Method and device for determining residual charging duration of device, and storage medium

Abstract

The invention provides a method and equipment for determining the residual charging time of equipment and a storage medium, and relates to the technical field of vehicle charging, and the method comprises the steps: firstly, obtaining the current battery electric quantity, charging parameters and capacity data of the charging equipment in response to the detection that the charging equipment is arranged in a wireless charging device, the charging parameter is used for representing the electric energy transmission state in the charging process, and the capacity data is used for representing the maximum capacity of a battery of the charging equipment; secondly, based on the capacity data, the current battery electric quantity and the charging parameters, the residual charging duration of the charging equipment is determined; and finally, outputting the residual charging duration. The technical problem that an existing vehicle-mounted wireless charging system is poor in user experience due to the fact that the existing vehicle-mounted wireless charging system lacks prediction and real-time display capacity on the residual charging time length is solved.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle charging technology, and in particular to a method, device, and storage medium for determining the remaining charging time of a device. Background Technology

[0002] With the widespread adoption of smart cars, in-vehicle wireless charging technology has become a standard feature in mainstream models. Most newly launched models support the international standard wireless charging function developed by the Wireless Power Consortium. This technology greatly enhances the user's charging experience in in-vehicle scenarios due to its convenience of eliminating the need for physical cables.

[0003] However, existing in-vehicle wireless charging systems still have significant limitations in their functional design. Their core shortcoming lies in their ability to only provide basic charging status indicators (such as charging in progress or charging complete), lacking the ability to accurately predict and display the remaining charging time for devices like mobile phones in real time. This deficiency directly leads to users being unable to accurately predict the specific time required for a device to fully charge when using wireless charging in a vehicle scenario. In scenarios such as long-distance driving, users may end their trip prematurely due to uncertainty about the charging progress, or frequently check the device's battery level, affecting the rationality of trip planning and distracting driving attention, thus posing serious driving safety hazards. Even in daily short trips, users find it difficult to determine whether they can complete the target battery replenishment within the trip time, reducing the practical value of the wireless charging function.

[0004] In summary, existing in-vehicle wireless charging systems suffer from poor user experience due to a lack of ability to predict and display remaining charging time in real time. Summary of the Invention

[0005] In view of the above problems, this disclosure provides a method, device, and storage medium for determining the remaining charging time to overcome or at least partially solve the technical problem of poor user experience caused by the lack of prediction and real-time display capabilities of existing in-vehicle wireless charging systems. The technical solution is as follows: A method for determining the remaining charging time of a device, the method comprising: In response to detecting that the charging device is placed in the wireless charging device, the current battery power, charging parameters and capacity data of the charging device are obtained. The charging parameters are used to characterize the power transmission status during the charging process, and the capacity data are used to characterize the maximum capacity of the battery of the charging device. Based on the capacity data, the current battery level, and the charging parameters, the remaining charging time of the charging device is determined; Output the remaining charging time.

[0006] In this way, by simultaneously acquiring the current battery level, charging parameters representing the power transmission status, and capacity data representing the maximum battery capacity after detecting the charging device, comprehensive and relevant basic data support is provided for determining the remaining charging time. This avoids the one-sidedness of estimation caused by a single data dimension, helps users plan their charging schedules in advance, reduces the need to check the device during driving due to uncertainty about the charging progress, and improves the convenience and safety of in-vehicle charging scenarios.

[0007] Optionally, determining the remaining charging time of the charging device based on the capacity data, the current battery level, and the charging parameters includes: Based on the current battery level and the charging parameters, the charging stage of the charging device is determined; Based on the charging stage, different strategies for determining the remaining charging time are determined. The remaining charging time is determined based on the capacity data, the charging parameters, and the remaining charging time determination strategy.

[0008] In this way, by first dividing the charging stage based on the current battery capacity and charging parameters, then matching a dedicated strategy for determining the remaining charging time for each stage, and finally combining capacity data, charging parameters and corresponding strategies to calculate the time, the logic for determining the time fits the dynamic changes in the charging process. This avoids the problem of unreasonable estimation caused by ignoring the characteristics of each stage when using a single calculation model, and better adapts to the dynamic scenario requirements of in-vehicle wireless charging.

[0009] Optionally, determining the charging stage of the charging device based on the current battery level and the charging parameters includes: In response to the charging parameters satisfying the first condition, the charging stage is determined to be a constant current fast charging stage, where the first condition is used to characterize the condition that the current is stable and the power meets the standard in the charging parameters. In response to the charging parameters satisfying the second condition, the charging stage is determined to be a constant current buffer stage. The second condition is used to characterize the condition in the charging parameters where the current is stable but the power does not reach the fast charging threshold. In response to the current battery level being greater than a power threshold and the charging parameters meeting a third condition, the charging stage is determined to be the final decay stage, whereby the third condition characterizes the condition that the power and current in the charging parameters are decaying.

[0010] In this way, the charging stages are clearly defined by the explicit conditions. The first, second, and third conditions correspond to the charging parameters and power characteristics of different stages, respectively. This provides a clear basis for stage determination, reduces strategy matching errors caused by stage ambiguity, lays a solid foundation for subsequent matching duration determination strategies, and reduces the adverse impact of stage misjudgment on the reference value of duration.

[0011] Optionally, the strategy for determining different remaining charging time based on the charging stage includes: In response to the charging phase being a constant current fast charging phase, the remaining charging time determination strategy is determined to be the first strategy. In response to the charging phase being a constant current buffer phase, the remaining charging duration determination strategy is determined to be the second strategy. In response to the fact that the charging phase is the final decay phase, the remaining charging time determination strategy is determined to be the third strategy.

[0012] In this way, a unique mapping relationship is established between the charging stage and the strategy for determining the remaining charging time. This ensures that the three stages of constant current fast charging, constant current buffering, and final attenuation each correspond to a dedicated calculation strategy, avoiding the confusion in calculation logic caused by the mismatch between the strategy and the stage. This improves the pertinence and rationality of the time determination, and makes the time derivation of different stages more in line with the charging characteristics of that stage.

[0013] Optionally, determining the remaining charging time based on the capacity data, the charging parameters, and the remaining charging time determination strategy includes: Based on the capacity data and the current battery level of the charging device, the remaining charging capacity is determined; The remaining charging time is determined based on the remaining charging capacity, the charging parameters, and the remaining charging time determination strategy.

