Dynamic power-assisted control method and device for electric bicycle

Abstract

The invention discloses a dynamic power-assisted control method and device for an electric bicycle, and belongs to the field of electric vehicle control. The method comprises the steps that two power supply batteries capable of being independently used are arranged on the electric bicycle, a target riding route is determined, road section recognition is conducted, and a plurality of power-assisted road sections are obtained; dividing the plurality of power-assisted road sections to obtain a plurality of single-battery power-assisted road sections and a plurality of double-battery power-assisted road sections; in the single-battery power-assisted road section, the remaining electric quantity of the first battery and the remaining electric quantity of the second battery are recognized, a power-assisted battery is determined based on the remaining electric quantity, and power-assisted control is conducted on the electric bicycle; and in the double-battery power-assisted road section, the first battery and the second battery are switched to be in a parallel connection state to form a parallel battery pack, and power-assisted control is carried out on the electric bicycle. By arranging the double batteries, the use of the batteries is dynamically optimized according to road section characteristics and battery states, and the technical effects that accurate and efficient electric traction is achieved under different road sections, and the cruising ability and the power performance of the electric bicycle are improved are achieved.

Description

Technical Field

[0001] The present invention relates to the field of electric vehicle control, and in particular to a dynamic power-assistance control method and device for an electric bicycle. Background Art

[0002] As an environmentally friendly and convenient means of transportation, electric bicycles' battery life and riding experience directly impact user satisfaction. However, current electric bicycles face numerous challenges. For one thing, most electric bicycles are equipped with only a single battery, resulting in extremely limited range and difficulty meeting users' needs for medium- and long-distance travel. Furthermore, their powertrains are unable to intelligently and accurately distribute power based on varying road conditions, such as climbing, flat roads, and downhill sections. This results in insufficient power on sections requiring high power output, such as climbing, and energy waste on flat roads or downhill sections.

[0003] The existing technology has technical problems such as short battery life of electric bicycles, poor power distribution on roads and imprecise battery management. Summary of the Invention

[0004] This application provides a dynamic power-assistance control method and device for an electric bicycle, aiming to solve the technical problems of short battery life, poor road power distribution and imprecise battery management of electric bicycles in the prior art.

[0005] In view of the above problems, the present application provides a method and device for dynamic power assistance control of an electric bicycle.

[0006] The first aspect disclosed in the present application provides a dynamic power-assistance control method for an electric bicycle, the method comprising: equipping the electric bicycle with two separately usable power supply batteries, namely a first battery and a second battery, and configuring a user input terminal, wherein the first battery is the same as the second battery; obtaining the current position information of the electric bicycle and the destination information of the target user through the user input terminal, and sending them to a cloud server to determine the target riding route; identifying the sections of the target riding route according to the historical riding data of the target user to obtain a plurality of power-assistance sections; dividing the plurality of power-assistance sections based on the historical riding data to obtain a plurality of single-battery power-assistance sections and a plurality of dual-battery power-assistance sections; in the single-battery power-assistance section, identifying the remaining power of the first battery and the second battery, determining the power-assistance battery based on the remaining power, and performing power-assistance control on the electric bicycle; in the dual-battery power-assistance section, switching the first battery and the second battery to a parallel state to form a parallel battery pack to perform power-assistance control on the electric bicycle.

[0007] Another aspect disclosed in the present application provides a dynamic power-assistance control device for an electric bicycle, the device comprising: a hardware configuration module for equipping the electric bicycle with two separately usable power supply batteries, namely a first battery and a second battery, and configuring a user input terminal, wherein the first battery is the same as the second battery; a route planning module for obtaining the current location information of the electric bicycle and the destination information of the target user through the user input terminal, and sending the information to a cloud server to determine the target riding route; a section identification module for identifying sections of the target riding route based on the historical riding data of the target user to obtain multiple power-assistance sections; a power-assistance classification module for dividing the multiple power-assistance sections based on the historical riding data to obtain multiple single-battery power-assistance sections and multiple dual-battery power-assistance sections; a single-battery control module for identifying the remaining power of the first battery and the second battery in the single-battery power-assistance section, determining the power-assistance battery based on the remaining power, and performing power-assistance control on the electric bicycle; and a dual-battery control module for switching the first battery and the second battery into a parallel state in the dual-battery power-assistance section to form a parallel battery pack to perform power-assistance control on the electric bicycle.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: Since the electric bicycle is equipped with two separately usable power supply batteries, namely the first battery and the second battery, and a user input terminal is configured, wherein the first battery is the same as the second battery, a flexible power supply configuration is provided for the electric bicycle; the current position information of the electric bicycle and the destination information of the target user are obtained through the user input terminal, and sent to the cloud server to determine the target riding route, laying the foundation for subsequent road section analysis; the road section of the target riding route is identified according to the historical riding data of the target user, and multiple power-assisted sections are obtained to identify the road sections that need power assistance; based on the historical riding data, the multiple power-assisted sections are divided respectively to obtain multiple single-battery power-assisted sections and multiple dual-battery power-assisted sections, further refining the road section classification, and preparing for the subsequent dynamic battery usage strategy; in the case of single-battery power-assisted In the road section, the remaining power of the first battery and the second battery is identified, the power-assisting battery is determined based on the remaining power, and the electric bicycle is controlled with power assistance, which realizes the battery selection and control of the single-battery section and optimizes the battery use efficiency; in the dual-battery power-assisting section, the first battery and the second battery are switched to a parallel state to form a parallel battery pack, and the electric bicycle is controlled with power assistance. In the road section requiring greater power assistance, the dual batteries are used in parallel to provide a technical solution with stronger power support, which solves the technical problems of short battery life, poor power distribution on the road section and imprecise battery management of the electric bicycle in the existing technology. By setting up dual batteries, the battery use is dynamically optimized according to the road section characteristics and battery status, so as to achieve accurate and efficient electric traction in different sections, and improve the technical effect of improving the battery life and power performance of the electric bicycle.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flow chart of a method for controlling dynamic power assist of an electric bicycle is provided for an embodiment of the present application; Figure 2 A structural schematic diagram of a dynamic power-assistance control device for an electric bicycle is provided for an embodiment of the present application.

