A method and system for vehicle braking energy recovery

Abstract

This invention provides a method and system for vehicle braking energy recovery. The method includes: when a vehicle is detected to be braking in real time by a preset sensor array, collecting the braking energy generated during braking in real time by a preset supercapacitor inside the vehicle; extracting the corresponding instantaneous peak energy from the braking energy in real time, and generating an energy transfer strategy adapted to the braking energy in real time by a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm; transferring the braking energy to a preset flywheel energy storage module through the energy transfer strategy, and charging the battery pack inside the vehicle through the preset flywheel energy storage module. This invention can smoothly and effectively complete the transfer of braking energy, thereby improving the energy recovery efficiency.

Description

Technical Field

[0001] This invention relates to the field of new energy vehicle technology, and in particular to a method and system for recovering vehicle braking energy. Background Technology

[0002] With the advancement of science and technology and the rapid development of productivity, the production technology of new energy electric vehicles has become increasingly mature, and new energy electric vehicles have become popular in people's daily lives. In order to improve the energy utilization rate of new energy electric vehicles, existing technologies have installed braking energy recovery systems inside new energy electric vehicles to recover braking energy.

[0003] Among these, supercapacitors and flywheel energy storage modules have been developed and applied in existing regenerative braking systems to improve their recovery capabilities.

[0004] Furthermore, when existing technologies detect that a vehicle is braking in real time, they capture the braking energy generated by the vehicle through existing supercapacitors. However, during the energy transfer process, existing supercapacitors cannot smoothly and effectively transfer the braking energy to the flywheel energy storage module for storage, which easily leads to energy loss and reduces the energy recovery efficiency. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a vehicle braking energy recovery method and system to solve the problem that the existing technology cannot smoothly and effectively transfer the energy collected by the supercapacitor in real time to the flywheel energy storage module, which leads to the problem of easy energy loss.

[0006] The first aspect of the present invention proposes:

[0007] A method for recovering braking energy in a vehicle, wherein the method includes:

[0008] When the vehicle is detected to be braking in real time by a preset sensor array, the braking energy generated by the vehicle during braking is collected in real time by a preset supercapacitor inside the vehicle.

[0009] The instantaneous peak energy is extracted in real time from the regenerative braking energy, and an energy transfer strategy adapted to the regenerative braking energy is generated in real time by a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm.

[0010] The energy recovery from braking is transmitted to a preset flywheel energy storage module via the energy transfer strategy, and then the preset flywheel energy storage module charges the battery pack inside the vehicle.

[0011] The beneficial effects of this invention are as follows: a pre-set sensor array can accurately detect whether a vehicle has entered a braking state. Based on this, a pre-set supercapacitor inside the vehicle can collect the braking energy generated during braking in real time. In order to output smoothly and effectively, corresponding analysis is required. Specifically, this invention extracts the instantaneous peak energy in real time and outputs the corresponding energy transmission strategy in real time based on this feature. Finally, the energy can be smoothly and effectively transmitted to the pre-set flywheel energy storage module through this strategy, thereby effectively preventing energy loss and improving the energy recovery efficiency.

[0012] Furthermore, the step of extracting the corresponding instantaneous peak energy from the regenerative braking energy in real time includes:

[0013] When the regenerative braking energy is acquired in real time, the corresponding energy spectrum contained in the regenerative braking energy is detected in real time.

[0014] The energy fluctuation curves contained in the energy spectrum are extracted in real time, and the instantaneous peak energy is extracted in real time based on the energy fluctuation curves.

[0015] Furthermore, the step of extracting the instantaneous peak energy in real time based on the energy fluctuation curve includes:

[0016] When the energy fluctuation curve is acquired in real time, a full scan of the energy fluctuation curve is performed to detect the start point and end point corresponding to the energy fluctuation curve in real time.

[0017] Within the range between the starting point and the ending point, several maximum points and several minimum points sequentially contained in the energy fluctuation curve are detected in real time, and the instantaneous peak energy is extracted in real time based on the several maximum points and several minimum points.

[0018] Furthermore, the step of extracting the instantaneous peak energy in real time based on a plurality of maxima and a plurality of minima includes:

[0019] When a number of maximum points and a number of minimum points are obtained respectively, a corresponding target identifier is added to each of the maximum points and each of the minimum points in turn;

[0020] According to the target identifier, the target difference between two adjacent maximum and minimum points is calculated in real time in the direction from the starting point to the ending point, and each target difference is set as the instantaneous peak energy.