[0014] In this way, the remaining charging capacity is first determined based on the capacity data and the current battery level. Then, the remaining charging time is calculated by combining the charging parameters and corresponding strategies. This makes the starting point for determining the time clearer, avoids calculation deviations caused by the ambiguity of the amount to be charged, and makes the entire time derivation process more logical and based on more sufficient evidence, thereby improving the reference reliability of the time result.

[0015] Optionally, determining the remaining charging time based on the remaining charging capacity, the charging parameters, and the remaining charging time determination strategy includes: In response to the remaining charging time determination strategy being the first strategy, the effective charging power is determined based on the charging parameters, and the effective charging power is used to characterize the real and stable power transmission efficiency. The remaining charging time is determined based on the effective charging power and the remaining charging capacity. In response to the remaining charging time determination strategy being the second strategy, a decay trend is determined based on the charging parameters, and the decay trend is used to characterize the dynamic decay trend of the charging parameters as the charging process progresses. Based on the attenuation trend and the remaining charging capacity, the remaining charging time is determined; In response to the remaining charging time determination strategy being the third strategy, the rate of change is determined based on the charging parameters, wherein the rate of change characterizes the rate at which power changes with the amount of electricity. The remaining charging time is determined based on the rate of change and the remaining charging capacity.

[0016] In this way, specific core parameters are matched for different strategies. The first strategy focuses on the effective charging power that represents the real and stable power transmission efficiency, the second strategy focuses on the decay trend that represents the dynamic decay trend of charging parameters, and the third strategy focuses on the rate of change of power with the rate of change of power. This ensures that the duration calculation of each stage is in line with its own core charging characteristics, reduces the estimation deviation caused by the general selection of parameters, and improves the adaptability and fit of the duration determination of different stages.

[0017] Optionally, before outputting the remaining charging time, the method further includes: Based on the historical charging data of the charging device, the deviation between the predicted remaining charging time and the actual remaining charging time of the charging device is determined. Based on the deviation value, the optimization coefficients are determined; Based on the optimization coefficient, the remaining charging time is optimized.

[0018] In this way, by mining the historical charging data of the charging device, the deviation between the predicted duration and the actual duration is extracted and converted into an optimization coefficient. The remaining charging duration is then optimized so that the duration can gradually adapt to the actual charging pattern of the device, reducing estimation fluctuations during long-term use and improving the consistency and reference value of the duration results in multiple charging scenarios.

[0019] Optionally, before outputting the remaining charging time, the method further includes: Determine the model of the charging device; Based on the model of the charging device, correction parameters are determined. These correction parameters are used to characterize the features associated with the charging device model that affect the estimation of charging rate and duration. Based on the correction parameters, the remaining charging time is corrected.

[0020] In this way, by obtaining correction parameters related to the charging characteristics of the charging device model, the remaining charging time is corrected. This fully considers the differences in charging strategies and power limits of different brands and models of devices, reduces estimation deviations caused by different device characteristics, improves the compatibility of this application with multiple brands and models of devices, and allows all types of devices to obtain a time reference that is more in line with their own charging characteristics.

[0021] A device for determining the remaining charging time of a device, the device comprising: The acquisition module is used to acquire the current battery power, charging parameters and capacity data of the charging device in response to detecting that the charging device is placed in the wireless charging device. The charging parameters are used to characterize the power transmission status during the charging process, and the capacity data are used to characterize the maximum capacity of the battery of the charging device. The determination module is used to determine the remaining charging time of the charging device based on the capacity data, the current battery level, and the charging parameters; The output module is used to output the remaining charging time.

[0022] Optionally, the determination module is also used for: Based on the current battery level and the charging parameters, the charging stage of the charging device is determined; Based on the charging stage, different strategies for determining the remaining charging time are determined. The remaining charging time is determined based on the capacity data, the charging parameters, and the remaining charging time determination strategy.

[0023] Optionally, the determination module is also used for: In response to the charging parameters satisfying the first condition, the charging stage is determined to be a constant current fast charging stage, where the first condition is used to characterize the condition that the current is stable and the power meets the standard in the charging parameters. In response to the charging parameters satisfying the second condition, the charging stage is determined to be a constant current buffer stage. The second condition is used to characterize the condition in the charging parameters where the current is stable but the power does not reach the fast charging threshold. In response to the current battery level being greater than a power threshold and the charging parameters meeting a third condition, the charging stage is determined to be the final decay stage, whereby the third condition characterizes the condition that the power and current in the charging parameters are decaying.

[0024] Optionally, the determination module is also used for: In response to the charging stage being the constant current fast charging stage, the remaining charging time determination strategy is determined to be the first strategy. In response to the charging phase being the constant current buffering phase, the remaining charging duration determination strategy is determined to be the second strategy. In response to the charging phase being the final decay phase, the remaining charging duration determination strategy is determined to be the third strategy.

[0025] Optionally, the determination module is also used for: Based on the capacity data and the current battery level of the charging device, the remaining charging capacity is determined; The remaining charging time is determined based on the remaining charging capacity, the charging parameters, and the remaining charging time determination strategy.

[0026] Optionally, the determination module is also used for: In response to the remaining charging time determination strategy being the first strategy, the effective charging power is determined based on the charging parameters, and the effective charging power is used to characterize the real and stable power transmission efficiency. The remaining charging time is determined based on the effective charging power and the remaining charging capacity. In response to the remaining charging time determination strategy being the second strategy, a decay trend is determined based on the charging parameters, and the decay trend is used to characterize the dynamic decay trend of the charging parameters as the charging process progresses. Based on the attenuation trend and the remaining charging capacity, the remaining charging time is determined; In response to the remaining charging time determination strategy being the third strategy, the rate of change is determined based on the charging parameters, wherein the rate of change characterizes the rate at which power changes with the amount of electricity. The remaining charging time is determined based on the rate of change and the remaining charging capacity.

[0027] Optionally, before outputting the remaining charging time, the device for determining the remaining charging time of the device further includes a first determining module; The first determining module is used to determine the deviation between the predicted remaining charging time and the actual remaining charging time of the charging device based on the historical charging data of the charging device. Based on the deviation value, the optimization coefficients are determined; Based on the optimization coefficient, the remaining charging time is optimized.

[0028] Optionally, before outputting the remaining charging time, the device for determining the remaining charging time further includes a second determining module; The second determining module is used to determine the model of the charging device; Based on the model of the charging device, correction parameters are determined. These correction parameters are used to characterize the features associated with the charging device model that affect the estimation of charging rate and duration. Based on the correction parameters, the remaining charging time is corrected.

