A method, device, medium and equipment for braking energy recovery of an electric motorcycle

Abstract

The present application relates to the technical field of motorcycle energy recovery, and particularly relates to a braking energy recovery method, device, medium and equipment for an electric motorcycle. In the process of driving the electric motorcycle, angle data collected by an angle sensor installed on a brake hand lever is acquired. According to the angle data, a mechanical braking torque is determined. According to the mechanical braking torque, a motor current, a motor voltage and a motor speed of the electric motorcycle at the current time, a PWM control signal is determined through a preset motor braking optimization controller. According to the PWM control signal, a motor braking torque is determined, and braking energy recovery is performed according to the motor braking torque. According to the motor braking torque and the mechanical braking torque, braking control is performed on the electric motorcycle. In combination with the existing electric motorcycle braking system structure, the PWM control signal is determined through the motor braking optimization controller to realize motor braking, and is fully matched with the original mechanical braking to maximize braking energy feedback.

Description

Technical Field

[0001] This specification relates to the field of motorcycle energy recovery technology, and in particular to a method, device, medium and equipment for recovering braking energy of an electric motorcycle. Background Technology

[0002] Driven by the rapid development of new energy technologies and the increasing global awareness of environmental protection, electric motorcycles have become an important part of the automotive industry. In the electric motorcycle sector, energy recovery technology is key to improving range and riding experience.

[0003] Currently, most electric motorcycles rely on the brake lever switch signal (0-1 action detection), combined with the current vehicle speed and a MAP (Motor Braking Efficiency Map), to calculate the optimal regenerative braking torque of the motor through a lookup table to brake the electric motorcycle. However, this method has two main drawbacks: First, the coordination between the motor's regenerative braking torque and mechanical braking usually depends on empirical values ​​(i.e., lookup tables). Fixed "empirical values" cannot intelligently adapt to all situations, resulting in suboptimal energy recovery efficiency and difficulty in achieving optimal control of braking energy feedback. Second, the intervention process of motor regenerative braking is complex to debug, which can easily lead to a jerky feeling during riding, affecting riding comfort.

[0004] Therefore, this specification provides a method, apparatus, medium, and equipment for recovering braking energy of electric motorcycles. Summary of the Invention

[0005] This specification provides a method, apparatus, medium, and equipment for recovering braking energy of an electric motorcycle to solve the aforementioned problems existing in the prior art.

[0006] The following technical solution is adopted in this specification: This manual provides a method for regenerative braking of electric motorcycles, including: S1. During the operation of the electric motorcycle, acquire angle data collected by the angle sensor installed on the brake handbrake; S2. Determine the mechanical braking torque based on the angle data; S3. Based on the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle, determine the PWM control signal through a preset motor braking optimization controller; S4. Determine the motor torque based on the PWM control signal; S5. Based on the electric motor's driving torque and the mechanical braking torque, brake control is performed on the electric motorcycle, and braking energy is recovered based on the electric motor's driving torque.

[0007] Based on the aforementioned technical means, this solution combines the existing electric motorcycle braking system structure with a motor braking optimization controller to determine the PWM control signal for motor braking. This fully coordinates with the existing mechanical braking system, maximizing braking energy feedback through the optimal PWM control signal. Simultaneously, it ensures smooth coordination between the motor braking and the existing mechanical braking system, improving ride comfort.

[0008] Furthermore, the calculation expression for the mechanical braking torque mentioned in S2 is as follows:

[0009] in, The mechanical braking torque; This is the preset braking coefficient; The angle data is as described.

[0010] Furthermore, S3 specifically includes: The desired speed change is determined based on the mechanical braking torque and the preset change time period; and the actual speed change is determined based on the current motor speed of the electric motorcycle and the motor speed of the previous moment. The desired speed change, the actual speed change, the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle are input into a preset motor braking optimization controller. The motor braking optimization controller is then run to obtain the PWM control signal output by the motor braking optimization controller.

[0011] Furthermore, the expression for calculating the desired change in rotational speed is as follows:

[0012] in, The desired change in rotational speed; The preset time period of change; The mechanical braking torque; This is the preset moment of inertia.