[0021] Furthermore, the step of generating an energy transfer strategy adapted to the regenerative braking energy in real time using a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm includes:

[0022] When the instantaneous peak energy is acquired in real time, the initial control network contained within the preset PID controller is detected in real time.

[0023] A full scan of the initial control network is performed to detect the corresponding initial control nodes in the initial control network in real time. The instantaneous peak energy and each initial control node are then fused using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy.

[0024] Furthermore, the step of fusing the instantaneous peak energy and each initial control node using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy includes:

[0025] When each of the initial control nodes is detected in real time, the initial control parameters contained in each of the initial control nodes are detected in real time.

[0026] The preset fuzzy logic algorithm converts each instantaneous peak energy into a corresponding target control parameter, and outputs the energy transmission strategy according to the target control parameter and the initial control node.

[0027] Furthermore, the step of outputting the energy transfer strategy based on the target control parameters and the initial control node includes:

[0028] When each target control parameter is acquired in real time, the initial control parameter in each initial control node is replaced one by one with each target control parameter to form a corresponding target control network in the PID controller in real time.

[0029] The target control network outputs the corresponding target control strategy in real time, and sets the target control strategy as the energy transmission strategy.

[0030] The second aspect of the present invention proposes:

[0031] A vehicle braking energy recovery system, wherein the system comprises:

[0032] The acquisition module is used to collect the regenerative braking energy generated by the vehicle during braking in real time through a preset supercapacitor inside the vehicle when the vehicle is detected to be in a braking state in real time by a preset sensor array.

[0033] The extraction module is used to extract the corresponding instantaneous peak energy from the regenerative braking energy in real time, and generate an energy transmission strategy adapted to the regenerative braking energy in real time by a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm.

[0034] The transmission module is used to transmit the regenerative braking energy to the preset flywheel energy storage module through the energy transmission strategy, and to charge the battery pack inside the vehicle through the preset flywheel energy storage module.

[0035] Furthermore, the extraction module is specifically used for:

[0036] When the regenerative braking energy is acquired in real time, the corresponding energy spectrum contained in the regenerative braking energy is detected in real time.

[0037] The energy fluctuation curves contained in the energy spectrum are extracted in real time, and the instantaneous peak energy is extracted in real time based on the energy fluctuation curves.

[0038] Furthermore, the extraction module is specifically used for:

[0039] When the energy fluctuation curve is acquired in real time, a full scan of the energy fluctuation curve is performed to detect the start point and end point corresponding to the energy fluctuation curve in real time.

[0040] Within the range between the starting point and the ending point, several maximum points and several minimum points sequentially contained in the energy fluctuation curve are detected in real time, and the instantaneous peak energy is extracted in real time based on the several maximum points and several minimum points.

[0041] Furthermore, the extraction module is specifically used for:

[0042] When a number of maximum points and a number of minimum points are obtained respectively, a corresponding target identifier is added to each of the maximum points and each of the minimum points in turn;

[0043] According to the target identifier, the target difference between two adjacent maximum and minimum points is calculated in real time in the direction from the starting point to the ending point, and each target difference is set as the instantaneous peak energy.

[0044] Furthermore, the extraction module is specifically used for:

[0045] When the instantaneous peak energy is acquired in real time, the initial control network contained within the preset PID controller is detected in real time.

[0046] A full scan of the initial control network is performed to detect the corresponding initial control nodes in the initial control network in real time. The instantaneous peak energy and each initial control node are then fused using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy.

[0047] Furthermore, the extraction module is specifically used for:

[0048] When each of the initial control nodes is detected in real time, the initial control parameters contained in each of the initial control nodes are detected in real time.

[0049] The preset fuzzy logic algorithm converts each instantaneous peak energy into a corresponding target control parameter, and outputs the energy transmission strategy according to the target control parameter and the initial control node.

[0050] Furthermore, the extraction module is specifically used for:

[0051] When each target control parameter is acquired in real time, the initial control parameter in each initial control node is replaced one by one with each target control parameter to form a corresponding target control network in the PID controller in real time.

[0052] The target control network outputs the corresponding target control strategy in real time, and sets the target control strategy as the energy transmission strategy.

[0053] The third aspect of the present invention proposes:

[0054] A computer includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the vehicle braking energy recovery method as described above.

[0055] The fourth aspect of the present invention proposes:

[0056] A readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the vehicle braking energy recovery method as described above.

