Battery service system and method of intelligent door lock

Abstract

The invention relates to the technical field of battery management, and particularly discloses a battery service system and method for an intelligent door lock, and the system comprises a data collection module which collects the battery voltage, the battery electric quantity, the environment temperature, the duration of each unlocking of the door lock, and the time data of each unlocking of the door lock in real time; the battery health evaluation module is used for evaluating the health state of the battery according to the influence of the battery charging and discharging history, the battery self-discharging rate, the environment temperature and the collected data on the health state of the battery; the dynamic discharge model building module is used for building and training a nonlinear dynamic discharge model which comprehensively considers the battery health state and the door lock using habit according to the collected data and the battery health state evaluation result; and the intelligent early warning module is used for predicting a replacement threshold value of the current battery electric quantity by using the trained model, and sending a replacement early warning when the electric quantity is reduced to the replacement threshold value. The system provided by the invention effectively improves the accuracy of battery power consumption prediction according to the health degree of the battery and the habit of using the door lock by the user.

Description

Technical Field

[0001] The present invention relates to the field of battery management technology, and in particular to a battery service system and method for a smart door lock. Background Art

[0002] With the rapid development of smart home and Internet of Things technologies, smart door locks, as an important part of smart home, house rental and other fields, are increasingly valued by consumers for their stability and convenience. At present, smart door locks are mostly powered by lithium batteries, and the health of the battery directly affects the reliable operation of the device and user experience. However, current smart door locks have the following defects and deficiencies in battery management:

[0003] Battery health monitoring is rough: Battery health status is not only determined by the remaining power, but also affected by many factors such as the battery's charge and discharge history, self-discharge rate, ambient temperature, etc. Most smart door locks on the market can only provide a simple indication of the remaining battery power, lacking in-depth analysis of the battery's health, which will result in users being unable to understand the true condition of the battery in a timely manner, thus affecting the life of the smart door lock and the user experience.

[0004] Single prediction model: Existing battery management systems often predict battery life based on simple linear models, ignoring the impact of complex factors such as usage habits (such as the number and frequency of door openings) and ambient temperature on battery discharge behavior, resulting in low prediction accuracy, which in turn affects the user experience.

[0005] Passive maintenance service strategy: Users usually get low battery information from the door lock voice prompt only when the battery is completely exhausted or nearly exhausted. This passive maintenance service strategy not only affects the user experience, but may also cause the door lock to fail to work properly due to battery abnormalities or sudden power failure, posing a safety hazard.

[0006] Lack of personalized services: Existing battery management systems cannot provide personalized services based on user usage habits and battery health status, such as intelligently recommending replacement time, providing battery replacement service solutions, etc. This limits the convenience and flexibility of users in battery management. Summary of the invention

[0007] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a battery service system and method for a smart door lock, which can monitor the battery status in real time, accurately evaluate the battery health, and provide intelligent early warning, battery replacement recommendation and other services based on the user's usage habits and battery health status.

[0008] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0009] A smart door lock battery service system, comprising:

[0010] The data acquisition module is used to collect the battery voltage, battery power, local ambient temperature, duration of each door lock opening, and time data of each door lock opening of the smart door lock in real time;

[0011] The battery health assessment module is used to assess the battery health status using a machine learning algorithm based on the battery charge and discharge history, battery self-discharge rate, local ambient temperature, and the impact of data collected in real time by the data acquisition module on the battery health status;

[0012] The dynamic discharge model building module is used to build and train a nonlinear dynamic discharge model that comprehensively considers the battery health status and the door lock usage habits based on the collected data and the battery health status evaluation results using a machine learning algorithm;

[0013] The intelligent warning module uses the trained nonlinear dynamic discharge model to predict the replacement threshold of the battery power in the current state, and sends a battery replacement warning when the battery power drops to the replacement threshold.

[0014] Furthermore, the data acquisition module includes:

[0015] Battery monitoring module, used to monitor and record battery voltage and battery power in real time;

[0016] Use the recording module to record in real time the duration of each door lock opening, the time of each door lock opening, and the local ambient temperature when the door lock is opened each time;

[0017] A storage module is used to temporarily store the duration and time of each door lock opening when the network is disconnected or the signal is poor;

[0018] The wireless communication module is used to transmit the data in the battery monitoring module, the usage recording module and the storage module to the battery health assessment module and the dynamic discharge model building module at fixed time intervals.