[0011] Explanation of the reference numerals: hardware configuration module 11 , route planning module 12 , road section identification module 13 , power assistance classification module 14 , single battery control module 15 , dual battery control module 16 . DETAILED DESCRIPTION

[0012] The overall idea of the technical solution provided by this application is as follows: The embodiments of the present application provide a method and device for dynamic power-assistance control of an electric bicycle, which significantly improves the endurance and riding experience of the electric bicycle through intelligent road section recognition and dynamic battery management.

[0013] First, two identical batteries that can be used separately are configured on the electric bicycle to lay the foundation for a flexible power management strategy. Secondly, the current location and destination information are obtained through the user input terminal, and the target riding route is determined in combination with the data processing capabilities of the cloud server. Then, the user's historical riding data is used to intelligently analyze the target route, identify and divide the sections that require power, including single-battery power-assisted sections and dual-battery power-assisted sections. During the actual riding process, for single-battery power-assisted sections, the remaining power of the two batteries is identified and the most suitable battery is selected for power supply to achieve refined energy management; for dual-battery power-assisted sections, the two batteries are switched to a parallel state to form a parallel battery pack to provide stronger power support. Through dynamic adjustment, the present application maximizes the efficiency of battery use, effectively extending the range of the electric bicycle while ensuring sufficient power output.

[0014] In general, this application builds a comprehensive dynamic power-assistance control system by combining real-time traffic information, historical riding data, and intelligent battery management strategies, which not only improves the efficiency of electric bicycles but also improves the user's riding experience.

[0015] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the drawings in the specification.

[0016] Example 1, as Figure 1 As shown, an embodiment of the present application provides a method for controlling dynamic power assistance of an electric bicycle, the method comprising: S1: The electric bicycle is equipped with two independently usable power supply batteries, namely a first battery and a second battery, and a user input terminal, wherein the first battery and the second battery are identical.

[0017] Specifically, the electric bicycle is equipped with two independently usable power supply batteries, a first battery and a second battery. The specifications and performance parameters of the first battery and the second battery are identical. In addition to the first and second batteries, the electric bicycle is also equipped with a user input terminal, which may be a touch screen, a keypad, or other human-computer interaction interface, for receiving various user input information and providing the necessary data support for subsequent intelligent control.

[0018] The dual-battery configuration can increase the endurance of electric bicycles and meet the needs of users for long-distance riding. At the same time, they can be flexibly used individually or in parallel according to the needs of different road sections, thereby achieving more intelligent and efficient energy distribution. Furthermore, if one of the batteries has a problem, the other can continue to be used, improving system reliability and reducing riding interruptions caused by battery failure.

[0019] The dual-battery hardware configuration lays a solid foundation for subsequent dynamic power-assistance control and creates favorable conditions for achieving a more intelligent and efficient electric bicycle power-assistance system. It not only improves the performance and reliability of the system, but also provides users with a more flexible usage experience.

[0020] S2: Obtain the current location information of the electric bicycle and the destination information of the target user through the user input terminal, send them to the cloud server, and determine the target riding route.

[0021] Specifically, the current location information is automatically acquired via the GPS module built into the user input terminal, while the destination information is manually entered by the user. Subsequently, the current location information and destination information are transmitted to the cloud server via the wireless communication module. After receiving the current location information and destination information, the cloud server accesses its cloud map database. Based on the current location information and destination information, it retrieves and generates multiple alternative cycling routes. Next, the cloud server sends these alternative cycling routes back to the user input terminal via the wireless communication module. The user input terminal presents the multiple alternative cycling routes to the target user for selection. Once the target user makes a selection, the user input terminal returns the selection result to the cloud server, and the user-selected alternative cycling route is determined as the target cycling route.

[0022] By combining human-computer interaction and cloud computing, the accuracy and personalization of route planning are improved, thereby enhancing the overall user experience and laying a solid foundation for subsequent dynamic power-assisted control.

