Method for operating electric bicycle, electronic device, storage medium and program product

Abstract

The embodiment of the invention provides a method for operating an electric bicycle, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring comprehensive energy consumption prediction information, wherein the comprehensive energy consumption prediction information at least comprises the current position of the electric bicycle, road condition information related to the current position and user information of a user who is about to use the electric bicycle; determining energy consumption prediction data of the user in the process of riding the electric bicycle based on the comprehensive energy consumption prediction information; determining a lower limit electric quantity requirement for allowing the user to ride the electric bicycle based on the energy consumption prediction data; and controlling operation of the electric bicycle based on the lower limit electric quantity requirement. According to the embodiment of the invention, on the premise that normal riding of a user is not influenced, real-time and accurate electric quantity management and distance prediction can be provided, intelligent interaction with real-time environmental factors is realized, and a bicycle using decision is optimized.

Description

Technical Field

[0001] The exemplary embodiments disclosed herein generally relate to the field of electric bicycles, and more specifically, to methods, electronic devices, storage media, and program products for operating electric bicycles. Background Technology

[0002] In the context of today's intelligent transportation development, e-bikes, as a convenient mode of transportation, are gradually gaining popularity among users. Through a dedicated mobile application, users can check their e-bike's battery level in real time. This not only helps them plan their routes effectively but also reduces unexpected breakdowns due to low battery. Simultaneously, the application provides the location of nearby charging stations, allowing users to easily find charging facilities and enhancing the flexibility and convenience of their travel. This feature makes e-bike use more intelligent, meeting users' needs for short-distance travel. Summary of the Invention

[0003] In a first aspect of this disclosure, a method for operating an electric bicycle is provided. This method can be executed by a server. The method includes: acquiring comprehensive energy consumption prediction information, which includes at least the current location of the electric bicycle, road condition information related to the current location, and user information of the user of the electric bicycle to be used; determining energy consumption prediction data for the user during riding the electric bicycle based on the comprehensive energy consumption prediction information; determining a lower limit energy requirement for allowing the user to ride the electric bicycle based on the energy consumption prediction data; and controlling the operation of the electric bicycle based on the lower limit energy requirement.

[0004] The embodiments of this disclosure can provide real-time and accurate power management and distance prediction without affecting the user's normal riding, and can achieve intelligent interaction with real-time environmental factors to optimize vehicle usage decisions. In this case, the lower limit of the battery level that allows the user to ride the e-bike is no longer a fixed threshold, but can be dynamically adjusted according to real-time environmental factors and user information, thereby improving the overall energy utilization efficiency of the system and reducing vehicle idleness due to power issues. Further benefits of the embodiments of this disclosure will be further described below.

[0005] In some embodiments, the method further includes: determining the destination of the user riding the electric bicycle; acquiring distance information from the destination and distribution information of charging stations for the electric bicycle; determining a power warning level for the electric bicycle based on energy consumption prediction data, distance information, and distribution information; and causing at least one of the electric bicycle and the user's terminal device to issue a reminder message about the power level based on the power warning level.

[0006] In some embodiments, determining the destination includes: determining the user's historical cycling data based on user information; and determining the destination based on the historical cycling data.

[0007] In some embodiments, determining the destination further includes: obtaining user input about the destination from the user's terminal device; and determining the destination based on the input.

[0008] In some embodiments, controlling the operation of the electric bicycle includes: determining an upper limit for the output power of the electric bicycle's motor based on road condition information and the remaining charge of the electric bicycle's battery; and sending the upper limit for the output power to the electric bicycle so that the electric bicycle adjusts the output power of the motor based on the upper limit for the output power and the user's input angle to the handlebars.

[0009] In some embodiments, controlling the operation of the electric bicycle further includes: determining the riding route of the user riding the electric bicycle based on energy consumption prediction data and the remaining power of the electric bicycle's battery; and sending the riding route to at least one of the electric bicycle and the user's terminal device to allow the user to ride the electric bicycle based on the riding route.

[0010] In some embodiments, determining energy consumption prediction data includes: determining energy consumption prediction data of a user during the riding of an electric bicycle using an energy consumption prediction model and based on comprehensive energy consumption prediction information, wherein the energy consumption prediction model is trained based on historical data obtained by the user while riding the electric bicycle.

[0011] In some embodiments, the method further includes: adjusting virtual resources related to the user in response to determining that the user's riding of the electric bicycle meets predetermined conditions, wherein the predetermined conditions include at least one of the following: the battery level of the electric bicycle being ridden is lower than a battery threshold; the user is riding according to a pushed riding route; or the peak power output of the motor during riding is not greater than a power threshold or the peak speed during riding is not greater than a predetermined peak speed.

[0012] In a second aspect of this disclosure, a method for operating an electric bicycle is provided. This method can be executed by electronic equipment of the electric bicycle. The method includes: in response to a user's operation of the electric bicycle to prepare for riding, acquiring the current location of the electric bicycle and user information of the user intending to use the electric bicycle; sending the current location and user information to a remote device, so that the remote device determines energy consumption prediction data for the user during riding the electric bicycle based on comprehensive energy consumption prediction information including user information, current location, and road condition information related to the current location; acquiring a control command from the remote device, the control command being determined at least based on a lower limit energy requirement, wherein the lower limit energy requirement is determined based on the energy consumption prediction data; and controlling the operation of the electric bicycle based on the control command.