[0019] Furthermore, the wireless communication module transmits the data in the battery monitoring module, the usage recording module and the storage module to the battery health assessment module and the dynamic discharge model building module every day or when the battery power changes by 1%.

[0020] Furthermore, the wireless communication module uses a custom protocol to transmit data, and removes data from the battery monitoring module, usage recording module, storage module and wireless communication module after the battery health assessment module and the dynamic discharge model construction module respond.

[0021] Furthermore, before the dynamic discharge model building module trains the nonlinear dynamic discharge model, the collected data and the battery health status evaluation results are cleaned and preprocessed, and key features are extracted from all the cleaned and preprocessed data as inputs to the model;

[0022] The key features include: the number of door lock openings per day, the average duration of door lock opening, the time distribution of door lock openings per day, the daily local ambient temperature, and the battery health status.

[0023] Furthermore, the dynamic discharge model building module continuously optimizes and updates the trained model using a PPO reinforcement learning algorithm based on the collected data and the evaluation results of the battery health status to adapt to changes in the habits of using the door lock.

[0024] Furthermore, the system also includes:

[0025] The replacement recommendation module is used to analyze the usage habits of the door lock based on the real-time collected duration of each door lock opening, the time of each door lock opening, and the local ambient temperature, so as to intelligently recommend battery replacement services.

[0026] A battery service method for a smart door lock, based on a battery service system for a smart door lock as described in any one of the above, comprises the following steps:

[0027] Real-time data collection of the smart door lock's battery voltage, battery power, local ambient temperature, duration of each door lock opening, and time of each door lock opening;

[0028] The battery health status is evaluated using a machine learning algorithm based on the battery charge and discharge history, battery self-discharge rate, ambient temperature, and the impact of data collected in real time by the data acquisition module on the battery health status;

[0029] Based on the collected data and the evaluation results of the battery health status, a machine learning algorithm is used to build and train a nonlinear dynamic discharge model that comprehensively considers the battery health status and door lock usage habits;

[0030] The trained nonlinear dynamic discharge model is used to predict the replacement threshold of the battery power in the current state, and a battery replacement warning is sent when the battery power drops to the replacement threshold.

[0031] Furthermore, the PPO reinforcement learning algorithm is continuously used to optimize and update the trained model based on the collected data and the evaluation results of the battery health status to adapt to the changes in the habits of using the door lock.

[0032] Furthermore, the method further comprises:

[0033] Based on the real-time data collected on the duration of each door lock opening, the time of each door lock opening, and the local ambient temperature, the door lock usage habits are analyzed to intelligently recommend battery replacement services.

[0034] Due to the adoption of the above technical solution, the present invention has the following beneficial effects:

[0035] 1. It can accurately predict the remaining battery power based on the collected data of user door lock usage, battery health status, local ambient temperature and other factors, so that users can understand the battery life in advance, and actively send early warning information to users to remind users to replace batteries in time to avoid the inconvenience caused by battery exhaustion and the safety hazards caused by battery exhaustion, effectively improving the user experience.

[0036] 2. It can remind users to replace batteries in time to avoid over-discharge of batteries. It can also prevent damage to other electronic components of the door lock due to battery exhaustion, thereby extending the battery life. At the same time, it ensures that the smart door lock always maintains sufficient power, avoids accidents caused by battery problems, and improves home safety.

[0037] 3. It can analyze the user's door lock usage habits based on the collected data, and can intelligently recommend battery replacement services based on the user's usage habits and battery health status, so that users can choose the most appropriate service method, improve service efficiency, and increase user satisfaction. It can also help manufacturers reasonably arrange battery inventory and replacement services and reduce operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments will be briefly introduced below. Obviously, the drawings in the following description only relate to some embodiments of the present invention, but are not intended to limit the present invention.

[0039] Figure 1 It is a structural diagram of the battery service system provided in Example 1.

[0040] Figure 2 It is a structural diagram of the real data acquisition module.

[0041] Figure 3 It is a structural diagram of the battery service system provided in the second embodiment.

[0042] Figure 4 It is a schematic diagram of the communication connection between the battery service system and the user terminal and the background management system.

[0043] Figure 5 It is a flow chart of the battery service method provided in the third embodiment.

