundant power supply method provided in each of the above embodiments.

[0109] The above embodiments are merely illustrative of the principles and effects of the present application, and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A vehicle redundant power supply device, characterized in that: The device comprises: A sensor for monitoring vehicle driving parameters, wherein the vehicle driving parameters include vehicle speed, acceleration and braking force; a control unit connected to the sensor, and configured to determine a vehicle driving state based on vehicle driving parameters, and to determine a current energy recovery rate corresponding to the current vehicle driving state according to a preset energy recovery rate mapping relationship, wherein the energy recovery rate mapping relationship is used to characterize a relationship between the vehicle driving state and the energy recovery rate; an energy converter, for converting kinetic energy generated when the vehicle brakes into electrical energy according to the current energy recovery rate; A backup capacitor connected to the energy converter and the control unit, and used to store the electric energy obtained based on the kinetic energy conversion into the backup capacitor; A collision detection module is used to monitor the occurrence of a collision event and transmit the collision signal generated when the collision event occurs to the energy distribution module; The energy distribution module is connected to the backup capacitor and the collision detection module, and is used to distribute the energy in the backup capacitor to each functional unit of the vehicle according to a preset priority order when a collision signal is detected.

2. The vehicle redundant power supply device according to claim 1, characterized in that: The energy distribution module includes a neural network for predicting the working time of each functional unit combination of the vehicle powered by the backup capacitor under different backup capacitor storage power and different vehicle driving conditions.

3. The vehicle redundant power supply device according to claim 2, characterized in that: The neural network comprises: A data collection module, used to collect working time data of different functional units under different residual energy conditions; Data preprocessing module for data cleaning, feature selection, data standardization and data segmentation; Multilayer perceptron model, including input layer, hidden layer and output layer; A training module is used to train the initial model using a preset loss function and optimizer to obtain a working time prediction model; An evaluation module is used to evaluate the prediction accuracy of the working time prediction model using a test set. If the prediction accuracy is lower than a preset accuracy threshold, the working time prediction model is optimized until its prediction accuracy is greater than or equal to the preset accuracy threshold.

4. The vehicle redundant power supply device according to claim 2, characterized in that: The energy distribution module also includes: A priority sorting module, used to sort the power supply priorities of the functional units according to the prediction results and the preset functional priorities; An energy allocation calculation module is used to allocate energy to functional units with higher power supply priorities in a priority manner; The real-time adjustment module is used to dynamically adjust energy distribution according to the energy consumption and remaining energy monitored in real time.

5. A vehicle redundant power supply method, characterized in that: The method comprises: Monitoring vehicle driving parameters, wherein the vehicle driving parameters include at least vehicle speed, acceleration and braking force; Comparing the vehicle driving parameter with a preset vehicle driving parameter threshold to determine the driving state of the vehicle, and determining a current energy recovery rate that matches the current vehicle driving state according to a preset energy recovery rate mapping relationship, wherein the energy recovery rate mapping relationship is used to characterize the relationship between the vehicle driving state and the energy recovery rate; converting kinetic energy generated when the vehicle brakes into electrical energy according to the current energy recovery rate, and storing the electrical energy in a backup capacitor; Monitoring the occurrence of a collision event, generating a collision signal if a collision event is detected, and transmitting the collision signal to an energy distribution module; When the energy distribution module receives a collision signal, it distributes energy from the backup capacitor to various functional units of the vehicle according to a preset priority order.

6. The vehicle redundant power supply method according to claim 5, characterized in that: Before distributing energy from the backup capacitor to various functional units of the vehicle according to a preset priority order, it also includes: Obtain the current storage capacity of the backup capacitor, the current driving status of the vehicle, and the target power supply duration; Based on the trained working time prediction model, the working time of each functional unit combination powered by the backup capacitor under the current stored power and the current driving state is predicted to obtain the available working time of various functional unit combinations; Any functional unit combination whose available working time is longer than the target power supply time is determined as a target functional unit combination, and each functional unit in the target functional unit combination is determined as a target functional unit.

7. The vehicle redundant power supply method according to claim 6, characterized in that: Energy is distributed from the backup capacitor to various functional units of the vehicle according to a preset priority order, including: Obtain the importance score and urgency score of each target functional unit, as well as the weight ratio of importance and urgency; Calculate the importance score and urgency score of each target functional unit based on the weight proportion to obtain a comprehensive score of each target functional unit; Sorting each target functional unit of the vehicle according to the comprehensive score to obtain a power supply priority list; Obtaining a basic energy requirement of each target functional unit, wherein the basic energy requirement is the minimum energy requirement for maintaining the activation of the functional unit; A weighting coefficient is assigned to each target table functional unit based on the power supply priority list, and the current stored power of the backup capacitor is distributed to each target functional unit of the vehicle based on the weighting coefficient.

8. The vehicle redundant power supply method according to any one of claims 5 to 7, characterized in that: After distributing energy from the backup capacitor to various functional units of the vehicle, it also includes: Obtaining user feedback, wherein the user feedback includes user satisfaction and user-suggested power supply priority; When the user satisfaction is lower than a preset satisfaction threshold, the user-suggested power supply priority is used as an input item to optimize the training working time prediction model.

9. An electronic device, characterized in that: It comprises a processor, a memory and a communication bus; the communication bus is used to connect the processor and the memory; the processor is used to execute a computer program stored in the memory to implement the vehicle redundant power supply method as described in any one of claims 5-8.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and the computer program is used to enable a computer to execute the vehicle redundant power supply method as described in any one of claims 5-8.

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