[0013] In some embodiments, the method further includes: receiving a power warning level from a remote device to issue a power reminder to the user based on the power warning level.

[0014] In some embodiments, controlling the operation of the electric bicycle includes: obtaining the upper limit of the output power of the electric bicycle's motor from a remote device; obtaining the user's input angle to the handlebars; and adjusting the motor's output power based on the upper limit of the output power and the input angle.

[0015] In some embodiments, controlling the operation of the electric bicycle further includes: obtaining the riding route of the user riding the electric bicycle from a remote device; and presenting the riding route to allow the user to ride the electric bicycle based on the riding route.

[0016] In some embodiments, the method further includes, in response to determining that the user has not yet reached the destination while riding the e-bike and that the e-bike's battery level is below a lower limit battery level indicated by the lower limit battery requirement, causing the e-bike to enter a power-saving mode, wherein in the power-saving mode, the output power of the e-bike's motor is not higher than a power-saving power threshold and / or the speed of the e-bike is not higher than a power-saving speed threshold.

[0017] In a third aspect of this disclosure, an electronic device is provided. The electronic device includes at least one processing unit; and at least one memory coupled to the at least one processing unit and storing machine-executable instructions that, when executed by the at least one processing unit, cause the device to perform the method according to the first or second aspect described above.

[0018] In a fourth aspect of this disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program that can be executed by a processor to perform the methods described according to a first or second aspect of this disclosure.

[0019] In a fifth aspect of this disclosure, a computer program product is provided. The computer program product includes computer-executable instructions that, when executed by a processor, implement the method described according to a first or second aspect of this disclosure.

[0020] It should be understood that the content described in this summary section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0021] The above and other features, advantages, and aspects of various implementations of this disclosure will become more apparent in the following detailed description, taken in conjunction with the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0022] Figure 1 A block diagram of an example environment in which embodiments of the present disclosure can be implemented is shown;

[0023] Figure 2 A flowchart illustrating an example process of a method for operating an electric bicycle, performed by a server, according to some embodiments of the present disclosure;

[0024] Figure 3 A flowchart illustrating an example process of a method for operating a motorcycle, performed by electronic equipment of a motorcycle according to some embodiments of the present disclosure; and

[0025] Figure 4 A block diagram of an electronic device in which one or more embodiments of the present disclosure may be implemented is shown. Detailed Implementation

[0026] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0027] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may also be included below.

[0028] In this specification and the embodiments, any processing of personal information will be carried out only under the premise of legality (such as obtaining the consent of the personal information subject, or being necessary for the performance of a contract), and will only be carried out within the scope stipulated or agreed upon. A user's refusal to process personal information other than that necessary for basic functions will not affect the user's use of basic functions.

[0029] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0030] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure through appropriate means in accordance with relevant laws and regulations, and user authorization should be obtained.

[0031] For example, in response to receiving a user's active request, a prompt message is sent to the user to clearly inform the user that the requested operation will require the acquisition and use of the user's personal information, thereby enabling the user to choose whether to provide personal information to the software or hardware such as electronic devices, applications, servers or storage media that perform the operation of the technical solution disclosed herein, based on the prompt message.

[0032] As an optional but non-restrictive implementation, in response to a user's active request, a prompt message can be sent to the user, for example, via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose whether to "agree" or "disagree" to provide personal information to the electronic device.

[0033] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0034] The term "in response to" as used herein refers to a state in which a corresponding event occurs or a condition is satisfied. It will be understood that the timing of subsequent actions performed in response to such event or condition is not necessarily strongly correlated with the time when the event occurs or the condition is met. For example, in some cases, subsequent actions may be performed immediately upon the occurrence of the event or the fulfillment of the condition; while in others, they may be performed some time after the occurrence of the event or the fulfillment of the condition.

[0035] In e-bike management systems, fixed battery threshold management is widely used. This method sets a lower limit for the battery level of the e-bike under different conditions to ensure that the vehicle always maintains sufficient battery power during operation. In this case, users need to constantly and actively check the battery information of the e-bike to ensure that they do not have to stop riding due to battery issues.

[0036] First, relying on users to actively check battery information can lead to distraction. While mobile apps offer convenient battery monitoring functions, users can easily become distracted while riding, affecting safe driving. This method of obtaining information requires users to frequently look at their phones, which undoubtedly interferes with their attention and increases the risk of accidents.

[0037] Secondly, fixed battery threshold management methods lack flexibility, potentially leading to wasted battery power or a degraded user experience. In some cases, the actual battery demand of an e-bike may not match the set threshold, causing premature battery depletion. For example, if a user's route is short but the threshold is set too high, it will result in unnecessary battery waste. Furthermore, fixed thresholds may not adapt to the riding habits and needs of different users, thus reducing the overall user experience.