[0013] Furthermore, the expression for the motor braking optimization controller is:

[0014]

[0015]

[0016]

[0017]

[0018] in, , , , , , , , These represent the motor current, motor voltage, motor speed, PWM control signal, mechanical braking torque, input power, motor torque, and output power of the electric motorcycle at time k in the future, where k is an integer not less than 0; when k is 0, it represents the current time. For resistance, The electromotive force constant is . For inductance, The torque constant is The coefficient of friction of the motor. It is the moment of inertia; These are the preset transfer function constants; The preset time interval is used to characterize the time length between time k and time (k+1). , These are the preset power control weights and speed change control weights, respectively; n is the number of moments predicted by the motor braking optimization controller, and k≤n.

[0019] Furthermore, it also includes step S6: The PWM control signal and the mechanical braking torque are input into a preset electric motorcycle model to obtain the motor current, motor voltage, and motor speed at the next moment output by the electric motorcycle model. As the angle sensor continues to collect new angle data, the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment are sent to the motor braking optimization controller so that the motor braking optimization controller can continue to solve for new PWM control signals.

[0020] Based on the above technical means, after braking the electric motorcycle according to the PWM control signal and mechanical braking torque, the motor current, motor voltage, and motor speed predicted by the PWM control signal and mechanical braking torque can be calculated through the electric vehicle model. These data of the next moment are then fed back to the motor braking optimization controller to achieve rolling optimization, so that the PWM control signal can be accurately calculated in the next moment to maximize the braking energy feedback.

[0021] Furthermore, the expression for the electric motorcycle model is:

[0022] in, , , These are the motor current, motor speed, and motor voltage output by the electric motorcycle model at the next moment, respectively.

[0023] This manual provides a regenerative braking device for an electric motorcycle, comprising: The acquisition module is used to acquire angle data collected by the angle sensor installed on the brake handbrake during the operation of the electric motorcycle; The first determining module is used to determine the mechanical braking torque based on the angle data; The second determining module is used to determine the PWM control signal based on the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle at the current moment, through a preset motor braking optimization controller; The third determining module is used to determine the motor torque based on the PWM control signal; The braking module is used to control the braking of the electric motorcycle based on the motor's driving torque and the mechanical braking torque, and to recover braking energy based on the motor's driving torque.

[0024] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for recovering braking energy of an electric motorcycle.

[0025] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for regenerating braking energy of an electric motorcycle.

[0026] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects: This solution integrates with the existing electric motorcycle braking system structure. It uses a motor braking optimization controller to determine the PWM control signal for motor braking, and fully coordinates with the existing mechanical braking system. Through the optimal PWM control signal, it maximizes braking energy feedback. Simultaneously, it ensures smooth coordination between the motor braking and the existing mechanical braking system, improving ride comfort. Attached Figure Description

[0027] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings: Figure 1 A schematic flowchart illustrating a method for recovering braking energy of an electric motorcycle, provided as an embodiment of this specification. Figure 2This specification provides a flowchart of a braking energy recovery process. Figure 3 This is a schematic diagram of a braking energy recovery device for an electric motorcycle provided in this specification. Figure 4 This specification provides a corresponding Figure 1 A schematic diagram of the structure of an electronic device. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.

[0029] In embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0030] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0031] Figure 1 A flowchart illustrating a method for recovering braking energy of an electric motorcycle, provided in this embodiment of the specification, includes the following steps: S1: During the operation of the electric motorcycle, acquire angle data collected by the angle sensor installed on the brake handbrake.

[0032] This specification describes the process of regenerative braking of an electric motorcycle. In the embodiments described herein, the regenerative braking process can be executed by a brake controller. However, this specification does not limit the type of device or platform used to perform the regenerative braking process; for example, a personal computer, mobile terminal, vehicle infotainment system, or an onboard (or built-in) Electronic Control Unit (ECU) can also be used. For ease of description, the following description uses a brake controller as an example to illustrate the regenerative braking method for an electric motorcycle.

[0033] In one or more embodiments of this specification, an angle sensor is installed on the handbrake of the electric motorcycle to detect the angle of rotation of the handbrake when the driver attempts to turn it. Therefore, during the operation of the electric motorcycle, the braking system can acquire angle data collected by the angle sensor to determine the driver's intention to slow down.

[0034] S2: Determine the mechanical braking torque based on the angle data. S3: Based on the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle, a PWM control signal is determined through a preset motor braking optimization controller.

[0035] In one or more embodiments of this specification, the brake controller can determine the mechanical braking torque of the motorcycle's mechanical braking based on angle data.

[0036] The expression for calculating mechanical braking torque is:

[0037] in, It is the mechanical braking torque. This is the preset braking coefficient. This is angle data.