[0044] Description of reference numerals:

[0045] 10. Battery service system;

[0046] 110. Data acquisition module; 1101. Battery monitoring module; 1102. Usage record module; 1103. Storage module; 1104. Wireless communication module;

[0047] 120. Battery health assessment module; 130. Dynamic discharge model building module; 140. Intelligent warning module; 150. Replacement recommendation module;

[0048] 20. User terminal; 30 backend management system. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. The components of the embodiments of the present invention described and shown in the accompanying drawings can be arranged and designed in various configurations. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0051] Unless otherwise defined, the technical terms or scientific terms used in this patent document shall have the usual meanings understood by persons with ordinary skills in the field to which the invention belongs. The words "first", "second" and similar words used in the patent specification and claims of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one", "one" or "the" do not indicate a quantity limitation, but indicate the existence of at least one. Words such as "include" or "comprise" mean that the elements or objects appearing before "include" or "comprise" include the elements or objects listed after "include" or "comprise" and their equivalents, and do not exclude other elements or objects. "Center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention.

[0052] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0053] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the features of the following embodiments can be combined with each other.

[0054] Embodiment 1:

[0055] See also Figure 1 , Figure 4 This embodiment provides a battery service system for a smart door lock, including: a data acquisition module 110, a battery health assessment module 120, a dynamic discharge model construction module 130, and an intelligent early warning module 140. The battery service system 10, the user terminal 20, and the background management system 30 of the smart door lock are connected in communication with each other.

[0056] The battery service system 10 evaluates the battery health status and predicts the remaining battery power. According to the battery replacement threshold set by the user terminal 20, it sends a battery warning to the user terminal 20 and the background management system 30, and provides the user terminal 20 with a query port for the battery health status and the remaining battery power.

[0057] The user can set the battery replacement threshold according to personal habits on the user terminal 20, and can view information such as battery health status and battery power on the user terminal 20. The user terminal 20 includes a mobile phone, a tablet, a smart watch, a computer, etc.

[0058] The background management system 30 can obtain information such as the battery status of each user's smart door lock, smart door lock usage information, and the battery replacement threshold set by the user in real time, and send a battery replacement warning to the user terminal 20 when the battery power drops to the battery replacement threshold.

[0059] The data acquisition module 110 is used to collect the battery voltage, battery power, local ambient temperature, duration of each door lock opening, and time data of each door lock opening of the smart door lock in real time, and transmit the collected data to the battery health assessment module 20 and the dynamic discharge model construction module 30.

[0060] The battery health assessment module 120 is used to evaluate the battery health status using a machine learning algorithm based on the battery charge and discharge history, battery self-discharge rate, local ambient temperature, and the impact of data collected in real time by the data acquisition module 110 on the battery health status, and transmit the evaluation result of the battery health status to the dynamic discharge model construction module 130.

[0061] The dynamic discharge model building module 130 is used to build and train a nonlinear dynamic discharge model that comprehensively considers the battery health status and the door lock usage habits based on the collected data and the battery health status evaluation results using a machine learning algorithm.

[0062] The intelligent warning module 140 uses the trained nonlinear dynamic discharge model to predict the replacement threshold of the battery power in the current state, and sends a battery replacement warning to the user terminal 20 and the backend management system 30 when the battery power drops to the replacement threshold. The replacement threshold is recommended to be set to the last 15 days of battery power usage to ensure that the user has sufficient time to replace the battery and maximize the use of the battery power. The user can also set the battery replacement threshold according to his or her own usage habits.

[0063] The system can accurately predict the remaining battery power based on the collected data on user door lock usage, battery health status, local ambient temperature and other factors, allowing users to understand the battery life in advance and proactively send early warning information to users, reminding them to replace the battery in time to avoid the inconvenience caused by battery depletion and the safety hazards caused by battery depletion, effectively improving the user experience.

[0064] The system can promptly remind users to replace batteries to avoid over-discharge of batteries. It can also prevent damage to other electronic components of the door lock due to battery exhaustion, thereby extending the battery life.

[0065] See also Figure 2 The data acquisition module 110 includes a battery monitoring module 1101, a usage record module 1102, a storage module 1103, and a wireless communication module 1104. The battery monitoring module 1101, the usage record module 1102, and the storage module 1103 are all connected to the wireless communication module 1104 for communication, and transmit data to the battery health assessment module 120 and the dynamic discharge model construction module 130 through the wireless communication module 1104.