[0057] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0058] Figure 1 A flowchart of a vehicle braking energy recovery method provided in the first embodiment of the present invention;

[0059] Figure 2This is a structural block diagram of a vehicle braking energy recovery system provided in the third embodiment of the present invention.

[0060] The following detailed description, in conjunction with the accompanying drawings, will further illustrate the present invention. Detailed Implementation

[0061] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0062] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0063] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0064] Please see Figure 1 The figure shows a vehicle braking energy recovery method provided in the first embodiment of the present invention. The vehicle braking energy recovery method provided in this embodiment can smoothly and effectively complete the transmission of braking energy recovery, thereby improving the energy recovery efficiency.

[0065] Specifically, this embodiment provides:

[0066] A method for recovering braking energy in a vehicle specifically includes the following steps:

[0067] Step S10: When the vehicle is detected to be in a braking state in real time by a preset sensor array, the braking recovery energy generated by the vehicle during the braking process is collected in real time by a preset supercapacitor inside the vehicle.

[0068] It should be noted that existing new energy electric vehicles all have the function of regenerative braking, that is, they are all equipped with a regenerative braking system. This system includes a supercapacitor and a flywheel energy storage module to enhance the recovery capacity of the system. Based on this, when the vehicle is detected to be in motion, the vehicle's driving conditions are monitored in real time through pre-set speed sensors and acceleration sensors. When the vehicle is detected to be braking, the supercapacitor is immediately activated, and the regenerative braking energy generated during the braking process is collected in real time for subsequent processing.

[0069] Step S20: Extract the corresponding instantaneous peak energy from the regenerative braking energy in real time, and generate an energy transfer strategy adapted to the regenerative braking energy in real time by a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm.

[0070] It should be noted that after the required regenerative braking energy is collected in real time through the supercapacitor, in order to smoothly and effectively complete the transmission of the current regenerative braking energy, it is necessary to analyze the current regenerative braking energy in real time to determine the appropriate transmission strategy. Specifically, in order to accurately complete the subsequent transmission, this invention will detect the instantaneous peak energy contained in the current regenerative braking energy in real time, and can immediately perform logical processing on the current instantaneous peak energy through the existing PID controller and fuzzy logic algorithm, that is, analyze the characteristics of the current regenerative braking energy in real time, and formulate an appropriate energy transmission strategy for subsequent processing.

[0071] Step S30: The regenerative braking energy is transmitted to the preset flywheel energy storage module through the energy transmission strategy, and the battery pack inside the vehicle is charged through the preset flywheel energy storage module.

[0072] It should be noted that after obtaining the required energy transfer strategy in real time through the above steps, the current regenerative braking energy can be immediately transferred to the flywheel energy storage module according to the transfer method of the energy transfer strategy. Based on this, the flywheel energy storage module can charge the battery pack inside the vehicle, thereby effectively recovering the braking energy and improving the recovery efficiency.

[0073] Second Embodiment

[0074] Furthermore, the step of extracting the corresponding instantaneous peak energy from the regenerative braking energy in real time includes:

[0075] When the regenerative braking energy is acquired in real time, the corresponding energy spectrum contained in the regenerative braking energy is detected in real time.

[0076] The energy fluctuation curves contained in the energy spectrum are extracted in real time, and the instantaneous peak energy is extracted in real time based on the energy fluctuation curves.

[0077] It should be noted that, in order to accurately and effectively extract the required instantaneous peak energy from the aforementioned regenerative braking energy in real time, it is necessary to accurately obtain the information contained in the current regenerative braking energy. It should be pointed out that existing regenerative braking energy will generate corresponding spectra during real-time recovery. Based on this, the present invention can detect the corresponding energy spectra in the current regenerative braking energy in real time. It should be noted that the spectra can intuitively reflect the energy recovery situation, that is, the spectra contains the energy fluctuation curves generated by the regenerative braking energy during the recovery process, and can be used for subsequent analysis to facilitate subsequent processing.

[0078] Furthermore, the step of extracting the instantaneous peak energy in real time based on the energy fluctuation curve includes:

[0079] When the energy fluctuation curve is acquired in real time, a full scan of the energy fluctuation curve is performed to detect the start point and end point corresponding to the energy fluctuation curve in real time.

[0080] Within the range between the starting point and the ending point, several maximum points and several minimum points sequentially contained in the energy fluctuation curve are detected in real time, and the instantaneous peak energy is extracted in real time based on the several maximum points and several minimum points.

