Battery management system and method for electric bicycle and electronic equipment

Abstract

The invention relates to the technical field of battery management, and discloses a battery management system and method for an electric bicycle and electronic equipment, and the system comprises a first collection module, a second collection module, a management customization module and a management execution module. The method and the electronic equipment correspond to the system. According to the application, the first acquisition module is utilized to accurately acquire basic information such as battery remaining capacity, function state and health state, the second acquisition module can collect custom information such as conventional routes and use habits of users, and the first acquisition module and the second acquisition module cooperate to provide comprehensive data for the management custom module; the management customization module generates a customized power distribution strategy and a charging arrangement strategy, and the management execution module effectively executes the strategy, thereby fully adapting to different battery characteristics and use scene differences of the electric bicycle and the new energy automobile, improving the pertinence and effectiveness of electric bicycle battery management, and improving the user experience. The service life of the battery is prolonged; and the riding experience of a user is optimized.

Description

Technical Field

[0001] The present application relates to the field of battery management technology, and specifically to a battery management system, method and electronic equipment for an electric bicycle. Background Art

[0002] With the rapid development of battery technology, its application in transportation is becoming more and more extensive, and with it comes the need for battery management. Battery management aims to manage the battery by collecting the working status of the battery and based on the preset management logic. It is widely used in new energy vehicles. However, with the use of batteries such as lithium batteries in electric bicycles, the demand for battery management in electric bicycles is also increasing. It is understandable that the demand for battery management of electric bicycles and new energy vehicles is different, both in the nature of the battery itself and in the usage scenarios of electric bicycles and new energy vehicles. Therefore, it is necessary to study battery management that is more suitable for electric bicycles.

[0003] In their research on battery management of electric bicycles, the inventors found that compared with new energy vehicles, when users use electric bicycles, their driving routes are relatively fixed (such as routes to work, pick-up routes), and the charging and discharging frequencies are also relatively fixed (such as regular charging after get off work). Therefore, optimizing the battery management of electric bicycles by extracting users' usage habits is a feasible technical solution.

[0004] Chinese patent publication number CN117922382A discloses a fuel cell vehicle energy management method based on map path planning. The invention obtains the vehicle's current and future position and speed information through the map path planning API, re-acquires information in each time period based on the vehicle's current GPS position, corrects the position and speed information, performs dimensionality reduction clustering analysis on the obtained working conditions, obtains typical working conditions, builds an LVQ working condition identification algorithm, and dynamically calculates the SOC drop change under each typical working condition segment according to the obtained working conditions. Linear fitting is performed to obtain the SOC drop rate of each typical working condition, and the parameters of the typical working condition are used for correction. Finally, a two-layer online energy management strategy is proposed. However, the computing resources of electric bicycles are relatively limited, and they cannot handle such complex data flows like new energy vehicles. In addition, the invention does not fully consider the impact of the relatively fixed driving routes (such as commuting routes) and regular charging and discharging frequencies (such as fixed charging after get off work) of electric bicycle users on energy management, and it is difficult to be directly applied to the battery management scenario of electric bicycles.

[0005] In summary, a technical solution for battery management of electric bicycles is needed to improve the adaptability of battery management to electric bicycles. Summary of the invention

[0006] The purpose of this application is to provide a battery management system, method and electronic device for an electric bicycle to solve the technical problems raised in the above background technology.

[0007] To achieve the above objectives, this application discloses the following technical solutions:

[0008] In a first aspect, the present embodiment discloses a battery management system for an electric bicycle, the system comprising a first acquisition module for acquiring basic information of the battery, a second acquisition module for acquiring customized information of the user, a management customization module for generating a customized battery management strategy based on the basic information and the customized information, and a management execution module for executing the customized management strategy; the first acquisition module is communicatively connected to the management customization module, the second acquisition module is communicatively connected to the management customization module, and the management customization module is communicatively connected to the management execution module; wherein the basic information at least includes the remaining power, functional status and health status, the customized information at least includes the usual route and usage habits, and the customized battery management strategy at least includes the power allocation strategy and the charging arrangement strategy;

[0009] When the battery management system for an electric motorcycle is running, corresponding customized parameters are generated based on the customized information collected by the second acquisition module, the first acquisition module collects the basic information, the management customization module uses the basic information and combines the customized parameters to generate the corresponding customized management strategy, and the management execution module receives the customized management strategy and executes it; wherein, the customized parameters are used to adjust the customized management strategy.