[0038] Finally, current e-bike battery management systems lack consideration for real-time environmental factors and individual user circumstances, resulting in inaccurate battery predictions. Current systems often fail to collect and analyze information such as weather, traffic conditions, and user riding history in real time, significantly reducing the accuracy of battery predictions. For example, in severe weather conditions, e-bike battery consumption may increase significantly, but fixed management methods cannot be dynamically adjusted, thus failing to meet users' actual needs. Such shortcomings not only affect user trust in e-bikes but also limit their further development in the market.

[0039] The embodiments of this disclosure provide a method for operating an electric bicycle to solve, or at least partially solve, the aforementioned problems or other potential problems in conventional electric bicycle power management methods.

[0040] According to embodiments of this disclosure, comprehensive energy consumption prediction information, including the current location of the electric bicycle, road condition information related to the current location, and user information of the user who is about to use the electric bicycle, is obtained to determine the energy consumption prediction data of the user during the riding of the electric bicycle; then, the lower limit of the power requirement for allowing the user to ride the electric bicycle is determined based on the energy consumption prediction data, and the operation of the electric bicycle is controlled based on the lower limit of the power requirement.

[0041] The embodiments of this disclosure can provide real-time and accurate power management and distance prediction without affecting the user's normal riding, and can achieve intelligent interaction with real-time environmental factors to optimize vehicle usage decisions. In this case, the lower limit of the battery level that allows the user to ride the e-bike is no longer a fixed threshold, but can be dynamically adjusted according to real-time environmental factors and user information, thereby improving the overall energy utilization efficiency of the system and reducing vehicle idleness due to power issues. Further benefits of the embodiments of this disclosure will be further described below.

[0042] In the following text, we will first refer to Figure 1 This describes an example environment that can be implemented according to embodiments of the present disclosure.

[0043] Figure 1A schematic diagram of an example environment in which embodiments of the present disclosure can be implemented is shown. In this environment, electronic equipment is deployed in the motorcycle. The electronic equipment is capable of communicating with a server to perform various functions of the motorcycle. Output devices may also be present at appropriate locations on the motorcycle, such as, but not limited to, at least one of, the following: a display screen, indicator lights, and a speaker. The output devices can display various information about the motorcycle, such as battery level, unlocking information, route information, etc., and can also provide reminders to the user, which will be further described below.

[0044] The electric bicycle can be a shared electric bicycle. Users can associate their terminal devices with the electronic devices of the electric bicycle through appropriate means to use various functions of the vehicle. These appropriate means may include, but are not limited to: scanning identification codes such as QR codes on the vehicle; touching predetermined parts of the vehicle through means such as near field communication (NFC).

[0045] The terminal devices mentioned herein can operate on suitable electronic devices. These electronic devices can be any type of computing-capable device, including terminal devices or server devices. Terminal devices can be any type of mobile terminal, fixed terminal, or portable terminal, including mobile phones, desktop computers, laptop computers, notebook computers, netbook computers, tablet computers, media computers, multimedia tablets, personal communication system (PCS) devices, personal navigation devices, personal digital assistants (PDAs), audio / video players, digital cameras / camcorders, positioning devices, television receivers, radio receivers, e-book devices, gaming devices, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. Servers mentioned herein may include, for example, computing systems / servers, such as mainframes, edge computing nodes, computing devices in cloud environments, etc. It should be understood that the structure and function of the environment are described for illustrative purposes only and do not imply any limitation on the scope of this disclosure.

[0046] For example, if a user wants to ride an e-bike, they can scan the QR code on the bike. After the user's device and the e-bike's electronic equipment are linked, the e-bike's electronic equipment obtains information from the user's device and user information, and sends this information to the server as part of the order information. The server then controls the e-bike's operation based on the obtained information. These operations include, but are not limited to, at least one of the following: unlocking the e-bike to allow the user to ride; alerting the user to the e-bike's battery level via the e-bike's output device; limiting the e-bike's peak output power; and disabling the operation and providing corresponding information due to low battery levels, etc. These will be further explained below.

[0047] It should be understood that the structure and function of the environment are described for illustrative purposes only and do not imply any limitation on the scope of this disclosure.

[0048] The method according to embodiments of this disclosure will now be described by describing the use of an electric bicycle. It should be understood that the process described below is merely illustrative and is not intended to limit the scope of protection of this disclosure.

[0049] As illustrated in the previous example, users can establish a connection between their mobile devices and the e-bike's electronic systems by scanning a QR code on the vehicle. Data transmission after connection can be achieved via Bluetooth, Wi-Fi, Near Field Communication (NFC), or cellular networks. The e-bike's electronic systems then retrieve relevant information from the user's mobile device (such as location information) and user information. User information may include, for example, the user's identifier and order details.

[0050] The electric bicycle's electronic devices send this information to the server. It should be understood that, in addition to this information, the electric bicycle's electronic devices also send information such as the bicycle's current location and battery level to the server. After obtaining this data, the server will at least obtain traffic information related to the electric bicycle's current location. This traffic information can include: road congestion information, weather conditions, road morphology information, etc. Road congestion information refers to real-time road congestion index information; weather conditions can include real-time weather conditions, such as whether it is raining or snowing, wind speed, and whether there is fog. Road morphology information can include whether the road has inclines or declines, whether there are narrow roads, and whether there are one-way streets. This information can be obtained through appropriate means, which will not be elaborated on further below. Traffic information can also be referred to as real-time environmental information.