[0081] It should be noted that existing curves will form maximum and minimum points during the generation process. Similarly, several maximum and minimum points also appear sequentially within the energy fluctuation curve mentioned above. It should be pointed out that these maximum and minimum points can reflect the energy fluctuation in real time, that is, they can reflect the magnitude of the braking energy during the real-time recovery process. Therefore, by analyzing the extreme points, the instantaneous peak energy generated in real time can be determined, and the required energy transmission strategy can be generated in real time based on the instantaneous peak energy to complete the energy transmission for subsequent processing.

[0082] Furthermore, the step of extracting the instantaneous peak energy in real time based on a plurality of maxima and a plurality of minima includes:

[0083] When a number of maximum points and a number of minimum points are obtained respectively, a corresponding target identifier is added to each of the maximum points and each of the minimum points in turn;

[0084] According to the target identifier, the target difference between two adjacent maximum and minimum points is calculated in real time in the direction from the starting point to the ending point, and each target difference is set as the instantaneous peak energy.

[0085] It should be noted that after obtaining several maxima and minima through the above steps, subsequent extraction processing can be performed. Specifically, to facilitate subsequent differentiation, this invention will add corresponding target identifiers to each current maxima and minima in sequence, and immediately calculate the target difference between adjacent maxima and minima in the direction from the starting point to the ending point, based on each target identifier. That is, subtract the current minima from the current maxima, thereby calculating the peak energy corresponding to a certain moment, which is much greater than the energy corresponding to other moments. Based on this, this invention can set the energy corresponding to each current target difference as the instantaneous peak energy and perform subsequent analysis for subsequent processing.

[0086] Furthermore, the step of generating an energy transfer strategy adapted to the regenerative braking energy in real time using a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm includes:

[0087] When the instantaneous peak energy is acquired in real time, the initial control network contained within the preset PID controller is detected in real time.

[0088] A full scan of the initial control network is performed to detect the corresponding initial control nodes in the initial control network in real time. The instantaneous peak energy and each initial control node are then fused using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy.

[0089] It should be noted that after acquiring the required instantaneous peak energy in real time through the above steps, the PID controller and fuzzy logic algorithm will be immediately activated. It should be pointed out that existing PID controllers all have corresponding control networks internally. Based on this, in order to complete subsequent control, this invention will perform a full scan of the current initial control network and simultaneously scan out several initial control nodes contained within it. Then, by using the instantaneous peak energy to improve each initial control node, a target control network adapted to the current vehicle can be finally formed, thereby outputting the corresponding control strategy for subsequent processing.

[0090] Furthermore, the step of fusing the instantaneous peak energy and each initial control node using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy includes:

[0091] When each of the initial control nodes is detected in real time, the initial control parameters contained in each of the initial control nodes are detected in real time.

[0092] The preset fuzzy logic algorithm converts each instantaneous peak energy into a corresponding target control parameter, and outputs the energy transmission strategy according to the target control parameter and the initial control node.

[0093] It should be noted that after detecting each initial control node in real time through the above steps, since existing technologies set corresponding control parameters for each control node, this invention can detect the initial control parameters contained in each initial control node in real time. Based on this, the current instantaneous peak energy is immediately converted in real time using the above fuzzy logic algorithm to convert it into target control parameters that can be recognized by the controller for subsequent processing. It should be noted that during the real-time conversion process, the extreme values ​​contained in the current instantaneous peak energy are extracted in real time through the sliding window in the aforementioned fuzzy logic algorithm. Based on this, the current fuzzy logic algorithm can immediately perform median filtering and fuzzy normalization processing on the current extreme values ​​in sequence, thereby mapping the current extreme values ​​to the required membership values. Based on this, the existing PWM regulator performs real-time decoding processing on the current membership values ​​and can map the current membership values ​​to the corresponding register values ​​in real time. Finally, the control parameters corresponding to the register values ​​are matched in real time in the preset control parameter table, and the control parameters are finally set as the required target control parameters. Based on this, the target control parameters are transmitted to the internal part of the controller for subsequent processing.

[0094] Furthermore, the step of outputting the energy transfer strategy based on the target control parameters and the initial control node includes:

[0095] When each target control parameter is acquired in real time, the initial control parameter in each initial control node is replaced one by one with each target control parameter to form a corresponding target control network in the PID controller in real time.

[0096] The target control network outputs the corresponding target control strategy in real time, and sets the target control strategy as the energy transmission strategy.