[0023] S3: Identify sections of the target cycling route based on the historical cycling data of the target user to obtain multiple assisting sections.

[0024] Specifically, first, the target user's historical riding data is extracted, including but not limited to the target user's past riding routes, riding speed, cadence, power assist usage, and other information. By analyzing the target user's historical riding data, a deeper understanding of the user's riding habits and preferences is obtained. Secondly, this historical riding data is compared and analyzed with the current target riding route to identify road segment features on the target riding route that are similar or match the user's historical riding data. Based on this analysis, multiple sections on the target riding route that may require power assist are identified, namely, multiple power assist sections. These power assist sections may be uphill sections with steep slopes, sections where the user has historically frequently used power assist, or sections predicted to require power assist based on the user's physical condition. The road segment identification method based on historical riding data is highly personalized. Even for the same route, the identified power assist sections may be different for different users. This personalized identification method can better meet the needs of different users and improve the intelligence level of e-bikes.

[0025] Through road section recognition, a more detailed and personalized road section division is provided for subsequent dynamic power assist control, laying the foundation for accurate and efficient power distribution. It can not only improve the user's riding comfort, but also achieve more reasonable power use and extend the range of electric bicycles.

[0026] S4: Based on the historical riding data, the plurality of power-assisted sections are divided into a plurality of single-battery power-assisted sections and a plurality of dual-battery power-assisted sections.

[0027] Specifically, each identified power-assisted route segment is analyzed individually using the target user's historical riding data, taking into account multiple factors such as the segment's slope, length, and expected riding speed. Based on these factors and combined with historical riding data, the required power assist for each segment is estimated, and the multiple power-assisted routes are then divided into single-battery and dual-battery routes. A single-battery route segment is one where the required power assist is estimated to be low and can be met using a single battery. These may be flat roads or sections with slight inclines. A dual-battery route segment is one where the required power assist is estimated to be high and requires two batteries in parallel. These may be steep uphill sections or routes where the target user has historically required higher power assist. This segmentation enables more refined energy management. On single-battery routes, a single battery is selectively used to extend overall range. On dual-battery routes, the system switches to dual-battery mode to ensure adequate power assist and enhance riding comfort.

[0028] Through intelligent road section division, a more accurate basis is provided for subsequent dynamic power assist control, which helps to optimize the utilization of battery energy. It can not only improve the endurance of electric bicycles, but also ensure that sufficient power assist is provided in time when high power output is required, thereby improving the user's riding experience.

[0029] S5: In the single-battery power-assisted section, the remaining power of the first battery and the second battery is identified, and a power-assisted battery is determined based on the remaining power, and power-assisted control is performed on the electric bicycle.

[0030] Specifically, when an electric bicycle enters a single-battery assisted section, it first identifies the remaining charge of the first and second batteries, compares the remaining charge of the two batteries, and selects the most suitable battery to provide assistance, thereby achieving balanced use and optimal management of battery energy. After the comparison is completed, the battery with the larger remaining charge will be selected as the assist battery for the current single-battery assisted section. By selecting the assist battery, the use of the two batteries can be balanced, avoiding the situation where one battery is over-discharged while the other is idle; at the same time, the riding range on a single charge is maximized, and the battery with the larger charge is always used first to avoid a large difference in the remaining charge of the two batteries in the dual-battery assisted section; at the same time, avoiding frequent deep discharge of a single battery is beneficial to extending the overall life of the battery. After the assist battery is determined, the corresponding battery is started to power the electric motor and assist control is performed on the electric bicycle.

[0031] Through the dynamic selection mechanism based on the remaining power, it not only improves the energy utilization efficiency, but also maximizes the riding mileage while ensuring the power-assisting effect, and effectively extends the range of the electric bicycle while ensuring the riding performance.

[0032] S6: In the dual-battery power-assisted section, the first battery and the second battery are switched to a parallel state to form a parallel battery pack to perform power-assisted control on the electric bicycle.

[0033] Specifically, when the e-bike enters a dual-battery power-assisted section, the automatic battery configuration switching mechanism is triggered, and the control circuit connects the first and second batteries, which originally operate independently, into a parallel configuration. In this parallel configuration, both batteries simultaneously power the electric motor, providing higher current output to meet high-power requirements, such as steep uphill slopes or situations requiring rapid acceleration. This parallel configuration not only increases instantaneous available power but also balances the discharge of the two batteries, extending overall battery life. Once in parallel mode, the power assistance level is dynamically adjusted based on road conditions and user needs, such as increasing motor output power, increasing the power assistance ratio, or extending the power assistance duration, to provide an optimal riding experience. This dynamic switching mechanism allows the e-bike to flexibly adjust its battery configuration between different sections of road. On flat roads or downhill slopes, it uses a single battery mode to save energy, while automatically switching to dual-battery parallel mode on sections requiring high power output, thus achieving a balance between energy use and riding performance.