[0051] After obtaining the user's identifier (such as user account), the server will also obtain information such as the user's historical order information and historical riding data, which will be used as updated user information for subsequent energy consumption prediction. This will be further explained below.

[0052] In traditional solutions, the server does not obtain this real-time environmental information. Instead, it directly determines whether to unlock and allow the user to start the e-bike by judging whether the battery level is higher than a predetermined threshold. For example, in a traditional solution, if the battery level is determined to be below 20%, the user may not be allowed to ride. This results in a poor user experience for most short-distance users and also wastes vehicle resources.

[0053] The method according to embodiments of this disclosure determines energy consumption prediction data for a user riding the electric bicycle 1021 by acquiring comprehensive energy consumption prediction information, including at least the current location of the electric bicycle 1021, road condition information related to the current location, and user information of the user who is to use the electric bicycle 1021. The server 110 then determines a lower limit of battery power required for allowing the user to ride the electric bicycle 1021 based on the energy consumption prediction data, and controls the operation of the electric bicycle 1021 based on the lower limit of battery power required.

[0054] For example, in some embodiments, based on user information such as the location information of the electric bicycle and the user's order information, the server 110 can determine that the user's current ride is a short-distance ride, close to the destination, and, based on historical orders and historical riding data, that the user typically rides smoothly without sudden acceleration or deceleration. The server 110 further determines, based on road condition information, that the congestion index is low and the weather conditions are good. In this case, the server 110 will set the minimum battery level requirement for allowing the user to ride the electric bicycle 1021 to a low value, such as 8% or any other appropriate value, thereby facilitating the user's journey to their destination or the nearest charging station.

[0055] Of course, in some embodiments, the lower limit energy requirement can also be set based on the condition and information of the vehicle or battery itself. For example, the lower limit energy requirement of the battery can be determined based on the energy consumption prediction data mentioned above, while also taking into account information such as the battery's service life, brand, and rated capacity.

[0056] In other words, the solution according to the embodiments of this disclosure can dynamically adjust the lower limit of battery power required for users to ride the vehicle based on real-time environmental information and user information. Compared with the electric bicycle 1021 which uses a fixed lower limit of battery power, this solution can improve the user experience while further exploring the potential of low-battery electric bicycles and improving the utilization efficiency and value of electric bicycle 1021.

[0057] In some embodiments, the server 110 can determine the destination of the user's electric bicycle 1021 by appropriate means. For example, in some embodiments, the server 110 can determine the user's historical riding data based on user information, and determine the user's destination based on the historical riding data. For example, if historical riding data shows that the user rides to a certain residential area every afternoon after get off work, then the server 110 can estimate that the user's destination that afternoon is also likely to be that residential area, and will then determine that residential area as the destination and proceed with subsequent operations.

[0058] If the user fails to ride to the destination as determined by the above method, resulting in the user being unable to ride to the new destination before the lower limit of the power requirement, the method according to the embodiments of this disclosure can also activate the power saving mode, thereby using the emergency reserve power of the electric bicycle 1021 to allow the user to ride to the new destination or reach the nearest charging station, which will be further explained later.

[0059] In some embodiments, server 110 can also determine the destination based on the user's input of the destination on the terminal device. For example, in some cases, there may be an area on the user interface displayed on the terminal device where the user can input the destination for this motorcycle ride. Thus, server 110 can determine the destination based on the user's input.

[0060] In some embodiments, energy consumption prediction data can be more accurately determined based on comprehensive energy consumption prediction information and machine learning algorithms. For example, in some embodiments, server 110 can determine the user's energy consumption prediction data during riding the electric bicycle 1021 using an energy consumption prediction model and based on comprehensive energy consumption prediction information. The energy consumption prediction model can be a machine learning model that can be trained by analyzing historical data obtained by the user during riding the electric bicycle 1021. For example, the historical data used for training may include the user's historical riding data, such as riding time, distance, speed, terrain conditions, and environmental factors. By using this training data, the energy consumption prediction model can gradually optimize its predictive ability, thereby better meeting the user's energy consumption needs in different riding scenarios.

[0061] Energy consumption prediction models can be trained by collecting anonymized usage data, thereby improving the performance of both the model and the system. Furthermore, these models can undergo in-depth learning on a specific user to analyze behavioral patterns and provide more personalized services.

[0062] Furthermore, server 110 can also interface with the city management system. This interface can further optimize the layout of charging stations and traffic planning for electric bicycles 1021. By integrating data from traffic flow, user demand, and environmental changes, city managers can develop more scientific and rational charging station distribution strategies to meet the growing demand for electric bicycles 1021. Simultaneously, this collaboration can optimize overall traffic planning, improve urban traffic flow and sustainability, and provide residents with more convenient and efficient travel options.