[0066] The battery monitoring module 1101 has a built-in high-precision battery monitoring chip for real-time monitoring and recording of battery voltage and battery power. The recorded data is converted into a digital signal through an ADC (digital-to-analog converter) and the signal is transmitted to the wireless communication module 1104.

[0067] The recording module 1102 is used to record in real time the duration of each door lock opening, the time of each door lock opening, and the local ambient temperature each time the door lock is opened, and transmit the recorded data to the wireless communication module 1104.

[0068] The storage module 1103 uses norflash to store the unlocking record of the door lock, and is used to temporarily store the duration and time of each door lock opening when the network is disconnected or the signal is poor, and transmit the data to the wireless communication module 1104.

[0069] The wireless communication module 1104 is used to transmit the data in the battery monitoring module 1101, the usage recording module 1102, and the storage module 1103 to the battery health assessment module and the dynamic discharge model construction module at fixed time intervals. The wireless communication module transmits the data to the battery health assessment module 120 and the dynamic discharge model construction module 130 every day or when the battery power changes by 1%.

[0070] The data transmission rules can be further set to transmit the collected data every 8 hours or after the user unlocks the door 5 times.

[0071] The wireless communication module uses a custom protocol to transmit data, and the protocol is set to a one-response mode. After the battery health assessment module 120 and the dynamic discharge model construction module 130 respond (i.e., after receiving the data), the data in the battery monitoring module 1101, the usage record module 1102, the storage module 1103 and the wireless communication module 1104 are removed to ensure efficient and stable data transmission.

[0072] Before the battery health assessment module 120 assesses the battery health status, the battery charge and discharge history, battery self-discharge rate, and local ambient temperature data are cleaned and preprocessed; before the dynamic discharge model construction module 130 trains the nonlinear dynamic discharge model, the collected data and the battery health status assessment results are cleaned and preprocessed to remove outliers and smooth noise data, thereby facilitating the assessment of the battery health status and the training of the nonlinear dynamic discharge model. The outlier refers to data that causes rapid power loss due to abnormalities in the battery itself. In this embodiment, the moving average method is used to smooth the noise data, that is, the mean of the battery data in a certain time window is set.

[0073] The dynamic discharge model building module 130 extracts key features from all the cleaned and preprocessed data as input to the model; the key features include: the number of door lock openings per day, the average duration of door lock openings, the distribution of door lock opening times per day, the local ambient temperature per day, and the battery health status.

[0074] The dynamic discharge model building module can continuously optimize and update the trained model using the PPO reinforcement learning algorithm based on the collected data and the evaluation results of the battery health status to adapt to the changes in the user's habits of using the door lock and further improve the accuracy of the prediction.

[0075] The PPO reinforcement learning algorithm can perform online learning and continuously update model parameters using the latest battery usage data to ensure the timeliness and effectiveness of the prediction model.

[0076] The system covers the entire chain from data collection, processing and analysis to intelligent early warning. It can accurately estimate battery power and evaluate battery health status, and based on this, provide users with proactive and accurate battery replacement information.

[0077] Embodiment 2:

[0078] See also Figure 3 The battery service system for a smart door lock provided in this embodiment is different from that in the first embodiment in that the system also includes a replacement recommendation module 150 connected to the intelligent early warning module 140. The replacement recommendation module 150 is used to analyze the habit of using the door lock based on the duration of each door lock opening, the time of each door lock opening, and the local ambient temperature collected in real time, so as to intelligently recommend battery replacement services.

[0079] After receiving the battery replacement warning and recommended battery replacement service on the user terminal 20, the user can also set the specific battery replacement time and specific battery replacement method in the user terminal 20 according to his or her personal habits, such as making an appointment for a specific time for door-to-door replacement, requesting the manufacturer to mail the battery and battery replacement method instructions, etc.

[0080] The system covers the entire chain from data collection, processing and analysis, intelligent early warning, to intelligent recommendation. It can accurately estimate battery power and evaluate battery health status, and based on this, provide users with proactive and accurate battery replacement services.