[0034] Through the parallel control of dual batteries, the performance of electric bicycles on difficult road sections is significantly improved. It can not only meet the instantaneous high-power demand, but also extend the overall riding mileage, ensuring the riding comfort of the road section while taking into account the efficient use of energy, thereby comprehensively improving the adaptability and user experience of electric bicycles.

[0035] Furthermore, the embodiment of the present application also includes: On a cloud server, a cycling habit model is established based on the historical cycling data of the target user and stored in correspondence with the target user. The cycling habit model has power-assistance activation thresholds corresponding to different cycling section characteristics. When the cloud server receives the target cycling route, the target cycling route is mapped to a three-dimensional curve coordinate axis to obtain a target cycling curve. A curve reading frame of the cycling habit model is obtained, and the target cycling curve is traversed and identified based on the curve reading frame to obtain a plurality of power-assistance sections.

[0036] In a feasible implementation, a cycling habit model is established in the cloud server based on the historical cycling data of the target user. The cycling habit model is a personalized model for each user, which can reflect the user's power assistance needs under different cycling section characteristics. Among them, the cycling habit model contains the power assistance activation threshold corresponding to the characteristics of different cycling sections, involving data in multiple dimensions such as slope, speed, and cadence. After the cycling habit model is established, it is stored in correspondence with the target user for subsequent quick call and update. When the cloud server receives the target cycling route, it maps the target cycling route to a three-dimensional curve coordinate axis, which includes three dimensions: longitude, latitude, and altitude. Through mapping, the target cycling route is converted into a three-dimensional curve containing elevation information to obtain a target cycling curve, so as to more comprehensively analyze the route characteristics, especially in terms of slope changes.

[0037] Subsequently, the riding habit model corresponding to the target user is called, and the curve reading frame of the model is obtained. The curve reading frame is a sliding window that can move on the target riding curve and read the road section features within the window. Then, based on the curve reading frame, the entire target riding curve is traversed and identified. During the traversal process, the read road section features are compared with the power-assistance activation threshold in the riding habit model. When the features of a certain road section reach or exceed the corresponding power-assistance activation threshold, the road section is marked as a power-assistance road, thereby obtaining multiple road sections that require power-assistance control as multiple power-assistance sections.

[0038] By accurately identifying sections of road requiring power assistance based on each user's personalized needs, it not only considers the objective characteristics of the route but also incorporates the user's subjective riding habits, thereby achieving highly personalized section identification, providing a more accurate foundation for subsequent dynamic power assistance control, and helping to improve the intelligence level and user experience of e-bikes.

[0039] Furthermore, the embodiment of the present application also includes: In the cloud server, multiple user categories are pre-stored, and each user category corresponds to a universal cycling model; a registration request from a target user is received, personal information of the target user is obtained, the user category to which the target user belongs is determined based on the personal information, the target user category is obtained, and a target universal cycling model is determined; historical cycling data of the target user is obtained, and a training data set is generated based on the historical cycling data, the training data set including cycling section features and power-assisted start features; the target universal cycling model is trained using the training data set to obtain a cycling habit model for the target user, including power-assisted start thresholds for different cycling section features.

[0040] In a preferred embodiment, multiple user categories are pre-stored in the cloud server, and the multiple user categories are divided based on factors such as age, gender, and riding experience. Each user category corresponds to a general riding model, which represents the average riding habits and needs of users in this category, and provides a starting point for subsequent personalized model training. When a registration request is received from a target user, the target user's personal information is obtained, including age, height, weight, riding experience, etc. Subsequently, the cloud server classifies the target user into a predefined user category based on this personal information, thereby determining the target user category. After determining the target user category, the general riding model corresponding to the category is selected as the target general riding model, providing a suitable initial model for subsequent personalized model training.

[0041] Subsequently, the historical riding data of the target user is obtained from the target user's previous riding records, including route information, speed, cadence, power assist usage, etc. The historical riding data is processed into a training data set, which contains two types of information, namely riding section characteristics and power assist start-up characteristics. Riding section characteristics include slope, length, road type, etc., while power assist start-up characteristics reflect the user's power assist usage pattern in different situations. Next, the generated training data set is used to train the determined target general riding model, and the target general riding model is trained to a model that is more in line with the target user's personal habits. After the training is completed, a riding habit model for the target user is obtained, which includes the power assist start-up threshold under different riding section characteristics, and can accurately reflect the user's power assist needs under various road conditions.

[0042] By combining the universality of the general model and the specificity of personal data, we first select a suitable general model and then use personal historical data to fine-tune it. This allows us to generate a highly personalized cycling habit model in a relatively short period of time. This not only improves the accuracy and applicability of the model, but also allows us to generate a reasonable cycling habit model even when there is less user data.

[0043] Furthermore, the embodiment of the present application also includes: The target riding curve is divided into a plurality of curve segments according to the curve reading frame; the plurality of curve segments are traversed through the curve reading frame to obtain a current curve segment, and characteristic parameters of the current curve segment are read as current segment characteristics; the current segment characteristics are input into the riding habit model to determine whether a power-assistance activation threshold of the current segment characteristics is met; if so, the current curve segment is marked as a power-assistance segment and added to the plurality of power-assistance segments.