[0097] It should be noted that after obtaining the required initial control nodes and target control parameters through the above steps, the PID controller can be adaptively adjusted. Specifically, this invention immediately replaces the initial control parameters in each initial control node with the corresponding target control parameters, thereby forming the final target control network in real time within the current PID controller. This target control network then generates the corresponding target control strategy in real time based on the control sequence of each target control node. Ultimately, the current target control strategy is set as the energy transfer strategy for subsequent energy transfer, enabling smooth and effective recovery of braking energy. This process effectively avoids braking energy loss and ensures energy integrity, thus improving energy recovery efficiency. It should be noted that the target control network provided by this invention is a CAN network, and this target control network is electrically connected to components inside the vehicle, such as the vehicle controller, inverter, battery pack, and motor controller. Based on this, several target control nodes are formed within the current target control network. Each target control node controls a key component; for example, one target control node controls the vehicle controller, and another controls the inverter. This target control network connects the various important components inside the vehicle into a unified whole. Based on this, the invention adds a corresponding target identifier to each target control node according to the existing energy transmission inertia, thus setting the transmission order between each target control node in real time. Based on this, the braking energy collected in real time flows between these components according to the order of the target identifiers, ultimately transmitting the collected braking energy to the battery pack, effectively replenishing the battery pack. This improves the vehicle's driving range and enhances the user experience.

[0098] Please see Figure 2The third embodiment of the present invention provides:

[0099] A vehicle braking energy recovery system, wherein the system comprises:

[0100] The acquisition module is used to collect the regenerative braking energy generated by the vehicle during braking in real time through a preset supercapacitor inside the vehicle when the vehicle is detected to be in a braking state in real time by a preset sensor array.

[0101] The extraction module is used to extract the corresponding instantaneous peak energy from the regenerative braking energy in real time, and generate an energy transmission strategy adapted to the regenerative braking energy in real time by a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm.

[0102] The transmission module is used to transmit the regenerative braking energy to the preset flywheel energy storage module through the energy transmission strategy, and to charge the battery pack inside the vehicle through the preset flywheel energy storage module.

[0103] Furthermore, the extraction module is specifically used for:

[0104] When the regenerative braking energy is acquired in real time, the corresponding energy spectrum contained in the regenerative braking energy is detected in real time.

[0105] The energy fluctuation curves contained in the energy spectrum are extracted in real time, and the instantaneous peak energy is extracted in real time based on the energy fluctuation curves.

[0106] Furthermore, the extraction module is specifically used for:

[0107] When the energy fluctuation curve is acquired in real time, a full scan of the energy fluctuation curve is performed to detect the start point and end point corresponding to the energy fluctuation curve in real time.

[0108] Within the range between the starting point and the ending point, several maximum points and several minimum points sequentially contained in the energy fluctuation curve are detected in real time, and the instantaneous peak energy is extracted in real time based on the several maximum points and several minimum points.

[0109] Furthermore, the extraction module is specifically used for:

[0110] When a number of maximum points and a number of minimum points are obtained respectively, a corresponding target identifier is added to each of the maximum points and each of the minimum points in turn;

[0111] According to the target identifier, the target difference between two adjacent maximum and minimum points is calculated in real time in the direction from the starting point to the ending point, and each target difference is set as the instantaneous peak energy.

[0112] Furthermore, the extraction module is specifically used for:

[0113] When the instantaneous peak energy is acquired in real time, the initial control network contained within the preset PID controller is detected in real time.

[0114] A full scan of the initial control network is performed to detect the corresponding initial control nodes in the initial control network in real time. The instantaneous peak energy and each initial control node are then fused using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy.

[0115] Furthermore, the extraction module is specifically used for:

[0116] When each of the initial control nodes is detected in real time, the initial control parameters contained in each of the initial control nodes are detected in real time.

[0117] The preset fuzzy logic algorithm converts each instantaneous peak energy into a corresponding target control parameter, and outputs the energy transmission strategy according to the target control parameter and the initial control node.

[0118] Furthermore, the extraction module is specifically used for:

[0119] When each target control parameter is acquired in real time, the initial control parameter in each initial control node is replaced one by one with each target control parameter to form a corresponding target control network in the PID controller in real time.

[0120] The target control network outputs the corresponding target control strategy in real time, and sets the target control strategy as the energy transmission strategy.

[0121] The fourth embodiment of the present invention provides a computer, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the vehicle braking energy recovery method as described above.