[0063] In some embodiments, server 110 can also perform dynamic battery threshold management for electric bicycle 1021. Specifically, after determining the user's destination using the method mentioned above, server 110 can then obtain distance information to the destination and the distribution information of charging stations for electric bicycle 1021. Server 110 determines the battery warning level for electric bicycle 1021 based on energy consumption prediction data, distance information, and distribution information. After determining the battery warning level, server 110 can cause at least one of electric bicycle 1021 and user's terminal device to issue a battery reminder message based on the battery warning level.

[0064] For example, in some embodiments, if the user's destination is far away, the riding time is long, or the number of charging stations along the way is small, the battery warning level can be set slightly higher, such as 15% or any other appropriate value. For example, if the server 110 determines that the user's battery level may fall below 15% during the riding under the above circumstances, it will pop up a reminder in an appropriate manner, which may include, but is not limited to, at least one of the following: outputting the battery reminder through the output device 134 of the electric bicycle 1021, such as an indicator light and / or a speaker, or through the user's terminal device.

[0065] In some embodiments, if the user's destination is nearby and / or there are many charging stations along the way, the warning level can be set lower, such as 10% or any other suitable value. In this case, if the server 110 determines that the user's battery level may drop below 10% during the ride, it will pop up a reminder in an appropriate manner, which may include, but is not limited to, at least one of the following: outputting a battery level reminder through an output device 134 of the electric bicycle 1021, such as an indicator light and / or a speaker, or through the user's terminal device.

[0066] This reminder can be given in advance after the user has scanned the QR code on the e-bike 1021 but before starting to ride, which can improve the user experience and riding safety. In some alternative embodiments, the reminder can also be given at an appropriate time during the ride, such as when the user is stopped at a red light. Of course, in some embodiments, this reminder can also be given in real time through the relevant user interface on the e-bike 1021 and / or the user's terminal device.

[0067] In some embodiments, server 110 can also control the upper limit of the motor output power of electric bicycle 1021 in certain situations. For example, in some embodiments, server 110 can determine the upper limit of the motor output power of electric bicycle 1021 based on road condition information and the remaining battery power of electric bicycle 1021. After determining the upper limit of power output, server 110 can send the upper limit of power output to electric bicycle 1021 so that electric bicycle 1021 can adjust the motor output power based on the upper limit of power output and the user's input angle to the handlebars.

[0068] For example, in some embodiments, when the remaining battery power is low and road conditions indicate rain or recent rain, making the road slippery, the server 110 can adjust the motor's output power limit to a lower level, such as 60% of the rated peak level, after the user scans the code and before riding, and transmit this information to the e-bike 1021. In this case, even if the user twists the handlebars to their maximum angle during riding, the motor's peak output power will still be 60% of the rated peak power, ensuring the user rides at a slow speed and avoiding sudden acceleration and deceleration, thereby ensuring riding safety and improving the user experience. Furthermore, this setting can significantly improve energy efficiency while maintaining performance, extending battery life and riding time.

[0069] In some embodiments, server 110 may also determine the riding route of user riding electric bicycle 1021 based on energy consumption prediction data and the remaining battery power of electric bicycle 1021. Server 110 is able to send the riding route to at least one of electric bicycle 1021 and user's terminal device to allow user to ride electric bicycle 1021 based on the riding route.

[0070] In this way, server 110 can consider various factors such as charging station location, road gradient, and traffic conditions to provide an optimized cycling route, ensuring the user's safe arrival at their destination. In some embodiments, when providing cycling routes, more than one route can be offered for the user to choose from. Each route can be identified in an appropriate way, such as indicating "shortest distance" for some routes and "charging station closer to the destination" for others, to facilitate the user's selection based on their needs, thereby improving the user experience.

[0071] Furthermore, in some embodiments, the riding route can be sent to at least one of the user's terminal device or the electronic device 132 of the e-bike 1021. For example, after the user scans the code and the server 110 receives the required data transmitted from the electronic device 132 of the e-bike 1021 and the user's terminal device, the server 110 determines at least one optimized riding route for the user to choose from based on the power information and energy consumption prediction data in the data, and sends it to the electronic device 132 of the e-bike 1021. The electronic device 132 of the e-bike 1021 can display the riding route on an output device such as a display screen 134, so that the user can ride the e-bike 1021 based on the riding route. In some embodiments, alternatively or additionally, the server 110 can also send the riding route to the user's terminal device and make the terminal device display the riding route, so that the user can ride the e-bike 1021 based on the riding route.

[0072] In some embodiments, a reward mechanism can be set to encourage users to choose low-battery vehicles or participate in energy-saving riding. Specifically, in some embodiments, server 110 can also adjust virtual resources related to the user when it determines that the user's riding of the electric bicycle 1021 meets predetermined conditions. Virtual resources may include, for example, points accumulated by the user in applications related to the electric bicycle 1021, discounts on the cost of riding the electric bicycle 1021, etc. For example, predetermined conditions may include, but are not limited to, at least one of the following: the battery level of the electric bicycle 1021 being ridden is below a battery threshold; riding according to the pushed riding route; the peak motor power output during riding is not greater than a power threshold or the peak speed during riding is not greater than a predetermined peak speed, etc.