[0044] In one feasible implementation, the target riding curve is first divided into multiple continuous curve segments using a curve reading frame. This allows subsequent analysis to focus on local features, improving recognition accuracy and efficiency. The curve reading frame is then used to sequentially traverse the multiple divided curve segments. During each traversal, the current curve segment is located and its characteristic parameters, including but not limited to slope, length, and curvature, are read. These characteristic parameters are then combined to form the current segment feature.

[0045] The acquired current segment characteristics are then fed into the established riding habits model, which calculates a corresponding predicted power assist demand value based on the input current segment characteristics. This predicted power assist demand value is then compared with the corresponding power assist activation threshold to determine whether power assist is required for the current curve segment. If the judgment result indicates that the current segment characteristics meet the power assist activation threshold, the current curve segment is marked as a power assist segment and added to the list of multiple power assist segments. This enables the conversion from judgment results to specific power assist segments, laying the foundation for subsequent dynamic power assist control.

[0046] By using the curve reading frame, it is possible to conduct detailed analysis of the cycling route and capture local changes in road conditions. Combined with a personalized riding habit model, it can accurately identify each user's actual power assistance needs in different sections of the road. This not only improves the accuracy of power assistance control, but also adapts to the needs of different users and different road conditions, thereby enhancing the intelligence level and user experience of electric bicycles.

[0047] Furthermore, the embodiment of the present application also includes: Based on the historical riding data of the target user, a correspondence between riding mileage and a threshold reduction coefficient is established to obtain a threshold reduction coefficient curve; while obtaining the current road section characteristics, the current riding mileage of the current curve section in the target riding route is obtained, and the current threshold reduction coefficient is determined in combination with the threshold reduction coefficient curve; the power-assistance start threshold of the current road section characteristics is adjusted according to the current threshold reduction coefficient to obtain an adjusted power-assistance start threshold; it is determined whether the current road section characteristics meet the adjusted power-assistance start threshold, and if so, the current curve section is marked as a power-assistance section and added to the multiple power-assistance sections.

[0048] In a preferred embodiment, a method for dynamically adjusting the power-assistance start threshold is provided to more accurately identify power-assistance sections. First, based on the historical riding data of the target user, a correspondence between riding mileage and the threshold reduction coefficient is established, and a threshold reduction coefficient curve is generated by analyzing the changes in the user's power-assistance demand at different riding distances. The threshold reduction coefficient curve shows an upward trend with the increase in riding mileage, reflecting the general rule that the user's power-assistance demand gradually increases during long-distance riding. While obtaining the characteristics of the current section, the position of the current curve segment in the entire target riding route, that is, the current riding mileage, is determined. The current riding mileage is input into the threshold reduction coefficient curve to determine the current threshold reduction coefficient, which reflects the target user's fatigue level and changes in power-assistance demand during the current riding stage.

[0049] The determined current threshold reduction coefficient is then used to adjust the original power-assisted activation threshold corresponding to the current road segment characteristics. The original power-assisted activation threshold is multiplied by the current threshold reduction coefficient, thereby lowering the threshold for power-assisted activation. This results in a power-assisted activation threshold that is dynamically adjusted based on the riding progress, yielding the adjusted power-assisted activation threshold. Subsequently, the current road segment characteristics are compared with the adjusted power-assisted activation threshold. If the current road segment characteristics meet the adjusted power-assisted activation threshold, the current curve segment is marked as a power-assisted road segment and added to the multiple power-assisted road segments.

[0050] By dynamically adjusting the power-assistance start threshold, the power-assistance of electric bicycles can be more in line with the actual needs of users. It not only takes into account the objective characteristics of the road section, but also takes into account the target user's riding mileage, thereby achieving more refined and personalized power-assistance control. It can provide more power-assistance in time when the user is tired, thereby improving the comfort and safety of long-distance riding.

[0051] Furthermore, the embodiment of the present application also includes: Traverse multiple power-assisted sections to obtain a first power-assisted section, and extract the current section feature of the first power-assisted section to obtain the first section feature; determine the power-assisted power requirement under the first section feature based on the first section feature and the historical riding data; read the power-assisted power thresholds of the first battery and the second battery; when the power-assisted power requirement is greater than the power-assisted power threshold, determine the first power-assisted section as a dual-battery power-assisted section and add it to multiple dual-battery power-assisted sections; when the power-assisted power requirement is less than or equal to the power-assisted power threshold, determine the first power-assisted section as a single-battery power-assisted section and add it to multiple single-battery power-assisted sections.

[0052] In a feasible implementation, first, traverse the multiple identified power-assisted sections, obtain one power-assisted section each time as the first power-assisted section, and extract its current section features to obtain the first section features. Then, based on the first section features and the user's historical riding data, determine the power-assisted demand under the first section features. Specifically, match the current first section features with the section features in the historical riding data to find the most similar situation and obtain the target user's riding record under similar section features. Based on the matched riding records, obtain the power-assisted demand that the target user usually needs under such road conditions. For example, use a machine learning algorithm to train a prediction model based on a large amount of historical data, input the first section features, output the predicted power-assisted demand, and obtain the power-assisted demand under the first section features.