[0010] Preferably, the first acquisition module is arranged on the electric bicycle; the second acquisition module is arranged on the user's smart device; and the management execution module is arranged on the electric bicycle.

[0011] Preferably, the basic information collection process includes:

[0012] Use the preset SOC estimation algorithm to obtain the corresponding remaining power;

[0013] Using the preset SOF estimation algorithm to obtain the corresponding functional state;

[0014] Use the preset SOH estimation algorithm to obtain the corresponding health status;

[0015] The remaining power, the functional status and the health status obtained are packaged and defined as basic information and then output to the management customization module.

[0016] Preferably, the process of collecting the customized information includes:

[0017] Using the user's smart device to determine the predetermined starting point and the predetermined end point of the user's use of the electric bicycle, obtain a common route, and analyze the common route to obtain a corresponding operating condition set, wherein the operating condition set is used to characterize the road conditions of the common route;

[0018] Using the user's smart device to determine the predetermined charging frequency and predetermined charging time period for using the electric bicycle, and obtain the usage habits;

[0019] The commonly used route and the corresponding working condition set and the use habit are packaged and defined as customized information and then output to the management customization module.

[0020] Preferably, the process of generating the customized parameters includes:

[0021] Quantifying the operating condition set, generating an operating condition fusion parameter based on the proportion of different operating conditions and corresponding energy consumption weights and standard speeds, wherein the operating condition fusion parameter is used to characterize the comprehensive influence of different sections on the power demand under the conventional route;

[0022] The features of the predetermined charging frequency and the predetermined charging period are extracted from the usage habit to generate a habit fusion parameter, wherein the habit fusion parameter is used to formulate a charging arrangement strategy based on the basic information.

[0023] Preferably, the generation process of the power allocation strategy includes:

[0024] Obtaining an initial output power function based on historical basic information and corresponding power allocation conditions, wherein the initial output power function is used to determine an initial output power range of the battery based on the basic information;

[0025] Inputting the basic information into the initial output power function to obtain the initial output power P0;

[0026] The power distribution under different working conditions is obtained by using the preset power distribution formula and combining the working condition fusion parameters; wherein the power distribution formula is specifically as follows:

[0027] P x ≤P0*r x *ω x

[0028] Among them, r x is the proportion of operating condition x in the conventional route, ω x is the energy consumption weight of condition x in the usual route, P x is the power allocated to operating condition x in the conventional route.

[0029] Preferably, the generation process of the charging arrangement strategy includes:

[0030] Set the low battery threshold SOC L And warning power threshold SOC W Among them, SOC L <SOC W ;

[0031] Using battery capacity C, remaining power SOC, standard charging current I τ And the health status SOH get the estimated charging time

[0032] Based on the predetermined charging period [t s ,t e ], combined with the current time t, the corresponding short-term charging arrangement strategy is generated, specifically:

[0033] when And the remaining power SOC at the current time t t ≤SOC W When the battery is charged, the user is prompted to charge after entering the designated charging period, and the estimated charging time is T c_t ;

[0034] When t∈[t s ,t e ], and the remaining power SOC at the current time t t ≤SOC L When the battery is charged, the user is prompted to charge immediately, and the estimated charging time is T c_t ;

[0035] Based on the execution of the charging arrangement strategy, the charging time t after each charging is completed is recorded. lc , and calculate the recommended charging time in combination with the predetermined charging frequency f A long-term charging arrangement strategy is generated based on the recommended charging time.

[0036] Preferably, the operation process of the management execution module includes:

[0037] When SOC t ≤SOC L and When the power allocation strategy is enforced, a preset power controller is used.

[0038] In a second aspect, this embodiment discloses a battery management method for an electric bicycle, which is applicable to the battery management system for an electric bicycle as described above, and includes:

[0039] S1: Collecting customization information to generate corresponding customization parameters; wherein the customization information at least includes a common route and usage habits, and the customization parameters are used to adjust the customization management strategy;

[0040] S2: Collect basic information; wherein the basic information at least includes remaining power, functional status and health status;

[0041] S3: Generate the corresponding customized management strategy using the basic information and combining the customized parameters; wherein the customized management strategy at least includes a power allocation strategy and a charging arrangement strategy;

[0042] S4: Execute the customized management policy.