[0029] An electronic device includes a memory, a processor, and a computer program stored in the memory, wherein when the processor executes the computer program, it implements a method for determining the remaining charging time of the device as described above, which is optional in any of the above methods.

[0030] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for determining the remaining charging time of a device as described above, for any of the optional methods above.

[0031] By employing the above technical solution, this disclosure provides a method for determining the remaining charging time of a device. First, in response to detecting that the charging device is placed on a wireless charging device, the current battery level, charging parameters, and capacity data of the charging device are acquired. The charging parameters characterize the energy transfer status during charging, and the capacity data characterizes the maximum capacity of the battery. Second, based on the capacity data, the current battery level, and the charging parameters, the remaining charging time of the charging device is determined. Finally, the remaining charging time is output. In this way, by simultaneously acquiring the current battery level (characterizing the real-time charging status), the charging parameters (reflecting the dynamics of energy transfer during charging), and the capacity data (characterizing the inherent properties of the battery) after detecting that the charging device is placed on a wireless charging device, a comprehensive data support system integrating the inherent properties of the battery, real-time charging progress, and energy transfer efficiency is constructed. This solves the problem of estimation bias caused by relying on single or partial data in existing technologies. Simultaneously, the complementarity of this data system effectively offsets the fluctuations and distortions caused by factors such as vehicle bumps, power fluctuations, and electromagnetic interference in vehicle scenarios, making the determination of the remaining charging time more suitable for the energy transfer characteristics of dynamic vehicle scenarios and ensuring the accuracy of the time result. Stability and reference reliability; based on this, by integrating the above core data to calculate and output the remaining charging time, users can clearly know the charging status without subjective guessing or frequently operating the charging device to check the progress. This facilitates the advance planning of charging rhythm and trip arrangements, avoiding the problems of ending the trip early without a full charge or wasting time by waiting too long, significantly improving the practical value and user experience of the in-vehicle wireless charging function. It also reduces driving distraction caused by checking the device while driving. At the same time, the comprehensive core data collected can also provide a reliable input basis for subsequent phased calculations, model adaptation corrections, historical data optimizations and other refined strategies, enhancing the flexibility and scalability of the entire technical solution.

[0032] The above description is merely an overview of the technical solution disclosed herein. In order to better understand the technical means of this disclosure and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this disclosure more apparent and understandable, specific embodiments of this disclosure are described below. Attached Figure Description

[0033] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this disclosure. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 One of the flowcharts illustrating a method for determining the remaining charging time of a device according to an embodiment of this disclosure is shown. Figure 2A second schematic flowchart of a method for determining the remaining charging time of a device according to an embodiment of this disclosure is shown. Figure 3 The third schematic flowchart illustrates the method for determining the remaining charging time of a device according to an embodiment of this disclosure; Figure 4 The fourth flowchart illustrates a method for determining the remaining charging time of a device according to an embodiment of this disclosure. Figure 5 A schematic diagram of a device for determining the remaining charging time of a device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0034] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0035] Existing in-vehicle wireless charging devices lack an integrated module for calculating remaining charging time in their hardware and software design. They focus solely on power transmission without addressing users' needs for predicting charging duration. Furthermore, the wireless charging protocol itself does not support real-time reading of battery power information, making it difficult for the in-vehicle system to obtain accurate basic power data. Additionally, some existing solutions rely on the charging device's own application for time estimation, but data interaction between the in-vehicle system and the device suffers from latency and asynchrony. Moreover, they fail to consider differences in charging strategies among different brands of devices (such as different fast-charging stage switching thresholds and power decay patterns), ultimately resulting in poor accuracy and insufficient real-time performance in the estimation results, failing to meet users' core need for predictive charging time.

[0036] To address the technical problem of poor user experience caused by the lack of prediction and real-time display capabilities for remaining charging time in existing in-vehicle wireless charging systems, this disclosure provides a method for determining the remaining charging time of a device, such as... Figure 1 As shown, Figure 1 This is a schematic flowchart illustrating a method for determining the remaining charging time of a device according to an embodiment of this disclosure. The method includes: S11. In response to detecting that the charging device is placed on the wireless charging device, obtain the current battery power, charging parameters and capacity data of the charging device.

[0037] Among them, the charging parameters are used to characterize the state of electrical energy transmission during the charging process, and the capacity data is used to characterize the maximum capacity of the battery of the charging device.

[0038] Specifically, when the sensing module of the vehicle wireless charging device detects that the charging device has been placed in the charging area and established electromagnetic coupling, the data acquisition process in this step is automatically triggered. This is based on the basic working logic of vehicle wireless charging, ensuring that data acquisition and charging start-up are synchronized, and avoiding information lag.

[0039] The current battery level is obtained through a two-way communication link between the vehicle and the charging equipment. Charging parameters that characterize the power transmission status are collected through the wireless charging module. Capacity data is obtained through a query link between the device model and the cloud database. The acquisition process of these three types of data is triggered synchronously and is interconnected. Among them, the device model can be read through a protocol, such as relying on the wireless charging standard protocol or Bluetooth / Wi-Fi communication link to directly read the model information from the charging equipment system.

[0040] Specifically, a real-time data link between the vehicle's infotainment system and the charging device can be established through in-vehicle Bluetooth or Wi-Fi communication protocols to directly read the current battery level fed back by the device system, ensuring data real-time performance. If Bluetooth / Wi-Fi communication is temporarily interrupted, the charging device's battery management system can be used to divide the battery level into low, medium, and high segments on a periodic basis. The temporary battery level can be estimated by reporting it to the in-vehicle wireless charging module through the dedicated data frame field reserved in the protocol. The estimate will be automatically corrected after communication is restored.

[0041] Charging parameters can be collected in real time by the vehicle's wireless charging module. Specifically, these parameters include charging current, charging voltage, and charging power. These parameters are obtained through the communication channel of the wireless charging protocol. The charging power is calculated and verified in real time based on the current and voltage. At the same time, a preset quantitative abnormal threshold is set based on the charging stage. Combined with the anti-shake mechanism, instantaneous abnormal values ​​caused by vehicle bumps and poor contact are eliminated to ensure parameter stability.