[0053] At the same time, the assist power thresholds of the first battery and the second battery are read. The assist power threshold is determined by the performance parameters and safety considerations of the battery, and represents the maximum assist power that a single battery can provide safely and continuously. Then, the determined assist power demand is compared with the assist power threshold. If the assist power demand is greater than the assist power threshold, it means that a single battery cannot meet the power demand of the section. In this case, the first assist section is determined as a dual-battery assist section, and it is added to multiple dual-battery assist sections, which means that two batteries will be enabled to work in parallel in this section to provide sufficient assist. If the assist power demand is less than or equal to the assist power threshold, it means that a single battery can meet the power demand of the section. In this case, the first assist section is determined as a single-battery assist section, and it is added to multiple single-battery assist sections, which means that only one battery needs to be enabled in this section to provide sufficient assist, thereby achieving the purpose of energy saving.

[0054] Furthermore, the embodiment of the present application also includes: Obtain the remaining power of a first battery and a second battery, which are respectively the first battery remaining power and the second battery remaining power; compare the first battery remaining power and the second battery remaining power; if the first battery remaining power is greater than or equal to the second battery remaining power, use the first battery as a booster battery; if the first battery remaining power is less than the second battery remaining power, use the second battery as a booster battery.

[0055] In a feasible implementation, first, the remaining power information of the first battery and the second battery is obtained, and the remaining power of the first battery obtained is recorded as the first battery remaining power, and the remaining power of the second battery is recorded as the second battery remaining power. Then, the first battery remaining power is compared with the second battery remaining power. If the comparison result shows that the first battery remaining power is greater than or equal to the second battery remaining power, the first battery is designated as the power-assisting battery, that is, in the subsequent single-battery power-assisting section, the first battery is used to provide power support first, which helps to balance the use of the two batteries and avoid excessive discharge of a certain battery. If the first battery remaining power is less than the second battery remaining power, the second battery will be designated as the power-assisting battery. In this case, the subsequent single-battery power-assisting section will mainly rely on the second battery to provide power support.

[0056] Through the dynamic selection mechanism based on the remaining power, balanced battery usage can be achieved, avoiding frequent deep discharge of a battery, which is beneficial to extending the overall battery life. At the same time, it ensures that batteries with sufficient power are always used, reducing the need to replace batteries during riding and improving the user experience.

[0057] In summary, the electric bicycle dynamic power assist control method provided by the embodiments of the present application has the following technical effects: The electric bicycle is equipped with two independently usable power supply batteries, a first battery and a second battery, and a user input terminal. The first and second batteries are identical, laying the hardware foundation for the electric bicycle's dynamic power assist control. The user input terminal obtains the electric bicycle's current location and the target user's destination information, which is then transmitted to a cloud server to determine the target riding route, providing the necessary data for subsequent route segment analysis. The target route is identified based on the target user's historical riding data, and multiple power assist segments are obtained. This intelligent segmentation of the route is implemented, identifying sections requiring power assist and paving the way for subsequent refined control. Based on the historical riding data, the multiple power assist segments are divided into multiple single-battery power assist segments and multiple dual-battery power assist segments. The segment classification is further refined, and the required power assist level for each segment is predicted based on historical data, providing a basis for subsequent dynamic battery usage strategies. In single-battery power assist segments, the remaining charge of the first and second batteries is identified, and the power assist battery is determined based on the remaining charge. Power assist control is implemented for the electric bicycle, implementing intelligent battery management for single-battery segments, optimizing energy efficiency by selecting the battery with the most appropriate remaining charge to provide power assist. In dual-battery assisted sections, the first battery and the second battery are switched to a parallel state to form a parallel battery pack to control the power assist of the electric bicycle. For sections requiring greater power assist, stronger power support is provided by connecting two batteries in parallel to ensure performance under high demand conditions.

[0058] The second embodiment is based on the same inventive concept as the electric bicycle dynamic power assist control method in the above embodiment. Figure 2 As shown, an embodiment of the present application provides a dynamic power-assistance control device for an electric bicycle, the device comprising: The hardware configuration module 11 is used to equip the electric bicycle with two independently usable power supply batteries, namely a first battery and a second battery, and to configure a user input terminal, wherein the first battery and the second battery are the same; The route planning module 12 is used to obtain the current location information of the electric bicycle and the destination information of the target user through the user input terminal, send them to the cloud server, and determine the target riding route; a road segment identification module 13, configured to identify road segments of the target cycling route based on the historical cycling data of the target user, and obtain a plurality of power-assisted road segments; a power-assisted classification module 14 for dividing the plurality of power-assisted sections based on the historical riding data into a plurality of single-battery power-assisted sections and a plurality of dual-battery power-assisted sections; a single battery control module 15 for identifying the remaining power of the first battery and the second battery in the single battery power-assisted section, determining the power-assisted battery based on the remaining power, and performing power-assisted control on the electric bicycle; The dual-battery control module 16 is used to switch the first battery and the second battery into a parallel state to form a parallel battery pack in the dual-battery power-assisted section, so as to perform power-assisted control on the electric bicycle.