[0043] In a third aspect, the present application discloses an electronic device, comprising: at least one processor and at least one memory, wherein the memory is communicatively connected to the processor; the memory stores a computer program that can be executed by the processor, and when the computer program is executed by the processor, the battery management method for an electric bicycle as described above is implemented.

[0044] Beneficial effects: The battery management system, method and electronic device for electric bicycles of the present application utilize a battery management system architecture of a first acquisition module, a second acquisition module, a management customization module and a management execution module specially designed for electric bicycles to achieve precise management of electric bicycle batteries. The first acquisition module can accurately obtain basic information such as the remaining battery power, functional status and health status, and the second acquisition module can collect customized information such as the user's usual routes and usage habits. The two work together to provide comprehensive data for the management customization module. The management customization module generates customized power allocation strategies and charging arrangement strategies based on this, and the management execution module effectively executes them. This fully adapts to the different battery characteristics and usage scenario differences between electric bicycles and new energy vehicles, overcomes the drawbacks that existing automotive battery management technology is not suitable for electric bicycles, improves the pertinence and effectiveness of electric bicycle battery management, extends battery life and optimizes the user's riding experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 A structural block diagram of a battery management system for an electric bicycle provided in an embodiment of the present application;

[0047] Figure 2 A flowchart of a battery management method for an electric bicycle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0049] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0050] The first aspect of this embodiment discloses Figure 1 A battery management system for an electric bicycle is shown, the system comprising a first acquisition module for acquiring basic information of the battery, a second acquisition module for acquiring customized information of the user, a management customization module for generating a customized battery management strategy based on the basic information and the customized information, and a management execution module for executing the customized management strategy; the first acquisition module is communicatively connected to the management customization module, the second acquisition module is communicatively connected to the management customization module, and the management customization module is communicatively connected to the management execution module; wherein the basic information at least includes the remaining power, functional status and health status, the customized information at least includes the usual route and usage habits, and the customized battery management strategy at least includes the power allocation strategy and the charging arrangement strategy;

[0051] When the battery management system for electric motorcycles is running, corresponding customized parameters are generated based on the customized information collected by the second acquisition module, the first acquisition module collects basic information, the management customization module uses the basic information and combines the customized parameters to generate corresponding customized management strategies, and the management execution module receives and executes the customized management strategies; wherein, the customized parameters are used to adjust the customized management strategies.

[0052] Based on the above, this embodiment utilizes the battery management system architecture of the first acquisition module, the second acquisition module, the management customization module and the management execution module specially designed for electric bicycles to achieve accurate management of electric bicycle batteries. The first acquisition module can accurately obtain basic information such as the remaining battery power, functional status and health status, and the second acquisition module can collect customized information such as the user's usual routes and usage habits. The two work together to provide comprehensive data for the management customization module. The management customization module generates customized power allocation strategies and charging arrangement strategies based on this, and the management execution module effectively executes them. This fully adapts to the different battery characteristics and usage scenario differences between electric bicycles and new energy vehicles, overcomes the drawbacks that existing automotive battery management technology is not suitable for electric bicycles, improves the pertinence and effectiveness of electric bicycle battery management, extends battery life and optimizes user riding experience.

[0053] Specifically, the first acquisition module is set on the electric bicycle; the second acquisition module is set on the user's smart device; and the management execution module is set on the electric bicycle.

[0054] Based on the above, this embodiment utilizes the layout of setting the first acquisition module on the electric bicycle, the second acquisition module on the smart device, and the management execution module on the electric bicycle to achieve efficient data collection and strategy execution, wherein the first acquisition module monitors the operating data of the electric bicycle battery in real time to ensure the timeliness and accuracy of basic information, the second acquisition module conveniently obtains user usage habit information with the help of smart devices, broadens the data source, and the management execution module can directly perform power control and other operations on the battery on the electric bicycle, reduce data transmission delays, ensure that customized management strategies take effect quickly, improve the response speed and operating efficiency of the entire battery management system, and make battery management closely integrated with the actual operation of the electric bicycle. It should be noted that the first acquisition module, the second acquisition module, and the management execution module of this embodiment are all constructed using existing hardware devices, such as current sensors, voltage sensors, smart terminals (such as mobile phones), and power controllers, and the management customization module of this embodiment can be, but is not limited to, any existing data cloud platform, thereby avoiding placing a large number of data processing tasks locally.