[0042] Capacity data serves as the benchmark for calculations. The model of the charging device can be read first via the wireless charging protocol, and then the vehicle system can send the model information to the car manufacturer's cloud database to query the maximum battery capacity corresponding to that model. The cloud database has pre-stored mainstream mobile phone models and capacity data on the market and will be updated in real time according to the new product release schedule. If a niche model cannot be found, the average capacity of the same brand and series of models can be used as a temporary value, and a cloud update request will be triggered at the same time.

[0043] For example, when a user places their phone on the in-car wireless charging pad, the wireless charging device's sensing module detects the phone and automatically activates the in-car Bluetooth module to establish a communication link with the phone. Every 0.5 seconds, it reads the current battery level (e.g., 35%) fed back by the phone's system. At the same time, it reads the phone model through a protocol, and the wireless charging module collects parameters such as charging current, charging voltage, and charging power in real time. The in-car system sends the phone model to the automaker's cloud database to query and obtain the maximum battery capacity corresponding to that model, thus completing the synchronous acquisition of three types of core data.

[0044] In this embodiment, after the charging device triggers the detection mechanism of the vehicle-mounted wireless charging device, three types of key data—inherent battery attributes, real-time status, and transmission efficiency—are collected simultaneously. This addresses the shortcomings of existing technologies in acquiring single and incomplete data, providing a complete and reliable input basis for subsequent calculation of remaining charging time.

[0045] S12. Based on capacity data, current battery power, and charging parameters, determine the remaining charging time of the charging device.

[0046] Specifically, the remaining charging capacity is first determined by the difference between the capacity data and the current battery level. Then, the charging parameters are processed to remove anomalies and screen for stability. Finally, an adaptive algorithm is used to adapt to the characteristics of different charging stages (constant current fast charging, constant current buffering, and end-stage decay), and the calculation logic is dynamically adjusted to ensure that the duration calculation adapts to dynamic changes such as power fluctuations and stage switching.

[0047] First, calculate the remaining charging capacity based on the capacity data and the current battery level: ΔC = capacity data - current battery level, thus determining the total amount of energy that needs to be replenished. Then, perform secondary optimization on the charging parameters. Stable charging parameters can be filtered out using a sliding window algorithm to eliminate abnormal data such as instantaneous pulse power and voltage jumps, thereby obtaining core calculation parameters such as effective charging current and effective charging power.

[0048] For example, given a capacity of 4700mAh and a current battery level of 35%, first calculate the remaining charging capacity as 4700mAh × (1-35%) = 3055mAh. Then, using a sliding window algorithm (3-second window length), eliminate transient current jumps caused by vehicle vibrations (such as anomalies like a sudden drop from 1800mA to 500mA), resulting in a stable effective current of 1780mA. Combined with the current charging power of 16.2W (≥10W fast charging threshold), it is determined to be in the constant current fast charging stage. Using the linear calculation model in the adaptive algorithm, calculate the base charging time as "remaining charging capacity ÷ effective current" (3055mAh ÷ 1780mA ≈ 1.72 hours). Adjust the base time based on the phone's fast charging efficiency characteristics to obtain the final remaining charging time.

[0049] Throughout the calculation process, the remaining time is recalibrated based on the updated charging parameters (such as changes in current and power) and the remaining charging capacity to ensure that the results change dynamically with the charging status.

[0050] In this embodiment, the capacity data, current battery level, and charging parameters obtained in S11 are used as core inputs. Through data integration, characteristic analysis, and algorithm adaptation, the remaining charging time is derived. This solves the problem that the single formula calculation in the prior art ignores the dynamic characteristics of charging and the differences between devices, and makes the time calculation result fit the dynamic scene of the vehicle and the charging pattern of the mobile phone.

[0051] S13, Output remaining charging time.

[0052] Specifically, the output format is adapted to the display logic of the in-vehicle infotainment system, supports simultaneous display and dynamic updates on multiple carriers, and can be overlaid with voice prompts. The displayed content is concise and clear, and the update frequency matches the calculation, avoiding information lag from affecting user judgment.

[0053] For example, the vehicle's infotainment system calculates the remaining charging time of 1.68 hours (approximately 101 minutes) and simultaneously pushes it to the central control screen and the HUD head-up display. The central control screen displays "Remaining charging time: 1 hour 41 minutes" in the form of a progress bar (35% charged, 65% not charged), while the HUD projects a simplified version of "1h41min" onto the windshield. The system is also set to update the display content every second. When the remaining time drops to 10 minutes, the car audio system automatically issues a voice prompt: "Your phone is almost fully charged, please check." This allows users to monitor the charging progress without looking down while driving.

[0054] Meanwhile, the remaining charging time is updated every second to keep in line with the calculation and calibration frequency of S12, so as to avoid the display information being lagging behind. If there is an abnormality in the charging parameters (such as a sudden drop in power due to poor contact), a prompt will be displayed on the output interface that says "Charging status is unstable, duration is for reference only", so as to ensure that users get accurate status feedback.

[0055] In this embodiment, the remaining charging time calculated in S12 is output through the vehicle's mainstream display carrier, ensuring that users can intuitively obtain the charging progress without additional operation during driving. This solves the problem of existing technologies lacking real-time vehicle display and requiring users to frequently check their mobile phones, thus balancing ease of use and driving safety.

[0056] In the above scheme, firstly, in response to the detection that the charging device is placed on the wireless charging device, the current battery level, charging parameters, and capacity data of the charging device are acquired. The charging parameters characterize the energy transfer status during charging, and the capacity data characterizes the maximum capacity of the battery. Secondly, based on the capacity data, current battery level, and charging parameters, the remaining charging time of the charging device is determined. Finally, the remaining charging time is output. In this way, by simultaneously acquiring the current battery level (characterizing the real-time charging status), charging parameters (reflecting the dynamics of energy transfer during charging), and capacity data (characterizing the inherent properties of the battery) after detecting that the charging device is placed on the wireless charging device, a comprehensive data support system integrating battery inherent properties, real-time charging progress, and energy transfer efficiency is constructed. This solves the problem of estimation bias caused by relying on single or partial data in existing technologies from the source. At the same time, the complementarity of this data system can effectively offset the fluctuations and distortions caused by factors such as vehicle bumps, power fluctuations, and electromagnetic interference in the vehicle scenario, making the determination of the remaining charging time more suitable for the energy transfer characteristics of the dynamic vehicle scenario and ensuring the accuracy of the time result. Stability and reference reliability; based on this, by integrating the above core data to calculate and output the remaining charging time, users can clearly know the charging status without subjective guessing or frequently operating the charging device to check the progress. This facilitates the advance planning of charging rhythm and trip arrangements, avoiding the problems of ending the trip early without a full charge or wasting time by waiting too long, significantly improving the practical value and user experience of the in-vehicle wireless charging function. It also reduces driving distraction caused by checking the device while driving. At the same time, the comprehensive core data collected can also provide a reliable input basis for subsequent phased calculations, model adaptation corrections, historical data optimizations and other refined strategies, enhancing the flexibility and scalability of the entire technical solution.