[0038] Then, the brake controller determines the PWM control signal based on the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle, through a preset motor braking optimization controller.

[0039] Specifically, the brake controller determines the desired speed change based on the mechanical braking torque and a preset change time period. It also determines the actual speed change based on the current motor speed of the electric motorcycle and the motor speed of the previous moment.

[0040] The expression for calculating the desired change in rotational speed is:

[0041] in, This represents the desired change in rotational speed. The preset time period is the length of time between the current moment and the previous moment. It is the mechanical braking torque. This is the preset moment of inertia.

[0042] Subsequently, the brake controller inputs the desired speed change, actual speed change, mechanical braking torque, and the current motor current, voltage, and speed of the electric motorcycle into a preset motor brake optimization controller. The motor brake optimization controller then runs, generating a PWM control signal output by the controller. PWM stands for Pulse Width Modulation, and it can be used to control the motor. Publicly available methods exist for determining the motor's braking torque based on PWM.

[0043] The expression for the motor braking optimization controller is:

[0044]

[0045]

[0046]

[0047]

[0048] The aforementioned motor braking optimization controller can be used as a model predictive controller (MPC). By running the motor braking optimization controller, the objective function is solved, the optimal solution (PWM) at multiple future time points is predicted, and the final output result of the motor braking optimization controller is determined from the optimal solutions at multiple future time points.

[0049] in, , , , , , , , These represent the predicted motor current, motor voltage, motor speed, PWM control signal, mechanical braking torque, input power, motor torque, and output power of the electric motorcycle at time k, as determined by the motor braking optimization controller. k is an integer not less than 0. When k is 0, it represents the current time, i.e., the initial time when the motor braking optimization controller begins prediction. The motor-related parameters in the motor braking optimization controller include... For resistance, The electromotive force constant is . For inductance, The torque constant is The coefficient of friction of the motor. Let be the moment of inertia. These are the preset transfer function constants. The preset time interval is used to characterize the time length between time k and time (k+1), as described above. The time length is the same. , These are the preset power control weights and speed change control weights, respectively. By adjusting these weights, the motor braking energy feedback and the occupant comfort resulting from deceleration smoothness control during braking can be balanced and optimized. 'n' represents the number of prediction moments by the motor braking optimization controller, characterizing the time step of the internal prediction by the controller, where k ≤ n.

[0050] S4: Determine the motor torque based on the PWM control signal.

[0051] S5: Based on the electric motor's driving torque and the mechanical braking torque, brake control is performed on the electric motorcycle, and braking energy is recovered based on the electric motor's driving torque.

[0052] In one or more embodiments of this specification, the braking controller may further determine the motor braking torque of the motor based on the PWM control signal determined by the motor braking optimization controller.

[0053] This system controls the braking of the electric motorcycle through the motor's driving torque and mechanical braking torque, and recovers braking energy based on the motor's driving torque. This energy recovery is an inherent function of the motor itself. The braking current generated by the motor's driving torque flows from the motor to the battery, effectively charging it. Thus, braking energy is recovered and stored through the motor's driving torque. Furthermore, a motor braking optimization controller outputs a PWM control signal that maximizes braking energy recovery, causing the motor to operate according to the corresponding driving torque, thereby maximizing braking energy recovery.

[0054] based on Figure 1 The described electric motorcycle braking energy recovery method, combined with the existing electric motorcycle braking system structure, uses a motor braking optimization controller to determine the PWM control signal to achieve motor braking, and fully coordinates with the original mechanical braking to maximize braking energy feedback. Simultaneously, it ensures smooth coordination between the motor braking and the existing mechanical braking system, improving riding comfort.

[0055] Furthermore, in one or more embodiments of this specification, step S6 is also included: the brake controller can input the PWM control signal and the mechanical braking torque into a preset electric motorcycle model to obtain the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment. For ease of subsequent description, the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment are referred to as the system state value. Furthermore, if the angle sensor continues to collect new angle data, the brake controller sends the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment to the motor brake optimization controller. Simultaneously, the brake controller determines a new mechanical braking torque based on the collected new angle data. Based on the new mechanical braking torque and the aforementioned system state value (i.e., the motor current, motor voltage, and motor speed at this time, equivalent to the current motor current, motor voltage, and motor speed), the motor brake optimization controller continues to solve for a new PWM control signal.