[0122] The fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the vehicle braking energy recovery method as described above.

[0123] In summary, the vehicle braking energy recovery method and system provided in the above embodiments of the present invention can smoothly and effectively complete the recovery of braking energy, thereby improving the energy recovery efficiency.

[0124] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0125] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0126] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0127] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0128] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0129] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for recovering braking energy in a vehicle, characterized in that, The method includes: When the vehicle is detected to be braking in real time by a preset sensor array, the braking energy generated by the vehicle during braking is collected in real time by a preset supercapacitor inside the vehicle. The instantaneous peak energy is extracted in real time from the regenerative braking energy, and an energy transfer strategy adapted to the regenerative braking energy is generated in real time by a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm. The energy recovery from braking is transmitted to a preset flywheel energy storage module through the energy transmission strategy, and the battery pack inside the vehicle is charged through the preset flywheel energy storage module. The step of extracting the corresponding instantaneous peak energy from the regenerative braking energy in real time includes: When the regenerative braking energy is acquired in real time, the corresponding energy spectrum contained in the regenerative braking energy is detected in real time. The energy fluctuation curves contained in the energy spectrum are extracted in real time, and the instantaneous peak energy is extracted in real time based on the energy fluctuation curves. The step of extracting the instantaneous peak energy in real time based on the energy fluctuation curve includes: When the energy fluctuation curve is acquired in real time, a full scan of the energy fluctuation curve is performed to detect the start point and end point corresponding to the energy fluctuation curve in real time. Within the range between the starting point and the ending point, several maximum points and several minimum points successively contained in the energy fluctuation curve are detected in real time, and the instantaneous peak energy is extracted in real time based on the several maximum points and several minimum points. The step of extracting the instantaneous peak energy in real time based on a plurality of maximum points and a plurality of minimum points includes: When a number of maximum points and a number of minimum points are obtained respectively, a corresponding target identifier is added to each of the maximum points and each of the minimum points in turn; According to the target identifier, the target difference between two adjacent maximum and minimum points is calculated in real time in the direction from the starting point to the ending point, and each target difference is set as the instantaneous peak energy.

2. The vehicle braking energy recovery method according to claim 1, characterized in that: The step of generating an energy transfer strategy adapted to the regenerative braking energy in real time using a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm includes: When the instantaneous peak energy is acquired in real time, the initial control network contained within the preset PID controller is detected in real time. A full scan of the initial control network is performed to detect the corresponding initial control nodes in the initial control network in real time. The instantaneous peak energy and each initial control node are then fused using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy.

3. The vehicle braking energy recovery method according to claim 2, characterized in that: The step of fusing the instantaneous peak energy and each initial control node using the preset fuzzy logic algorithm to output the corresponding energy transmission strategy includes: When each of the initial control nodes is detected in real time, the initial control parameters contained in each of the initial control nodes are detected in real time. The preset fuzzy logic algorithm converts each instantaneous peak energy into a corresponding target control parameter, and outputs the energy transmission strategy according to the target control parameter and the initial control node.

4. The vehicle braking energy recovery method according to claim 3, characterized in that: The step of outputting the energy transfer strategy based on the target control parameters and the corresponding initial control node includes: When each target control parameter is acquired in real time, the initial control parameter in each initial control node is replaced one by one with each target control parameter to form a corresponding target control network in the PID controller in real time. The target control network outputs the corresponding target control strategy in real time, and sets the target control strategy as the energy transmission strategy.

5. A vehicle braking energy recovery system, characterized in that, For implementing the vehicle braking energy recovery method as described in any one of claims 1 to 4, the system comprises: The acquisition module is used to collect the regenerative braking energy generated by the vehicle during braking in real time through a preset supercapacitor inside the vehicle when the vehicle is detected to be in a braking state in real time by a preset sensor array. The extraction module is used to extract the corresponding instantaneous peak energy from the regenerative braking energy in real time, and generate an energy transmission strategy adapted to the regenerative braking energy in real time by a preset PID controller based on the instantaneous peak energy and a preset fuzzy logic algorithm. The transmission module is used to transmit the regenerative braking energy to the preset flywheel energy storage module through the energy transmission strategy, and to charge the battery pack inside the vehicle through the preset flywheel energy storage module.

6. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the vehicle braking energy recovery method as described in any one of claims 1 to 4.

7. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the vehicle braking energy recovery method as described in any one of claims 1 to 4.

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