[0057] In some embodiments, such as Figure 2 As shown, the method for determining the remaining charging time of the device also includes: S121. Based on the current battery power and charging parameters, determine the charging stage of the charging device.

[0058] Specifically, the core criteria for determining the charging stage of a device are the stability of charging parameters, power threshold, and energy threshold. This approach adapts to wireless charging standards (such as fast charging power threshold and constant current / constant voltage stage characteristics) and is also compatible with the different charging strategies of various mobile phone brands (such as different fast charging start thresholds and different triggering times for end-stage degradation).

[0059] When the charging parameters meet the first condition, the charging stage is determined to be the constant current fast charging stage. The first condition is used to characterize the condition that the current is stable and the power meets the standard in the charging parameters. The first condition can be that the current is stable and the power meets the standard. For example, the current stability is quantified by the fluctuation amplitude ≤ ±5% to avoid the interference of instantaneous fluctuations caused by vehicle bumps. The power meets the standard fast charging threshold (≥10W) to ensure that the high efficiency characteristics of the constant current fast charging stage are identified.

[0060] For example, if the charging parameters are "current 1250mA (fluctuation ≤ ±5%), voltage 9V, power 11.25W (≥10W fast charging threshold)", the first condition is met, and it is determined to be in the constant current fast charging stage.

[0061] When the charging parameters meet the second condition, the charging stage is determined to be the constant current buffer stage. The second condition is used to characterize the condition in the charging parameters where the current is stable but the power does not reach the fast charging threshold. The second condition can be that the current is stable but the power does not reach the fast charging threshold. For example, the power range is limited to 5W≤P<10W (standard normal charging range), which distinguishes it from the fast charging stage and also separates it from the low power stage at the end, thus solving the problem of fuzzy estimation in the intermediate stage.

[0062] For example, if the power drops to 8W during charging (5W≤8W<10W) and the current remains stable at 1000mA (fluctuation ≤±5%), the second condition is met, and it is determined to be the constant current buffer stage.

[0063] If the current battery level is greater than the battery level threshold and the charging parameters meet the third condition, the charging stage is determined to be the final stage of degradation. The third condition is used to characterize the conditions under which the power and current in the charging parameters are decaying. The third condition can be that the battery level is up to standard and the power / current is decaying. For example, the battery level threshold is set to 90%, the power is ≤5W and the current decays by ≥10% every 10 seconds, which fits the characteristics of power decay at the end of charging. The requirement to meet the dual conditions is to avoid misjudging the low power caused by poor contact as the final stage and to ensure the accuracy of the judgment.

[0064] For example, if the current battery level rises to 92% (>90% battery level threshold), and the charging parameters are "power 4.5W (≤5W), current continuously decreasing from 500mA to 400mA (attenuation ≥10% every 10 seconds)", it meets the third condition and is judged to be in the final stage of degradation.

[0065] In this embodiment, the charging stage is distinguished based on the real-time status of the charging device (current battery level) and the power transmission status (charging parameters). This solves the estimation bias problem caused by the prior art ignoring the differences in charging stages and using a single calculation logic, and provides a basis for subsequent matching of dedicated calculation strategies.

[0066] S122. Based on the charging stage, determine different strategies for determining the remaining charging time.

[0067] Specifically, the mapping rules strictly match the stage division of S121, and each stage corresponds to a dedicated calculation strategy: the first strategy of the constant current fast charging stage focuses on linear calculation under efficient and stable transmission, adapting to the characteristics of power meeting the standard and current stability; the second strategy of the constant current buffer stage focuses on segmented calculation under the attenuation trend, adapting to the transition characteristics of power not meeting the standard but current still stable; the third strategy of the final attenuation stage focuses on integral calculation under low power attenuation, adapting to the final characteristics of continuous power / current attenuation.

[0068] When the charging stage is the constant current fast charging stage, the strategy for determining the remaining charging time is the first strategy. The core of the first strategy is to directly deduce the remaining time based on the stable effective charging power, which is suitable for the high efficiency and stable parameters of the fast charging stage.

[0069] When the charging stage is a constant current buffer stage, the strategy for determining the remaining charging time is the second strategy. The core of the second strategy is to combine the current decay trend and calculate separately for the stable segment and the decay segment, adapting to the characteristics of the slow change of parameters in the buffer stage.

[0070] When the charging stage is the final decay stage, the strategy for determining the remaining charging time is the third strategy. The core of the third strategy is based on the decay law of power with the amount of electricity, and the duration is derived through integral calculation to adapt to the characteristics of rapid decay of parameters at the end.

[0071] In this embodiment, by establishing a mapping relationship between charging stages and calculation strategies, the duration calculation logic of different stages is made to fit their charging characteristics, solving the problem that the existing one-size-fits-all calculation model cannot adapt to the dynamic changes of multiple stages, and improving the targeting and fit of duration calculation.

[0072] S123. Determine the remaining charging time based on the strategy determined by capacity data, charging parameters and remaining charging time.

[0073] Specifically, based on the core logic of capacity data and the current battery level of the charging device, the remaining charging capacity is calculated. Then, according to different strategies, the corresponding key parameters (effective charging power / attenuation trend / rate of change) are matched. The key parameters are all from the charging parameters after anomaly removal. Furthermore, relying on the cloud database, the system adapts to the characteristics of multiple brands of devices (such as the rate of change of different devices and differences in fast charging efficiency). The calculation process dynamically responds to parameter changes and is calibrated every second to ensure real-time performance and reliability.

[0074] When the remaining charging time determination strategy is the first strategy, the effective charging power is determined based on the charging parameters; then, the remaining charging time is determined based on the effective charging power and the remaining charging capacity. The effective charging power can be determined by using a sliding window algorithm to eliminate instantaneous pulse power caused by vehicle bumps and poor contact, thus obtaining the true and stable effective charging power P.e ff (e.g., if the collected power is 13.5W, after removing outliers that suddenly spike to 15W, P) e ff=13.5W), its core function is to characterize the actual power transmission efficiency after noise reduction.