[0056] After braking the electric motorcycle based on the PWM control signal and mechanical braking torque, the electric vehicle model can continue to calculate the motor current, motor voltage, and motor speed predicted by the PWM control signal and mechanical braking torque for the next moment. This data for the next moment is then fed back to the motor braking optimization controller to achieve rolling optimization, so that the PWM control signal can be accurately calculated for the next moment, maximizing the braking energy feedback.

[0057] The expression for the electric motorcycle model is:

[0058] in, , , These are the motor current, motor speed, and motor voltage output by the electric motorcycle model at the next moment.

[0059] Figure 2 This document provides a flowchart of a braking energy recovery process. As shown, the brake controller determines the mechanical braking torque using angle data. This mechanical braking torque is then input to the motor braking optimization controller to determine the PWM control signal. The PWM control signal determines the motor braking torque, which, in conjunction with the mechanical braking torque, controls the braking of the electric motorcycle. The motor current, motor voltage, and motor speed are then fed back to the motor braking optimization controller using an electric motorcycle model.

[0060] Based on one or more embodiments of this specification, a method for recovering braking energy of an electric motorcycle is provided. Following the same logic, this specification also provides a corresponding device for recovering braking energy of an electric motorcycle, such as… Figure 3 As shown.

[0061] Figure 3 This specification provides a schematic diagram of a regenerative braking device for an electric motorcycle, specifically including: The acquisition module 300 is used to acquire angle data collected by the angle sensor installed on the brake handbrake during the operation of the electric motorcycle. The first determining module 302 is used to determine the mechanical braking torque based on the angle data; The second determining module 304 is used to determine the PWM control signal based on the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle at the current moment, through a preset motor braking optimization controller. The third determining module 306 is used to determine the motor torque based on the PWM control signal; The braking module 308 is used to control the braking of the electric motorcycle according to the motor torque and the mechanical braking torque, and to recover braking energy according to the motor torque.

[0062] Furthermore, the calculation expression for the mechanical braking torque in the first determining module 302 is as follows:

[0063] in, The mechanical braking torque; This is the preset braking coefficient; The angle data is as described.

[0064] Furthermore, the second determining module 304 is used to determine the desired speed change based on the mechanical braking torque and the preset change time period; and to determine the actual speed change based on the motor speed of the electric motorcycle at the current moment and the motor speed at the previous moment. The desired speed change, the actual speed change, the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle are input into a preset motor braking optimization controller. The motor braking optimization controller is then run to obtain the PWM control signal output by the motor braking optimization controller.

[0065] Furthermore, the calculation expression for the desired change in rotational speed in the second determining module 304 is as follows:

[0066] in, The desired change in rotational speed; The preset time period of change; The mechanical braking torque; This is the preset moment of inertia.

[0067] Furthermore, the expression for the motor braking optimization controller in the second determining module 304 is:

[0068]

[0069]

[0070]

[0071]

[0072] in, , , , , , , , These represent the motor current, motor voltage, motor speed, PWM control signal, mechanical braking torque, input power, motor torque, and output power of the electric motorcycle at time k in the future, where k is an integer not less than 0; when k is 0, it represents the current time. For resistance, The electromotive force constant is . For inductance, The torque constant is The coefficient of friction of the motor. It is the moment of inertia; These are the preset transfer function constants; The preset time interval is used to characterize the time length between time k and time (k+1). , These are the preset power control weights and speed change control weights, respectively; n is the number of moments predicted by the motor braking optimization controller, and k≤n.

[0073] Furthermore, the device also includes an optimization module 310, which is used to input the PWM control signal and the mechanical braking torque into a preset electric motorcycle model to obtain the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment. As the angle sensor continues to collect new angle data, the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment are sent to the motor braking optimization controller so that the motor braking optimization controller can continue to solve for new PWM control signals.

[0074] Furthermore, the expression for the electric motorcycle model in the optimization module 310 is:

[0075] in, , , These are the motor current, motor speed, and motor voltage output by the electric motorcycle model at the next moment, respectively.

[0076] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 A method for recovering braking energy in electric motorcycles is provided.

[0077] This instruction manual also provides Figure 4 The diagram shows a schematic structural representation of the electronic device. Figure 4 As shown, at the hardware level, this electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above. Figure 1 A method for recovering braking energy in electric motorcycles is provided.