[0055] Specifically, the process of collecting basic information includes:

[0056] Use the preset SOC estimation algorithm to obtain the corresponding remaining power;

[0057] Using the preset SOF estimation algorithm to obtain the corresponding functional state;

[0058] Use the preset SOH estimation algorithm to obtain the corresponding health status;

[0059] The remaining power, functional status and health status are packaged and defined as basic information and then output to the management customization module.

[0060] Through the above, this embodiment uses any of the existing SOC estimation algorithms, SOF estimation algorithms and SOH estimation algorithms to collect basic information, thereby realizing accurate quantification of the battery status. The SOC estimation algorithm can accurately know the remaining power and provide a power basis for power allocation and charging arrangements. The SOF estimation algorithm accurately determines the functional status to ensure the reasonable allocation of power under different working conditions. The SOH estimation algorithm clarifies the health status and optimizes the management strategy considering the degree of battery aging. Through the comprehensive use of these algorithms, the system can deeply understand the battery performance, avoid management errors caused by misjudgment of the battery status, improve the safety of battery use, and provide a reliable data basis for the subsequent generation of customized strategies, so that battery management is more in line with actual needs.

[0061] Specifically, the collection process of customized information includes:

[0062] Using the user's smart device to determine the user's predetermined starting point and predetermined end point of the electric bicycle, obtaining a common route, parsing the common route to obtain a corresponding working condition set, the working condition set is used to characterize the road conditions of the common route;

[0063] Using the user's smart device to determine the predetermined charging frequency and predetermined charging time period for using the electric bicycle, and obtain the usage habits;

[0064] The commonly used routes and the corresponding working condition sets and usage habits are packaged and defined as customized information and then output to the management customization module.

[0065] Based on the above, this embodiment uses smart devices to collect information about the user's established starting point, end point, charging frequency, and time period when using an electric bicycle, thereby achieving in-depth mining of the user's usage habits. The usual route determined by the established starting point and end point can be parsed into a set of operating conditions, providing a road condition basis for the power allocation strategy, so that the electric bicycle can reasonably allocate power in different sections of the road, saving energy and increasing efficiency. The usage habits composed of established charging frequencies and time periods provide a reference for the charging arrangement strategy, allowing the battery to be charged at the right time, reducing unnecessary charging losses and extending battery life. This method of collecting information based on user habits makes the battery management system more personalized and improves user satisfaction and recognition of electric bicycle battery management.

[0066] Specifically, the process of generating customized parameters includes:

[0067] The working condition set is quantified, and working condition fusion parameters are generated based on the proportion of different working conditions, the corresponding energy consumption weights and standard speeds. The working condition fusion parameters are used to characterize the comprehensive impact of different sections on power demand under the usual route;

[0068] The features of the established charging frequency and the established charging period are extracted from the usage habits to generate habit fusion parameters, which are used to formulate a charging arrangement strategy based on basic information.

[0069] Based on the above, this embodiment utilizes the quantization of the working condition set to generate the working condition fusion parameters and the extraction of the usage habits to generate the habit fusion parameters, thereby realizing the precise adjustment of the management strategy by customized parameters. The working condition fusion parameters reflect the comprehensive influence of different road sections on the power demand, so that the power allocation strategy can be flexibly changed according to the road conditions, such as reasonably increasing the power output on the climbing section and appropriately reducing it on the flat road to improve energy utilization efficiency. The habit fusion parameters formulate the charging arrangement strategy based on the usage habits, such as determining the power threshold according to the charging frequency, optimizing the power usage during the non-charging period, and reasonably controlling the charging current and voltage during the charging period. These customized parameters effectively improve the intelligence level of the battery management system, making the management strategy more in line with the actual operation of electric bicycles and user needs.

[0070] Specifically, the process of generating the power allocation strategy includes:

[0071] Based on the historical basic information and the corresponding power allocation situation, an initial output power function is obtained, and the initial output power function is used to determine the initial output power range of the battery based on the basic information;

[0072] Input the basic information into the initial output power function to obtain the initial output power P0;

[0073] The power distribution under different working conditions is obtained by using the preset power distribution formula and combining the working condition fusion parameters. The specific power distribution formula is as follows:

[0074] P x ≤P0*r x *ω x

[0075] Among them, r x is the proportion of operating condition x in the conventional route, ω x is the energy consumption weight of condition x in the usual route, P x is the power allocated to operating condition x in the conventional route.