[0073] For example, in some embodiments, if the number of e-bikes ridden by a user is less than 10%, the user rides the recommended route, and / or the peak power output of the motor during the ride is less than a power threshold, points can be added to the user's account after completing the corresponding order. These points can then be used for ranking, increasing priority weight, and adjusting order price discounts. Furthermore, a social challenge mechanism can be created to rank user points or encourage users to share them, thereby increasing user engagement and improving system optimization.

[0074] Of course, it should be understood that the examples of predetermined conditions described above are merely illustrative and are not intended to limit the scope of this disclosure. Predetermined conditions may be set according to any suitable circumstances, and this disclosure does not limit such settings.

[0075] In some embodiments, emergency energy management measures can be set. For example, in some embodiments, the electronic equipment 132 of the electric bicycle can put the electric bicycle 1021 into a power-saving mode if it is determined that the user has not yet reached the destination and the battery level of the electric bicycle 1021 is lower than the lower limit indicated by the lower limit battery requirement. In power-saving mode, the output power of the motor of the electric bicycle 1021 does not exceed the power-saving threshold.

[0076] For example, if the electric bicycle 1021's battery level falls below the minimum requirement (e.g., 8%) before reaching its destination (or the new destination mentioned earlier) during a ride, the electronic equipment 132 of the electric bicycle 1021 can activate the reserved emergency reserve power. This emergency reserve power can come from a portion of the battery's charge that can only be activated under predetermined conditions. For example, initially, a certain percentage of the battery's charge can be hidden, and under normal circumstances, only the unhidden charge will be used. The reserved emergency reserve power will only be activated when predetermined conditions are met, allowing the user to ride to their destination or the nearest charging station.

[0077] In this situation, to ensure that users can ride to their destination using the emergency reserve power, they can enter a power-saving mode when using the emergency reserve power. In power-saving mode, the motor's output power can be controlled to not exceed the power-saving power threshold and / or the peak speed of the electric vehicle can be controlled to not exceed the power-saving speed threshold, thereby extending the riding distance and ensuring that the user can ride to their destination.

[0078] Figure 2 A flowchart of a method for operating a motorcycle 1021 according to some embodiments of the present disclosure is shown. Process 200 may be implemented at a suitable electronic device 132 (e.g., server 110). It should be understood that process 200 may include additional actions not shown and / or the actions shown may be omitted, and the scope of the present disclosure is not limited in this respect.

[0079] In box 210, server 110 obtains comprehensive energy consumption prediction information, which includes at least the current location of electric bicycle 1021, road condition information related to the current location, and user information of the user who wants to use electric bicycle 1021. As mentioned earlier, road condition information may include road congestion information, weather conditions, road shape information, etc.

[0080] In box 220, server 110 determines the predicted energy consumption data for the user while riding the electric bicycle 1021 based on comprehensive energy consumption prediction information. Next, in box 230, server 110 determines the minimum energy requirement for allowing the user to ride the electric bicycle 1021 based on the energy consumption prediction data. Finally, in box 240, server 110 controls the operation of the electric bicycle 1021 based on the minimum energy requirement.

[0081] In some embodiments, server 110 may determine the destination of the user riding electric bicycle 1021; obtain distance information to the destination and distribution information of charging stations for electric bicycle 1021; determine the power warning level for electric bicycle 1021 based on energy consumption prediction data, distance information and distribution information; and cause at least one of electric bicycle 1021 and user terminal device to issue a reminder message about power based on the power warning level.

[0082] In some embodiments, server 110 may determine the destination by: determining the user's historical cycling data based on the user information; and determining the destination based on the historical cycling data.

[0083] In some embodiments, server 110 may determine the destination by: obtaining user input about the destination from the user's terminal device; and determining the destination based on the input.

[0084] In some embodiments, server 110 may determine the upper limit of motor output power of electric bicycle 1021 based on road condition information and the remaining power of electric bicycle 1021's battery; and send the upper limit of output power to electric bicycle 1021 so that electric bicycle 1021 adjusts motor output power based on the upper limit of output power and the user's input angle to the handlebars.

[0085] In some embodiments, server 110 may determine the riding route of user riding electric bicycle 1021 based on energy consumption prediction data and the remaining battery power of electric bicycle 1021; and send the riding route to at least one of electric bicycle 1021 and user terminal device to allow user to ride electric bicycle 1021 based on the riding route.

[0086] In some embodiments, server 110 can determine the energy consumption prediction data of a user riding an electric bicycle 1021 by using an energy consumption prediction model and based on comprehensive energy consumption prediction information, wherein the energy consumption prediction model is trained based on training data obtained by the user while riding the electric bicycle 1021.

[0087] In some embodiments, server 110 may adjust virtual resources related to the user in response to determining that the user's riding of electric bicycle 1021 meets predetermined conditions. The predetermined conditions include at least one of the following: the battery level of the electric bicycle 1021 being ridden is lower than a battery threshold; the user is riding according to the pushed riding route; or the peak power output of the motor during riding is not greater than a power threshold or the peak speed during riding is not greater than a predetermined peak speed.