[0075] For example, according to the formula "Remaining time = ΔC ÷ (P)", e Derivation of "ff÷charging voltage", such as ΔC=3150mAh, P e If ff = 13.5W and voltage 9V, then the current = 13500mW ÷ 9V = 1500mA, and the remaining time = 3150mAh ÷ 1500mA = 2.1 hours. It should be noted that this is only an example and does not limit the specific method and formula for determining the remaining charging time.

[0076] When the remaining charging time determination strategy is the second strategy, the decay trend is determined based on the charging parameters. The decay trend is used to characterize the dynamic decay trend of the charging parameters as the charging process progresses. Thus, the remaining charging time is determined based on the decay trend and the remaining charging capacity. The decay trend k (unit mA / s) can be calculated by collecting current data for 5 consecutive seconds (e.g., if the current drops from 1200mA to 1100mA, then k=(1200-1100)mA / 5s=20mA / s), characterizing the gradual change trend of the current as the charging process progresses, and adapting to the transition characteristics of the buffer stage where the power does not reach fast charging, but the current still decays stably.

[0077] For example, a segmented calculation logic is used, divided into a current stabilization segment and a current decay segment: the stabilization segment is calculated based on the current effective current, and the decay segment adapts to the continuous decreasing trend of the current through integral calculation (e.g., ΔC=1800mAh, the stabilization segment covers 1000mAh, duration = 1000÷1100≈0.91 hours; the decay segment covers 800mAh, calculated by ∫dC / (1100-20t)≈0.83 hours, total duration≈1.74 hours), avoiding the deviation caused by a single formula ignoring the decay trend. It should be noted that this is only an example and does not limit the specific method and formula for determining the remaining charging time.

[0078] When the remaining charging time determination strategy is the third strategy, the rate of change is determined based on the charging parameters. The rate of change characterizes the rate at which power changes with the amount of electricity. Therefore, the remaining charging time is determined based on the rate of change and the remaining charging capacity. The rate of change 'a' (in W / %) can be retrieved from a cloud database that stores the final charging power decay curves of various mobile phone brands, characterizing the rate of power change as the battery saturates.

[0079] For example, using integral calculations, based on the remaining charging capacity (e.g., ΔC = 450mAh, corresponding to 90%-100% capacity) and the predicted power change trend (P...t =Current power - a × (Real-time remaining power / capacity data)), by integrating ∫dC / (P) t The calculation time is calculated by dividing the voltage by the time taken, avoiding the problem of a sudden increase in estimated time at the end of the traditional linear calculation. It should be noted that this is only an example and does not limit the specific method and formula for determining the remaining charging time.

[0080] Meanwhile, the duration is recalibrated every second based on updated charging parameters (such as current and power changes) and remaining charging capacity to ensure that the duration results reflect changes in charging status in real time and avoid information lag.

[0081] The above solution addresses the problem of existing technologies being unable to clearly define the characteristics of the charging process by dividing the charging process into three stages based on the current battery level and charging parameters: constant current fast charging, constant current buffering, and final attenuation. It establishes a mapping between each stage and a specific strategy for determining the remaining charging time, ensuring that the calculation logic for each stage aligns with its charging patterns and avoiding the rigidity of a single model adapting to all stages. First, the remaining charging capacity is determined based on capacity data and the current battery level. Then, core parameters such as effective charging power, attenuation trend, or rate of change are matched according to different strategies for targeted calculations. This ensures the accuracy of the calculation benchmark while adapting to the dynamic characteristics of energy transmission at each stage, effectively offsetting estimation deviations caused by parameter fluctuations in in-vehicle scenarios and differences in charging strategies among multiple brands of equipment, thus improving the accuracy and reliability of the remaining charging time estimation.

[0082] In some embodiments, such as Figure 3 As shown, before outputting the remaining charging time, the method for determining the remaining charging time of the device also includes: S14. Based on the historical charging data of the charging equipment, determine the deviation between the predicted remaining charging time and the actual remaining charging time.

[0083] Specifically, historical charging data can be stored locally in the vehicle's infotainment system or in a cloud database, containing key information from the past 20 complete charging processes. This key information may include: predicted remaining charging time for each stage (e.g., 40 minutes for fast charging and 10 minutes for the final stage); actual remaining charging time for the corresponding stage; dynamic changes in charging parameters (current, power, voltage); auxiliary information for the charging scenario (e.g., battery health, vehicle power status during charging, ambient temperature); deviation calculation proceeds with a hierarchical logic of single-cycle deviation, stage deviation, and overall deviation, ensuring that the deviation data accurately reflects the estimated deviation patterns of the device under different charging scenarios. Furthermore, during data filtering, invalid data from abnormal charging (e.g., power outages or poor contact) is removed based on preset abnormal charging judgment criteria and data verification rules to avoid interference.

[0084] In this embodiment, by tracing the historical charging data of the charging device, the deviation pattern between the predicted duration and the actual duration is extracted, which solves the defects of the existing technology that lacks self-learning ability and cannot adapt to the individual charging characteristics of the device, and provides a quantitative basis for subsequent optimization.

[0085] S15. Determine the optimization coefficients based on the deviation value.

[0086] Specifically, the optimization coefficients can be determined by first calculating the statistical characteristics of historical deviation values ​​(such as arithmetic mean, weighted average, with the deviations of the three most recent charging cycles given higher weight) to obtain the average deviation rate; and then deriving the optimization coefficients based on the average deviation rate.

[0087] For example, the formula for deriving the optimization coefficient can be "Optimization coefficient K = 1 - average deviation rate". If the average deviation rate is positive, it means the prediction is too long and the optimization coefficient is <1; if the average deviation rate is negative, it means the prediction is too short and the optimization coefficient is >1. It should be noted that this is only an example and does not limit the specific content and formula for determining the optimization coefficient.

[0088] At the same time, coefficient constraint ranges are set to avoid overcorrection caused by extreme deviations, ensuring that the optimization results are stable and reliable.

[0089] For example, the constraint range for the optimization coefficient is set to 0.8≤K≤1.2. If a device's average deviation rate reaches -30% due to a single abnormal charge, directly calculating K=1.3 would lead to overcorrection (significantly extending the prediction time). In this case, the constraint mechanism is triggered to limit K to 1.2, ensuring that the optimization result is stable and reliable and does not deviate from the actual charging pattern.