[0059] Furthermore, the road segment identification module 13 includes the following execution steps: On a cloud server, a cycling habit model is established based on the historical cycling data of the target user and stored in correspondence with the target user, wherein the cycling habit model has power assist activation thresholds for different cycling section characteristics; After receiving the target cycling route, the cloud server maps the target cycling route to a three-dimensional curve coordinate axis to obtain a target cycling curve; A curve reading frame of the riding habit model is obtained, and the target riding curve is traversed and identified based on the curve reading frame to obtain a plurality of power-assisted road sections.

[0060] Furthermore, the road segment identification module 13 further includes the following execution steps: In the cloud server, a plurality of user categories are pre-stored, each user category corresponding to a general riding model; receiving a registration request from a target user, obtaining personal information of the target user, determining a user category to which the target user belongs based on the personal information, obtaining the target user category, and determining a target general cycling model; Obtaining historical riding data of a target user, and generating a training data set based on the historical riding data, wherein the training data set includes riding section features and power-assisted start features; The target universal cycling model is trained using the training data set to obtain a cycling habit model for the target user, including power-assistance activation thresholds for different cycling section characteristics.

[0061] Furthermore, the road segment identification module 13 further includes the following execution steps: dividing the target riding curve into a plurality of curve segments according to the curve reading frame; Traversing multiple curve segments through the curve reading frame to obtain the current curve segment, and reading the characteristic parameters of the current curve segment as the current road segment feature; Inputting the current road section characteristics into the riding habit model to determine whether the power assist activation threshold of the current road section characteristics is met; If the conditions are met, the current curve segment is marked as an assisted road segment and added to the multiple assisted road segments.

[0062] Furthermore, the road segment identification module 13 further includes the following execution steps: Establishing a correspondence between riding mileage and a threshold reduction coefficient based on the target user's historical riding data to obtain a threshold reduction coefficient curve; While obtaining the current road segment characteristics, obtaining the current cycling mileage of the current curve segment in the target cycling route, and determining the current threshold reduction coefficient in combination with the threshold reduction coefficient curve; adjusting the power-assisted activation threshold of the current road section characteristics according to the current threshold reduction coefficient to obtain an adjusted power-assisted activation threshold; It is determined whether the characteristics of the current road section meet the adjustment power-assistance start threshold. If so, the current curve section is marked as a power-assistance section and added to the multiple power-assistance sections.

[0063] Furthermore, the assistance classification module 14 includes the following execution steps: Traversing multiple assisted road sections, obtaining a first assisted road section, and extracting the current road section feature of the first assisted road section to obtain the first road section feature; determining, based on the first road section characteristics and the historical riding data, an assist power requirement under the first road section characteristics; Reading the assist power thresholds of the first battery and the second battery; When the power-assistance demand is greater than the power-assistance threshold, determining the first power-assistance section as a dual-battery power-assistance section and adding the first power-assistance section to a plurality of dual-battery power-assistance sections; When the assist power requirement is less than or equal to the assist power threshold, the first assist section is determined as a single battery assist section and added to a plurality of single battery assist sections.

[0064] Furthermore, the single battery control module 15 includes the following execution steps: Obtaining the remaining power of the first battery and the second battery, which are the first battery remaining power and the second battery remaining power respectively; comparing the first battery level and the second battery level; If the remaining charge of the first battery is greater than or equal to the remaining charge of the second battery, use the first battery as a booster battery; If the remaining charge of the first battery is less than the remaining charge of the second battery, the second battery is used as a booster battery.

[0065] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0066] Furthermore, the terms "first" or "second" as described above may not only represent an order relationship but may also represent a specific concept and / or refer to the selectability of multiple elements, either individually or in combination. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, if such modifications and variations fall within the scope of this application and its equivalents, this application is intended to include such modifications and variations.

Claims

1. A dynamic power assist control method for an electric bicycle, characterized in that: The method comprises: The electric bicycle is equipped with two independently usable power supply batteries, namely a first battery and a second battery, and is provided with a user input terminal, wherein the first battery is the same as the second battery; Obtaining the current location information of the electric bicycle and the destination information of the target user through the user input terminal, sending the information to the cloud server, and determining the target riding route; Identify sections of the target cycling route based on the historical cycling data of the target user to obtain multiple assisting sections; Based on the historical riding data, the plurality of power-assisted sections are divided into a plurality of single-battery power-assisted sections and a plurality of dual-battery power-assisted sections; In the single-battery power-assisted section, identifying the remaining power of the first battery and the second battery, determining the power-assisted battery based on the remaining power, and performing power-assisted control on the electric bicycle; In the dual-battery power-assisted section, the first battery and the second battery are switched to a parallel state to form a parallel battery pack to perform power-assisted control on the electric bicycle.