[0088] Figure 3 A flowchart of a method for operating a motorcycle 1021 according to some embodiments of the present disclosure is shown. Process 300 may be implemented at a suitable electronic device 132 (e.g., electronic device 132 of motorcycle 1021). It should be understood that process 300 may include additional actions not shown and / or the actions shown may be omitted, and the scope of the present disclosure is not limited in this respect.

[0089] In box 310, the electronic device 132 of the electric bicycle 1021, in response to a user's operation on the electric bicycle 1021 to prepare for riding, acquires the current location of the electric bicycle 1021 and user information of the user who is about to use the electric bicycle 1021. In box 320, the electronic device 132 sends the current location and user information to a remote device, such as server 110, so that the remote device determines the user's energy consumption prediction data during riding the electric bicycle 1021 based on comprehensive energy consumption prediction information including the current location, user information, and road condition information related to the current location.

[0090] In box 330, electronic device 132 receives control commands from a remote device, the control commands being determined at least based on a lower limit power requirement, which is determined based on energy consumption prediction data. Finally, in box 340, electronic device 132 controls the operation of electric bicycle 1021 based on the control commands.

[0091] In some embodiments, the electronic device 132 of the electric bicycle 1021 can receive a power level warning from a remote device to issue a reminder message about the power level to the user based on the power level warning.

[0092] In some embodiments, the electronic device 132 of the motorcycle 1021 can obtain the upper limit of the output power of the motor of the motorcycle 1021 from a remote device; obtain the user's input angle to the handlebars; and adjust the output power of the motor based on the upper limit of the output power and the input angle.

[0093] In some embodiments, the electronic device 132 of the electric bicycle 1021 can obtain the riding route of the user riding the electric bicycle 1021 from a remote device; and present the riding route to allow the user to ride the electric bicycle 1021 based on the riding route.

[0094] In some embodiments, the electronic device 132 of the electric bicycle 1021 may, in response to determining that the user has not yet reached the destination by riding the electric bicycle 1021 and that the battery level of the electric bicycle 1021 is lower than the lower limit battery level indicated by the lower limit battery level requirement, cause the electric bicycle 1021 to enter a power saving mode. In the power saving mode, the output power of the motor of the electric bicycle 1021 is not higher than the power saving threshold and / or the speed of the electric bicycle 1021 is not higher than the power saving speed threshold.

[0095] Figure 4 A block diagram of an electronic device 400 in which one or more embodiments of the present disclosure may be implemented is shown. It should be understood that... Figure 4 The electronic device 400 shown is merely exemplary and should not be construed as limiting the functionality and scope of the embodiments described herein. Figure 4 The electronic device 400 shown can be used to achieve Figure 1 Electronic devices and / or servers for electric bicycles.

[0096] like Figure 4 As shown, electronic device 400 is in the form of a general-purpose electronic device. Components of electronic device 400 may include, but are not limited to, one or more processors or processing units 410, memory 420, storage device 430, one or more communication units 440, one or more input devices 450, and one or more output devices 440. Processing unit 410 may be a physical or virtual processor and is capable of performing various processes according to programs stored in memory 420. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capability of electronic device 400.

[0097] Electronic device 400 typically includes multiple computer storage media. Such media can be any available media accessible to electronic device 400, including but not limited to volatile and non-volatile media, removable and non-removable media. Memory 420 can be volatile memory (e.g., registers, cache, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. Storage device 430 can be a removable or non-removable medium and can include machine-readable media, such as flash drives, disks, or any other media that can be used to store information and / or data (e.g., training data for training) and can be accessed within electronic device 400.

[0098] Electronic device 400 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not explicitly stated... Figure 4As shown, disk drives for reading from or writing to removable, non-volatile disks (e.g., "floppy disks") and optical disk drives for reading from or writing to removable, non-volatile optical disks can be provided. In these cases, each drive can be connected to a bus (not shown) via one or more data media interfaces. Memory 420 may include computer program product 425 having one or more program modules configured to perform various methods or actions of various embodiments of this disclosure.

[0099] Communication unit 440 enables communication with other electronic devices via a communication medium. Additionally, the functionality of components of electronic device 400 can be implemented using a single computing cluster or multiple computing machines capable of communicating via communication connections. Therefore, electronic device 400 can operate in a networked environment using logical connections to one or more other servers, network personal computers (PCs), or another network node.

[0100] Input device 450 can be one or more input devices, such as a mouse, keyboard, trackball, etc. Output device 440 can be one or more output devices, such as a monitor, speaker, printer, etc. Electronic device 400 can also communicate with one or more external devices (not shown) via communication unit 440 as needed. These external devices include storage devices, display devices, etc., and can communicate with one or more devices that enable user interaction with electronic device 400, or with any device that enables electronic device 400 to communicate with one or more other electronic devices (e.g., network card, modem, etc.). Such communication can be performed via input / output (I / O) interface (not shown).

[0101] According to an exemplary implementation of this disclosure, a computer-readable storage medium is provided that stores computer-executable instructions thereon, wherein the computer-executable instructions are executed by a processor to implement the methods described above. According to an exemplary implementation of this disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, which are executed by a processor to implement the methods described above.