[0090] In this embodiment, by establishing a mapping relationship between deviation values ​​and optimization coefficients, historical deviation patterns are quantified into parameters that can be directly used for correction, solving the problem that deviation data in existing technologies cannot effectively guide optimization, and enabling duration correction to have a clear execution logic.

[0091] S16. Optimize the remaining charging time based on the optimization coefficient.

[0092] Specifically, the correction logic follows the principle of real-time application and dynamic updating: the optimization coefficient is bound to the current charging device and only applies to the duration calculation of that device, avoiding coefficient confusion between different devices; at the same time, after each complete charge, historical charging data is automatically updated, deviation values ​​and optimization coefficients are recalculated, realizing a self-learning closed loop of optimization after each charge, so that the coefficients always adapt to dynamic characteristics such as device battery aging and changes in charging strategies.

[0093] In this embodiment, by combining the optimization coefficient with the calculated basic remaining charging time, the estimation result is dynamically corrected, which solves the defect of the prior art that there is no iterative optimization after a single estimation, and allows the duration estimation to gradually conform to the actual charging pattern of the device as the number of charging times increases.

[0094] The above solution addresses the shortcomings of existing technologies that cannot accumulate individual charging characteristics of devices and are difficult to capture specific charging patterns by mining historical charging data of charging devices and extracting the deviation value between the predicted and actual remaining charging time. It transforms the deviation value into a quantitative optimization coefficient, clarifies the correction rules, and avoids the blindness of blind optimization when the deviation data cannot effectively guide the optimization. The optimization coefficient is applied to correct the basic remaining charging time and the coefficient is updated iteratively with each complete charge. This not only adapts to the dynamic characteristics of devices such as battery aging and changes in charging strategies, but also makes the estimation error gradually converge with the increase of charging times, significantly improving the long-term stability and accuracy of the remaining charging time estimation.

[0095] In some embodiments, such as Figure 4 As shown, before outputting the remaining charging time, the method for determining the remaining charging time of the device also includes: S17. Determine the model of the charging equipment.

[0096] Specifically, model identification can be achieved through a dual-link approach of protocol reading and verification matching: First, relying on the wireless charging standard protocol or Bluetooth / Wi-Fi communication link, the model information is directly read from the charging equipment system; after reading, the authenticity of the model is verified by a quick comparison between the vehicle system and the cloud device database to avoid interference from false model information. If the reading fails (e.g., due to protocol incompatibility with niche models), the device MAC address is called to query the model in reverse to ensure identification coverage.

[0097] In this embodiment, the unique model identifier of the device is obtained through communication and interaction between the vehicle-mounted wireless charging system and the charging device, which solves the shortcomings of the prior art that ignores the differences in device models and uses a general model for estimation, and establishes a correlation for subsequent matching of dedicated correction parameters.

[0098] S18. Determine the correction parameters based on the model of the charging equipment.

[0099] Among them, the correction parameters are used to characterize the features associated with the charging device model that affect the estimation of charging rate and duration.

[0100] Specifically, the design of the modified parameters can cover three major dimensions: charging strategy, stage characteristics, and battery adaptation. These parameters are stored in a dedicated database of models and parameters in the automaker's cloud (which is regularly synchronized with parameters of new products from the brand). For example, the modified parameters can include charging strategy parameters such as the upper limit of fast charging power and the power limit triggering conditions; stage characteristic parameters such as the power threshold for switching between constant current fast charging / buffering / end stage and the power decay benchmark rate for each stage; and battery adaptation parameters such as the battery internal resistance adaptation coefficient and the temperature sensitivity threshold (the difference in power response to temperature for different battery models).

[0101] In this embodiment, by mapping the identified device model to a specific correction parameter, the differences in charging strategies, power limits, battery characteristics, etc. of different models are quantified into calculable parameters, solving the problem that the general parameters of the prior art cannot be adapted to individual models, and providing a quantitative basis for correction.

[0102] S19. Based on the correction parameters, the remaining charging time is corrected.

[0103] Specifically, the correction logic follows the principle of phased correction and overall characteristic compensation. Phased correction: Phase characteristic parameters (such as switching threshold and attenuation trend) are integrated into the duration calculation of the corresponding phase. For example, the phase division nodes are corrected using the model-specific switching threshold, and the calculation model of the second / third strategy is adjusted using the attenuation reference rate. Overall compensation: The total duration is calibrated a second time using charging strategy parameters (such as efficiency coefficient) and battery adaptation parameters (such as internal resistance coefficient). After correction, the parameters and results are verified to ensure that the corrected duration does not deviate from the actual charging logic (such as the corrected duration in the fast charging phase does not exceed the theoretical minimum duration), and is synchronously optimized with the cloud update of model parameters.

[0104] In this embodiment, by combining the dedicated correction parameters with the basic remaining charging time, the characteristic differences of different models are dynamically compensated, solving the problem that the general estimation in the prior art has too large a deviation for some models, and making the time estimation fit the charging pattern of each model.

[0105] The above solution identifies the charging device model, overcoming the limitations of existing technologies that ignore device model differences and use general models for estimation, thus laying a solid foundation for dedicated adaptation. Based on the correction parameters that characterize the device's dedicated charging strategy, stage switching rules, and battery characteristics through model matching, the characteristic differences of different brands / models are quantified into calculable basis, avoiding the problem of insufficient adaptation caused by general parameters. The application of correction parameters to perform staged correction and overall calibration of the remaining charging time effectively offsets the estimation deviations caused by differences in fast charging protocols of multiple brands, different stage decay trends, and differences in battery internal resistance characteristics. The three aspects work together to form a closed loop of adaptation, including model positioning, characteristic quantification, and correction, which significantly improves the compatibility of multiple brands and models of devices, ensuring that the estimation errors of mainstream and niche models meet the requirements. This allows users to obtain realistic charging time predictions regardless of the model they use, reducing distraction when checking devices while driving and optimizing the user experience and driving safety of in-vehicle wireless charging.

[0106] In addition, such as Figure 5 As shown, Figure 5 This is a schematic diagram of a device 500 for determining the remaining charging time of a device according to an embodiment of this disclosure. The device includes: The acquisition module 501 is used to acquire the current battery power, charging parameters and capacity data of the charging device in response to detecting that the charging device is placed in the wireless charging device. The charging parameters are used to characterize the power transmission status during the charging process, and the capacity data is used to characterize the maximum capacity of the battery of the charging device. The determination module 502 is used to determine the remaining charging time of the charging device based on capacity data, current battery power, and charging parameters. Output module 503 is used to output the remaining charging time.