2. The electric bicycle dynamic power assist control method according to claim 1, characterized in that: Identify the target cycling route according to the historical cycling data of the target user, and obtain multiple assisting segments, including: On a cloud server, a cycling habit model is established based on the historical cycling data of the target user and stored in correspondence with the target user, wherein the cycling habit model has power assist activation thresholds for different cycling section characteristics; After receiving the target cycling route, the cloud server maps the target cycling route to a three-dimensional curve coordinate axis to obtain a target cycling curve; A curve reading frame of the riding habit model is obtained, and the target riding curve is traversed and identified based on the curve reading frame to obtain a plurality of power-assisted road sections.

3. The electric bicycle dynamic power assist control method according to claim 2, characterized in that: A cycling habit model is established based on the historical cycling data of the target user, including: In the cloud server, a plurality of user categories are pre-stored, each user category corresponding to a general riding model; receiving a registration request from a target user, obtaining personal information of the target user, determining a user category to which the target user belongs based on the personal information, obtaining the target user category, and determining a target general cycling model; Obtaining historical riding data of a target user, and generating a training data set based on the historical riding data, wherein the training data set includes riding section features and power-assisted start features; The target universal cycling model is trained using the training data set to obtain a cycling habit model for the target user, including power-assistance activation thresholds for different cycling section characteristics.

4. The electric bicycle dynamic power assist control method according to claim 2, characterized in that: The target riding curve is traversed and identified based on the curve reading frame to obtain multiple power-assisted sections, including: dividing the target riding curve into a plurality of curve segments according to the curve reading frame; Traversing multiple curve segments through the curve reading frame to obtain the current curve segment, and reading the characteristic parameters of the current curve segment as the current road segment feature; Inputting the current road section characteristics into the riding habit model to determine whether the power assist activation threshold of the current road section characteristics is met; If the conditions are met, the current curve segment is marked as an assisted road segment and added to the multiple assisted road segments.

5. The electric bicycle dynamic power assist control method according to claim 4, characterized in that: The method further comprises: Establishing a correspondence between riding mileage and a threshold reduction coefficient based on the target user's historical riding data to obtain a threshold reduction coefficient curve; While obtaining the current road segment characteristics, obtaining the current cycling mileage of the current curve segment in the target cycling route, and determining the current threshold reduction coefficient in combination with the threshold reduction coefficient curve; adjusting the power-assisted activation threshold of the current road section characteristics according to the current threshold reduction coefficient to obtain an adjusted power-assisted activation threshold; It is determined whether the characteristics of the current road section meet the adjustment power-assistance start threshold. If so, the current curve section is marked as a power-assistance section and added to the multiple power-assistance sections.

6. The electric bicycle dynamic power assist control method according to claim 4, characterized in that: Based on the historical riding data, multiple power-assisted sections are divided into multiple single-battery power-assisted sections and multiple dual-battery power-assisted sections, including: Traversing multiple assisted road sections, obtaining a first assisted road section, and extracting the current road section feature of the first assisted road section to obtain the first road section feature; determining, based on the first road section characteristics and the historical riding data, an assist power requirement under the first road section characteristics; Reading the assist power thresholds of the first battery and the second battery; When the power-assistance demand is greater than the power-assistance threshold, determining the first power-assistance section as a dual-battery power-assistance section and adding the first power-assistance section to a plurality of dual-battery power-assistance sections; When the assist power requirement is less than or equal to the assist power threshold, the first assist section is determined as a single battery assist section and added to a plurality of single battery assist sections.

7. The electric bicycle dynamic power assist control method according to claim 1, characterized in that: Determining a boost battery based on the remaining power includes: Obtaining the remaining power of the first battery and the second battery, which are the first battery remaining power and the second battery remaining power respectively; comparing the first battery level and the second battery level; If the remaining charge of the first battery is greater than or equal to the remaining charge of the second battery, use the first battery as a booster battery; If the remaining charge of the first battery is less than the remaining charge of the second battery, the second battery is used as a booster battery.

8. A dynamic power-assistance control system for an electric bicycle, used to implement the dynamic power-assistance control method for an electric bicycle according to any one of claims 1 to 7, characterized in that: The system comprises: A hardware configuration module is used to equip the electric bicycle with two independently usable power supply batteries, namely a first battery and a second battery, and to configure a user input terminal, wherein the first battery and the second battery are identical; A route planning module is used to obtain the current location information of the electric bicycle and the destination information of the target user through the user input terminal, send them to the cloud server, and determine the target riding route; A road segment identification module is used to identify the road segments of the target cycling route based on the historical cycling data of the target user and obtain multiple assisting road segments; a power-assisted classification module, configured to classify the plurality of power-assisted sections based on the historical riding data to obtain a plurality of single-battery power-assisted sections and a plurality of dual-battery power-assisted sections; a single battery control module, configured to identify the remaining power of the first battery and the second battery in the single battery power-assisted section, determine the power-assisted battery based on the remaining power, and perform power-assisted control on the electric bicycle; The dual-battery control module is used to switch the first battery and the second battery into a parallel state in the dual-battery power-assisted section to form a parallel battery pack to perform power-assisted control on the electric bicycle.

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