[0078] Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0079] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0080] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0081] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0082] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0083] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0084] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0085] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0086] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0087] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0088] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0089] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0090] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0091] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0092] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0093] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0094] The above description is merely an embodiment of this specification and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for recovering braking energy of an electric motorcycle, characterized in that, include: S1. During the operation of the electric motorcycle, acquire angle data collected by the angle sensor installed on the brake handbrake; S2. Determine the mechanical braking torque based on the angle data; S3. Determine the desired change in rotational speed based on the mechanical braking torque and the preset change time period; Based on the current motor speed of the electric motorcycle and the motor speed of the previous moment, the actual speed change is determined; the expected speed change, the actual speed change, the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle are input into a preset motor braking optimization controller, the motor braking optimization controller is run, and the PWM control signal output by the motor braking optimization controller is obtained; The expressions for the desired speed change and the motor braking optimization controller are as follows: In the formula, The desired change in rotational speed; The preset time period of change; The mechanical braking torque; The preset moment of inertia; , , , , , , , These represent the motor current, motor voltage, motor speed, PWM control signal, mechanical braking torque, input power, motor torque, and output power of the electric motorcycle at time k in the future, where k is an integer not less than 0; when k is 0, it represents the current time. For resistance, Let be the electromotive force constant. For inductance, The torque constant is The coefficient of friction of the motor. It is the moment of inertia; These are the preset transfer function constants; The preset time interval is used to characterize the time length between time k and time (k+1). , These are the preset power control weights and speed change control weights, respectively; n is the number of moments predicted by the motor braking optimization controller, k≤n; S4. Determine the motor torque based on the PWM control signal; S5. Based on the electric motor's driving torque and the mechanical braking torque, brake control is performed on the electric motorcycle, and braking energy is recovered based on the electric motor's driving torque.

2. The method for recovering braking energy of an electric motorcycle as described in claim 1, characterized in that, The expression for calculating the mechanical braking torque mentioned in S2 is: in, The mechanical braking torque; The preset braking coefficient; The angle data is as described.

3. The method for recovering braking energy of an electric motorcycle as described in claim 1, characterized in that, It also includes step S6: The PWM control signal and the mechanical braking torque are input into a preset electric motorcycle model to obtain the motor current, motor voltage, and motor speed at the next moment output by the electric motorcycle model. As the angle sensor continues to collect new angle data, the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment are sent to the motor braking optimization controller so that the motor braking optimization controller can continue to solve for new PWM control signals.

4. The method for recovering braking energy of an electric motorcycle as described in claim 3, characterized in that, The expression for the electric motorcycle model is: in, , , These are the motor current, motor voltage, and motor speed output by the electric motorcycle model at the next moment, respectively.

5. A braking energy recovery device for an electric motorcycle, characterized in that, include: The acquisition module is used to acquire angle data collected by the angle sensor installed on the brake handbrake during the operation of the electric motorcycle; The first determining module is used to determine the mechanical braking torque based on the angle data; The second determining module is used to determine the desired change in rotational speed based on the mechanical braking torque and the preset change time period. The actual change in motor speed is determined based on the current motor speed of the electric motorcycle and the motor speed at the previous moment. The desired speed change, the actual speed change, the mechanical braking torque, the current motor current, motor voltage, and motor speed of the electric motorcycle are input into a preset motor braking optimization controller. The motor braking optimization controller is run to obtain the PWM control signal output by the motor braking optimization controller. The expressions for the desired speed change and the motor braking optimization controller are as follows: In the formula, The desired change in rotational speed; The preset time period of change; The mechanical braking torque; The preset moment of inertia; , , , , , , , These represent the motor current, motor voltage, motor speed, PWM control signal, mechanical braking torque, input power, motor torque, and output power of the electric motorcycle at time k in the future, where k is an integer not less than 0; when k is 0, it represents the current time. For resistance, Let be the electromotive force constant. For inductance, The torque constant is The coefficient of friction of the motor. It is the moment of inertia; These are the preset transfer function constants; The preset time interval is used to characterize the time length between time k and time (k+1). , These are the preset power control weights and speed change control weights, respectively; n is the number of moments predicted by the motor braking optimization controller, k≤n; The third determining module is used to determine the motor torque based on the PWM control signal; The braking module is used to control the braking of the electric motorcycle based on the motor's driving torque and the mechanical braking torque, and to recover braking energy based on the motor's driving torque.

6. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 4.

7. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in any one of claims 1 to 4.

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