[0076] As a preferred implementation of this embodiment, this embodiment uses a speed limit formula to constrain power distribution, wherein the speed limit formula is specifically:

[0077]

[0078] Among them, v x_τ is the standard speed of condition x in the usual route, v x is the actual speed of the working condition x in the conventional route. In this way, the control v is realizedx To achieve power allocation; in a simple example, this embodiment transmits the generated power allocation strategy to the user's smart device, and reminds the user to limit the speed based on, but not limited to, voice prompts to improve the power allocation effect. Further, when the management execution module is running, the speed limiter can be used to limit the speed of the vehicle. x , thereby achieving the purpose of enforcing the power allocation strategy.

[0079] Based on the above, this embodiment utilizes the initial output power function based on historical basic information and power distribution conditions combined with the working condition fusion parameters to generate a power distribution strategy, thereby achieving scientific power distribution. The initial output power function determines the power range by comprehensively considering various aspects of the battery status to ensure that the allocated power is within the battery's tolerance range. The working condition fusion parameters further refine the power distribution according to the proportion of different road conditions and energy consumption weights, so that the electric bicycle can adjust the power output in real time according to the route during driving to avoid over-discharge or overload of the battery. For example, in routes with complex road conditions, concentrated power is used to climb uphill, and energy is appropriately recovered when going downhill, which improves the battery's endurance and overall performance, while extending the battery's service life and optimizing the power performance of the electric bicycle. It should be noted that the method for obtaining the initial output power function of this embodiment is any existing function construction method, and this embodiment is not limited here.

[0080] Specifically, the generation process of the charging arrangement strategy includes:

[0081] Set the low battery threshold SOC L And warning power threshold SOC W Among them, SOC L <SOC W ;

[0082] Using battery capacity C, remaining power SOC, standard charging current I τ And the health status SOH get the estimated charging time

[0083] Based on the established charging period [t s ,t e ], combined with the current time t, the corresponding short-term charging arrangement strategy is generated, specifically:

[0084] when And the remaining power SOC at the current time t t ≤SOC W When the battery is charged, the user is prompted to charge after entering the designated charging period, and the estimated charging time is T c_t ;

[0085] When t∈[t s ,t e], and the remaining power SOC at the current time t t ≤SOC L When the battery is charged, the user is prompted to charge immediately, and the estimated charging time is T c_t ;

[0086] Based on the execution of the charging arrangement strategy, the charging time t after each charging is completed is recorded. lc , and calculate the recommended charging time based on the established charging frequency f And generate a long-term charging schedule strategy based on the recommended charging time.

[0087] It should be noted that the health status in the calculation of the estimated charging time in this embodiment realizes the estimation of the charging time based on the health status, and based on this, when providing charging arrangement prompts, the health status can be provided to the user so that the user can understand the battery status. In a simple example, the prompt content is "The current power is low. It is recommended that you enter the charging period [t s ,t e ] and then charge. The estimated charging time is about T c_t hours. The charging time has been adjusted according to the battery health status. The current battery health is SOH".

[0088] Based on the above, this embodiment utilizes the setting of low battery threshold and warning battery threshold and generates charging arrangement strategy in combination with the established charging period and habit fusion parameters to achieve reasonable charging planning. The low battery threshold and warning battery threshold can timely remind the user of the charging status to avoid excessive discharge of the battery. In combination with the established charging period, charging prompts are given at the appropriate time. For example, when the battery is low in the non-charging period, a prompt is given to enter the charging period to charge and the estimated duration is given. When the battery is extremely low in the charging period, a prompt is given to charge immediately, which is convenient for user arrangement. At the same time, the habit fusion parameters are taken into consideration, and the charging arrangement is optimized according to habits such as charging frequency. The charging time is recorded to calculate the recommended charging time to generate a long-term strategy, so that the battery charging is carried out in an orderly manner, the safety and efficiency of battery charging are improved, and the continuous use of the electric bicycle is guaranteed.

[0089] Specifically, the operation process of the management execution module includes:

[0090] When SOC t ≤SOC L and When the power allocation strategy is enforced, the preset power controller is used.