[0102] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, devices, and computer program products implemented according to this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0103] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0104] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions that execute on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0105] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0106] Various implementations of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed implementations. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described implementations. The terminology used herein is chosen to best explain the principles, practical applications, or improvements to technology in the market, or to enable others skilled in the art to understand the various implementations disclosed herein.

Claims

1. A method for operating an electric bicycle, comprising: Obtain comprehensive energy consumption prediction information, which includes at least the current location of the electric bicycle, road condition information related to the current location, and user information of the user who is to use the electric bicycle; Based on the comprehensive energy consumption prediction information, the energy consumption prediction data of the user during the riding of the electric bicycle is determined; Based on the energy consumption prediction data, a lower limit of the required battery power for allowing users to ride the electric bicycle is determined; as well as The operation of the electric bicycle is controlled based on the lower limit power requirement.

2. The method according to claim 1, further comprising: Determine the destination where the user is riding the electric bicycle; Obtain distance information from the destination and distribution information of charging stations for the electric bicycle; The power warning level for the electric bicycle is determined based on the energy consumption prediction data, the distance information, and the distribution information. as well as The electric bicycle and the user's terminal device shall issue a reminder message regarding the battery level based on the battery warning level.

3. The method of claim 2, wherein determining the destination comprises: Based on the user information, determine the user's historical cycling data; as well as The destination is determined based on the historical cycling data.

4. The method of claim 2, wherein determining the destination further comprises: Obtain the user's input regarding the destination from the user's terminal device; as well as The destination is determined based on the input.

5. The method according to claim 1, wherein controlling the operation of the electric bicycle includes: The upper limit of the motor output power of the electric bicycle is determined based on the road condition information and the remaining power of the electric bicycle's battery. as well as The upper limit of output power is sent to the electric bicycle so that the electric bicycle adjusts the output power of the motor based on the upper limit of output power and the user's input angle to the handlebars.

6. The method according to claim 1, wherein controlling the operation of the electric bicycle further includes: The user's riding route for the electric bicycle is determined based on the energy consumption prediction data and the remaining battery power of the electric bicycle. as well as The riding route is sent to at least one of the electric bicycle and the user's terminal device to allow the user to ride the electric bicycle based on the riding route.

7. The method of claim 1, wherein determining the energy consumption prediction data comprises: The user's energy consumption prediction data during riding the electric bicycle is determined by an energy consumption prediction model and based on the comprehensive energy consumption prediction information, wherein the energy consumption prediction model is trained based on historical data obtained by the user while riding the electric bicycle.

8. The method according to claim 1, further comprising: In response to determining that the user's riding of the e-bike meets predetermined conditions, the virtual resources associated with the user are adjusted, wherein the predetermined conditions include at least one of the following: the battery level of the e-bike being ridden is lower than a battery threshold; the user is riding according to the pushed riding route; or the peak power output of the motor during riding is not greater than a power threshold or the peak speed during riding is not greater than a predetermined peak speed.

9. A method for operating an electric motorcycle, comprising: In response to a user's operation on the electric bicycle to prepare to ride it, the current location of the electric bicycle and the user information of the user who is about to use the electric bicycle are obtained. The current location and the user information are sent to a remote device so that the remote device can determine the user's energy consumption prediction data during the riding of the electric bicycle based on comprehensive energy consumption prediction information including the user information, the current location and road condition information related to the current location; Obtain control commands from the remote device, the control commands being determined at least based on a lower limit power requirement, wherein the lower limit power requirement is determined based on the energy consumption prediction data; and The operation of the electric bicycle is controlled based on the control commands.

10. The method of claim 9, further comprising: The system receives a power level warning from the remote device and sends a power level reminder to the user based on the warning level.

11. The method of claim 9, wherein controlling the operation of the electric bicycle includes: Obtain the upper limit of the motor output power of the electric bicycle from the remote device; Obtain the user's input angle for the grip; as well as The output power of the motor is adjusted based on the upper limit of the output power and the input angle.

12. The method according to claim 9, wherein controlling the operation of the electric bicycle further comprises: Obtain the user's riding route on the electric bicycle from the remote device; as well as The riding route is displayed to allow the user to ride the motorcycle based on the riding route.

13. The method of claim 9, further comprising: In response to determining that the user has not yet reached the destination while riding the e-bike and that the e-bike's battery level is below the lower limit battery level indicated by the lower limit battery requirement, the e-bike enters a power-saving mode, in which the output power of the e-bike's motor is not higher than a power-saving power threshold and / or the e-bike's speed is not higher than a power-saving speed threshold.

14. An electronic device, comprising: At least one processing unit; as well as At least one memory coupled to the at least one processing unit and storing machine-executable instructions that, when executed by the at least one processing unit, cause the device to perform the method according to any one of claims 1-8 or 9-13.

15. A computer-readable storage medium having stored thereon one or more computer instructions, wherein the one or more computer instructions are executed by a processor to implement the method according to any one of claims 1-8 or 9-13.

16. A computer program product comprising computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the method according to any one of claims 1-8 or 9-13.

Images