[0081] The following is a reference example for analyzing the user's door lock usage habits:

[0082] 1. Collect relevant data about users using door locks:

[0083] The duration of each door opening is recorded. A longer door opening time may mean that the user often carries heavy objects or carries a lot of things, and the user's family has a large number of people.

[0084] Recording the time of each door opening can reflect the user's daily routine; for example, the door opening times on weekdays are concentrated in a certain period of time in the morning and evening.

[0085] By counting the time distribution of each door lock opening and recording the number of times the user opens the door within a certain time range, it can reflect the frequency of the user's use of the door lock, or the user's house may be rented to multiple tenants.

[0086] By recording the temperature changes at the location where the door lock is located, it is possible to analyze the impact of temperature on battery discharge, and it also allows manufacturers to understand the distribution of users of the door locks in various locations.

[0087] 2. Data Analysis:

[0088] The system uses data analysis technology based on the recorded data related to the user's use of the door lock, processes and analyzes the collected data, and extracts the key features of the user's door lock usage habits, such as: the number of times the door lock is opened per day, the average duration of the door lock opening, the distribution of the time when the door lock is opened per day, the daily local ambient temperature, and the battery health status; the system uses the trained nonlinear dynamic discharge model to predict the replacement threshold of the battery power in the current state, and sends a battery replacement warning when the battery power drops to the replacement threshold. The nonlinear dynamic discharge model will continue to optimize and update the PPO reinforcement learning algorithm model based on the collected data and the evaluation results of the battery health status to adapt to the changes in the user's door lock usage habits.

[0089] 3. Recommended battery replacement service:

[0090] Based on the analyzed user habits of using door locks, the most suitable battery replacement service plan is recommended, such as reminding customers to make an appointment for a specific time for door-to-door replacement, or mailing batteries and instructions for battery replacement.

[0091] The system can analyze the user's door lock usage habits based on the collected data, and can intelligently recommend battery replacement services based on the user's usage habits and battery health status, making it convenient for users to choose the most appropriate service method, improve service efficiency, and increase user satisfaction. It can also help manufacturers reasonably arrange battery inventory and replacement services and reduce operating costs.

[0092] Embodiment three:

[0093] See also Figure 3 The present embodiment provides a battery service method for a smart door lock, based on the battery service system for the smart door lock described in the first and second embodiments, comprising the following steps:

[0094] Real-time data collection of the smart door lock's battery voltage, battery power, local ambient temperature, duration of each door lock opening, and time of each door lock opening;

[0095] The battery health status is evaluated using a machine learning algorithm based on the battery charge and discharge history, battery self-discharge rate, local ambient temperature, and the impact of data collected in real time by the data acquisition module on the battery health status;

[0096] Based on the collected data and the evaluation results of the battery health status, a machine learning algorithm is used to build and train a nonlinear dynamic discharge model that comprehensively considers the battery health status and the door lock usage habits. After the model training is completed, the PPO reinforcement learning algorithm is continuously used to optimize and update the trained model based on the collected data and the battery health status evaluation results to adapt to the changes in the door lock usage habits;

[0097] The trained nonlinear dynamic discharge model is used to predict the replacement threshold of the battery power in the current state, and a battery replacement warning is sent when the battery power drops to the replacement threshold. The door lock usage habits are analyzed based on the real-time collected duration of each door lock opening, the time of each door lock opening, and the local ambient temperature, to intelligently recommend battery replacement services.

[0098] The battery service system 10, the user terminal 20, and the backend management system 30 of the smart door lock are connected in communication with each other. The user can view information such as battery health status and battery power on the user terminal 20, set the battery replacement threshold according to personal habits on the user terminal 20, and set the specific time and method of battery replacement according to personal preferences after receiving the battery replacement warning and recommended battery replacement service.

[0099] This method can accurately predict the remaining battery power based on the collected data on user door lock usage, battery health status, local ambient temperature and other factors, so that users can understand the battery life in advance, and actively send early warning information to users to remind them to replace the battery in time to avoid the inconvenience caused by battery exhaustion and the safety hazards caused by battery exhaustion, effectively improving the user experience.

[0100] It can also analyze the user's door lock usage habits based on the collected data, and intelligently recommend battery replacement services based on the user's usage habits and battery health status, making it convenient for users to choose the most appropriate service method, improve service efficiency, and increase user satisfaction. It can also help manufacturers reasonably arrange battery inventory and replacement services and reduce operating costs.