[0091] Through the above, this embodiment utilizes the management execution module to enforce the power allocation strategy under specific power levels and working conditions, thereby achieving effective control over the battery power output. When the set conditions are met, the preset power controller ensures that the power allocation strategy is strictly implemented to prevent power allocation from getting out of control due to external factors or system failures. For example, when the battery power is low and in complex working conditions, the strategy is strictly followed to reduce unnecessary power consumption, ensuring that the electric bicycle can smoothly reach the destination or charging point, avoiding battery damage due to excessive discharge, and improving the reliability and stability of the battery management system at critical times, ensuring the stable operation of the electric bicycle.

[0092] The second aspect of this embodiment discloses Figure 2 A battery management method for an electric bicycle is shown, and the method is applicable to the battery management system for an electric bicycle as described above, and the method comprises:

[0093] S1: Collecting customization information to generate corresponding customization parameters; wherein the customization information at least includes the usual routes and usage habits, and the customization parameters are used to adjust the customization management strategy;

[0094] S2: Collect basic information; the basic information at least includes remaining power, functional status and health status;

[0095] S3: Generate a corresponding customized management strategy using the basic information and in combination with the customized parameters; wherein the customized management strategy includes at least a power allocation strategy and a charging arrangement strategy;

[0096] S4: Execute customized management strategies.

[0097] It should be noted that the battery management method for an electric bicycle of the present embodiment corresponds to the aforementioned battery management system for an electric bicycle. Therefore, the contents not specifically described in the battery management method for an electric bicycle of the present embodiment may include but are not limited to function definitions, working principles, and technical effects, etc., and may all refer to the records in the aforementioned battery management system for an electric bicycle, and this text will not elaborate on them here.

[0098] The third aspect of this embodiment discloses an electronic device, including: at least one processor and at least one memory, the memory is communicatively connected to the processor; the memory stores a computer program that can be executed by the processor, and when the computer program is executed by the processor, the battery management method for an electric bicycle as described above is implemented.

[0099] Similarly, it should be noted that the electronic device of this embodiment corresponds to the aforementioned battery management system for electric bicycles. Therefore, the contents not specifically described in the electronic device of this embodiment may include but are not limited to function definitions, working principles and technical effects, etc., and may refer to the records in the aforementioned battery management system for electric bicycles, and this text will not elaborate on them here.

[0100] In summary, the battery management system, method and electronic device for electric bicycles of this embodiment utilizes the battery management system architecture of the first acquisition module, the second acquisition module, the management customization module and the management execution module specially designed for electric bicycles to achieve accurate management of electric bicycle batteries. The first acquisition module can accurately obtain basic information such as the remaining battery power, functional status and health status, and the second acquisition module can collect customized information such as the user's usual routes and usage habits. The two work together to provide comprehensive data for the management customization module. The management customization module generates customized power allocation strategies and charging arrangement strategies based on this, and the management execution module effectively executes them. This fully adapts to the different battery characteristics and usage scenario differences between electric bicycles and new energy vehicles, overcomes the drawbacks that existing automotive battery management technology is not suitable for electric bicycles, improves the pertinence and effectiveness of electric bicycle battery management, extends battery life and optimizes user riding experience.

[0101] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein or their combination. For software implementation, part or all of the flow of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that is convenient for transmitting a computer program from one place to another. The storage medium can be any available medium that a computer can access. The computer-readable storage medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.

[0102] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A battery management system for an electric bicycle, characterized in that: The system includes a first acquisition module for acquiring basic information of the battery, a second acquisition module for acquiring customized information of the user, a management customization module for generating a customized battery management strategy based on the basic information and the customized information, and a management execution module for executing the customized management strategy; The first acquisition module is in communication connection with the management customization module, the second acquisition module is in communication connection with the management customization module, and the management customization module is in communication connection with the management execution module; wherein the basic information at least includes the remaining power, functional status and health status, the customized information at least includes the usual route and usage habits, and the customized battery management strategy at least includes the power allocation strategy and the charging arrangement strategy; When the battery management system for an electric motorcycle is running, corresponding customized parameters are generated based on the customized information collected by the second acquisition module, the first acquisition module collects the basic information, the management customization module uses the basic information and combines the customized parameters to generate the corresponding customized management strategy, and the management execution module receives the customized management strategy and executes it; wherein, the customized parameters are used to adjust the customized management strategy.

2. The battery management system for an electric bicycle according to claim 1, characterized in that: The first acquisition module is arranged on the electric bicycle; the second acquisition module is arranged on the user's smart device; and the management execution module is arranged on the electric bicycle.

3. The battery management system for an electric bicycle according to claim 1, characterized in that: The basic information collection process includes: Use the preset SOC estimation algorithm to obtain the corresponding remaining power; Using the preset SOF estimation algorithm to obtain the corresponding functional state; Use the preset SOH estimation algorithm to obtain the corresponding health status; The remaining power, the functional status and the health status obtained are packaged and defined as basic information and then output to the management customization module.

4. The battery management system for an electric bicycle according to claim 1, characterized in that: The process of collecting the customized information includes: Using the user's smart device to determine the predetermined starting point and the predetermined end point of the user's use of the electric bicycle, obtain a common route, and analyze the common route to obtain a corresponding operating condition set, wherein the operating condition set is used to characterize the road conditions of the common route; Using the user's smart device to determine the predetermined charging frequency and predetermined charging time period for using the electric bicycle, and obtain the usage habits; The commonly used route and the corresponding working condition set and the use habit are packaged and defined as customized information and then output to the management customization module.

5. The battery management system for an electric bicycle according to claim 4, characterized in that: The generation process of the customized parameters includes: Quantifying the operating condition set, generating an operating condition fusion parameter based on the proportion of different operating conditions and corresponding energy consumption weights and standard speeds, wherein the operating condition fusion parameter is used to characterize the comprehensive influence of different sections on the power demand under the conventional route; The features of the predetermined charging frequency and the predetermined charging period are extracted from the usage habit to generate a habit fusion parameter, wherein the habit fusion parameter is used to formulate a charging arrangement strategy based on the basic information.

6. The battery management system for an electric bicycle according to claim 5, characterized in that: The generation process of the power allocation strategy includes: Obtaining an initial output power function based on historical basic information and corresponding power allocation conditions, wherein the initial output power function is used to determine an initial output power range of the battery based on the basic information; Inputting the basic information into the initial output power function to obtain the initial output power P0; The power distribution under different working conditions is obtained by using the preset power distribution formula and combining the working condition fusion parameters; wherein the power distribution formula is specifically as follows: P x ≤P0*r x *oh x Among them, r x is the proportion of operating condition x in the conventional route, ω x is the energy consumption weight of condition x in the usual route, P x is the power allocated to operating condition x in the conventional route.

7. The battery management system for an electric bicycle according to claim 5, characterized in that: The generation process of the charging arrangement strategy includes: Set the low battery threshold SOC L And warning power threshold SOC W Among them, SOC L <SOC W ; Using battery capacity C, remaining power SOC, standard charging current I τ And the health status SOH get the estimated charging time Based on the predetermined charging period [t s ,t e ], combined with the current time t, the corresponding short-term charging arrangement strategy is generated, specifically: when And the remaining power SOC at the current time t t ≤SOC W When the battery is charged, the user is prompted to charge after entering the designated charging period, and the estimated charging time is T c_t ; When t∈[t s ,t e ], and the remaining power SOC at the current time t t ≤SOC L When the battery is charged, the user is prompted to charge immediately, and the estimated charging time is T c_t ; Based on the execution of the charging arrangement strategy, the charging time t after each charging is completed is recorded. lc , and calculate the recommended charging time in combination with the predetermined charging frequency f A long-term charging arrangement strategy is generated based on the recommended charging time.

8. The battery management system for an electric bicycle according to claim 7, characterized in that: The operation process of the management execution module includes: When SOC t ≤SOC L and When the power allocation strategy is enforced, a preset power controller is used.

9. A battery management method for an electric bicycle, the method being applicable to the battery management system for an electric bicycle as claimed in any one of claims 1 to 8, characterized in that: The method includes: S1: Collecting customization information to generate corresponding customization parameters; wherein the customization information at least includes a common route and usage habits, and the customization parameters are used to adjust the customization management strategy; S2: Collect basic information; wherein the basic information at least includes remaining power, functional status and health status; S3: Generate the corresponding customized management strategy using the basic information and combining the customized parameters; wherein the customized management strategy at least includes a power allocation strategy and a charging arrangement strategy; S4: Execute the customized management policy.

10. An electronic device, characterized in that: include: At least one processor and at least one memory, the memory being communicatively connected to the processor; the memory storing a computer program that can be executed by the processor, and when the computer program is executed by the processor, the battery management method for an electric bicycle as described in claim 9 is implemented.

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