[0101] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A battery service system for a smart door lock, characterized in that: include: The data acquisition module is used to collect the battery voltage, battery power, local ambient temperature, duration of each door lock opening, and time data of each door lock opening of the smart door lock in real time; The battery health assessment module is used to assess the battery health status using a machine learning algorithm based on the battery charge and discharge history, battery self-discharge rate, local ambient temperature, and the impact of data collected in real time by the data acquisition module on the battery health status; The dynamic discharge model building module is used to build and train a nonlinear dynamic discharge model that comprehensively considers the battery health status and door lock usage habits based on the collected data and the battery health status evaluation results using a machine learning algorithm; The intelligent warning module uses the trained nonlinear dynamic discharge model to predict the replacement threshold of the battery power in the current state, and sends a battery replacement warning when the battery power drops to the replacement threshold.

2. The battery service system for a smart door lock according to claim 1, characterized in that: The data acquisition module comprises: Battery monitoring module, used to monitor and record battery voltage and battery power in real time; Use the recording module to record in real time the duration of each door lock opening, the time of each door lock opening, and the local ambient temperature when the door lock is opened each time; A storage module is used to temporarily store the duration and time of each door lock opening when the network is disconnected or the signal is poor; The wireless communication module is used to transmit the data in the battery monitoring module, the usage recording module and the storage module to the battery health assessment module and the dynamic discharge model building module at fixed time intervals.

3. The battery service system for a smart door lock according to claim 2, characterized in that: The wireless communication module transmits the data in the battery monitoring module, the usage recording module and the storage module to the battery health assessment module and the dynamic discharge model construction module every day or when the battery power changes by 1%.

4. A battery service system for a smart door lock according to claim 2 or 3, characterized in that: The wireless communication module uses a custom protocol to transmit data, and removes data from the battery monitoring module, the usage record module, the storage module, and the wireless communication module after the battery health assessment module and the dynamic discharge model construction module respond.

5. The battery service system for a smart door lock according to claim 1, characterized in that: Before the dynamic discharge model building module trains the nonlinear dynamic discharge model, the collected data and the battery health status assessment results are cleaned and preprocessed, and key features are extracted from all the cleaned and preprocessed data as the input of the model; The key features include: the number of door lock openings per day, the average duration of door lock opening, the time distribution of door lock openings per day, the daily local ambient temperature, and the battery health status.

6. The battery service system for a smart door lock according to claim 1, characterized in that: The dynamic discharge model building module continuously optimizes and updates the trained model using the PPO reinforcement learning algorithm based on the collected data and the evaluation results of the battery health status to adapt to the changes in the habits of using the door lock.

7. A battery service system for a smart door lock according to any one of claims 1 to 6, characterized in that: The system also includes: The replacement recommendation module analyzes the usage habits of the door lock based on the real-time collected data of the duration of each door lock opening, the time of each door lock opening, and the local ambient temperature, and intelligently recommends battery replacement services.

8. A battery service method for a smart door lock, based on a battery service system for a smart door lock according to any one of claims 1 to 7, characterized in that: Includes steps: Real-time data collection of the smart door lock's battery voltage, battery power, local ambient temperature, duration of each door lock opening, and time of each door lock opening; The battery health status is evaluated using a machine learning algorithm based on the battery charge and discharge history, battery self-discharge rate, local ambient temperature, and the impact of data collected in real time by the data acquisition module on the battery health status; Based on the collected data and the evaluation results of the battery health status, a machine learning algorithm is used to build and train a nonlinear dynamic discharge model that comprehensively considers the battery health status and door lock usage habits; The trained nonlinear dynamic discharge model is used to predict the replacement threshold of the battery power in the current state, and a battery replacement warning is sent when the battery power drops to the replacement threshold.

9. A battery service method for a smart door lock according to claim 8, characterized in that: The PPO reinforcement learning algorithm is continuously used to optimize and update the trained model based on the collected data and battery health status assessment results to adapt to changes in door lock usage habits.

10. A battery service method for a smart door lock according to claim 8 or 9, characterized in that: The method also includes: Based on the real-time data collected on the duration of each door lock opening, the time of each door lock opening, and the local ambient temperature, the door lock usage habits are analyzed to intelligently recommend battery replacement services.

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