[0107] In the above scheme, firstly, in response to the detection that the charging device is placed on the wireless charging device, the current battery level, charging parameters, and capacity data of the charging device are acquired. The charging parameters characterize the energy transfer status during charging, and the capacity data characterizes the maximum capacity of the battery. Secondly, based on the capacity data, current battery level, and charging parameters, the remaining charging time of the charging device is determined. Finally, the remaining charging time is output. In this way, by simultaneously acquiring the current battery level (characterizing the real-time charging status), charging parameters (reflecting the dynamics of energy transfer during charging), and capacity data (characterizing the inherent properties of the battery) after detecting that the charging device is placed on the wireless charging device, a comprehensive data support system integrating battery inherent properties, real-time charging progress, and energy transfer efficiency is constructed. This solves the problem of estimation bias caused by relying on single or partial data in existing technologies from the source. At the same time, the complementarity of this data system can effectively offset the fluctuations and distortions caused by factors such as vehicle bumps, power fluctuations, and electromagnetic interference in the vehicle scenario, making the determination of the remaining charging time more suitable for the energy transfer characteristics of the dynamic vehicle scenario and ensuring the accuracy of the time result. Stability and reference reliability; based on this, by integrating the above core data to calculate and output the remaining charging time, users can clearly know the charging status without subjective guessing or frequently operating the charging device to check the progress. This facilitates the advance planning of charging rhythm and trip arrangements, avoiding the problems of ending the trip early without a full charge or wasting time by waiting too long, significantly improving the practical value and user experience of the in-vehicle wireless charging function. It also reduces driving distraction caused by checking the device while driving. At the same time, the comprehensive core data collected can also provide a reliable input basis for subsequent phased calculations, model adaptation corrections, historical data optimizations and other refined strategies, enhancing the flexibility and scalability of the entire technical solution.

[0108] In one specific embodiment, the determining module 502 is further configured to: Based on the current battery level and charging parameters, determine the charging stage of the charging device; Based on the charging stage, different strategies for determining the remaining charging time are established. The remaining charging time is determined based on the strategy based on capacity data, charging parameters, and remaining charging time.

[0109] In one specific embodiment, the determining module 502 is further configured to: In response to the charging parameters meeting the first condition, the charging stage is determined to be the constant current fast charging stage. The first condition is used to characterize the condition that the current is stable and the power meets the standard in the charging parameters. In response to the charging parameters meeting the second condition, the charging stage is determined to be a constant current buffer stage. The second condition is used to characterize the condition in the charging parameters where the current is stable but the power does not reach the fast charging threshold. In response to the current battery level being greater than the power threshold and the charging parameters meeting the third condition, the charging stage is determined to be the final decay stage. The third condition is used to characterize the condition in which the power and current in the charging parameters are decaying.

[0110] In one specific embodiment, the determining module 502 is further configured to: In response to the constant current fast charging stage, the strategy for determining the remaining charging time is the first strategy. In response to the constant current buffering phase during the charging phase, the strategy for determining the remaining charging time is the second strategy. Since the charging phase is the final decay phase, the strategy for determining the remaining charging time is the third strategy.

[0111] In one specific embodiment, the determining module 502 is further configured to: The remaining charging capacity is determined based on capacity data and the current battery level of the charging device; The remaining charging time is determined based on the remaining charging capacity, charging parameters, and remaining charging time determination strategy.

[0112] In one specific embodiment, the determining module 502 is further configured to: The remaining charging time determination strategy is the first strategy. Based on the charging parameters, the effective charging power is determined. The effective charging power is used to characterize the real and stable power transmission efficiency. The remaining charging time is determined based on the effective charging power and the remaining charging capacity. The remaining charging time determination strategy is the second strategy. Based on the charging parameters, the decay trend is determined. The decay trend is used to characterize the dynamic decay trend of the charging parameters as the charging process progresses. Based on the decay trend and the remaining charging capacity, determine the remaining charging time; The strategy for determining the remaining charging time is the third strategy, which determines the rate of change based on charging parameters. The rate of change characterizes the rate at which power changes with the amount of electricity. The remaining charging time is determined based on the rate of change and the remaining charging capacity.

[0113] In one specific embodiment, before outputting the remaining charging time, the device for determining the remaining charging time of the device 500 further includes a first determining module; The first determining module is used to determine the deviation between the predicted remaining charging time and the actual remaining charging time of the charging device based on the historical charging data of the charging device. Determine the optimization coefficients based on the deviation values; The remaining charging time is optimized based on the optimization coefficient.

[0114] In one specific embodiment, the device 500 for determining the remaining charging time of the device further includes a second determining module before outputting the remaining charging time; The second determining module is used to determine the model of the charging device; Based on the model of the charging device, correction parameters are determined. These correction parameters are used to characterize the characteristics associated with the charging device model that affect the estimation of charging rate and duration. The remaining charging time is adjusted based on the corrected parameters.

[0115] Regarding the apparatus in the above embodiments, the specific manner in which each unit performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0116] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory. When the processor executes the computer program, it implements any of the optional methods for determining the remaining charging time of the device as described above, thus achieving the same effect as the implementation method described above.

[0117] This embodiment also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements any of the optional methods described above for determining the remaining charging time of a device.

[0118] The beneficial effects of the above embodiments can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0119] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0120] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0121] In the description of this disclosure, it should be understood that if the terms "upper", "lower", "front", "rear", "left" and "right" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the position or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this disclosure.

[0122] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0123] The above are merely embodiments of this disclosure and are not intended to limit the scope of this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of the claims of this disclosure.

Claims

1. A method for determining the remaining charging time of a device, characterized in that, The method includes: In response to detecting that the charging device is placed in the wireless charging device, the current battery power, charging parameters and capacity data of the charging device are obtained. The charging parameters are used to characterize the power transmission status during the charging process, and the capacity data are used to characterize the maximum capacity of the battery of the charging device. Based on the capacity data, the current battery level, and the charging parameters, the remaining charging time of the charging device is determined; Output the remaining charging time.

2. The determination method according to claim 1, characterized in that, Determining the remaining charging time of the charging device based on the capacity data, the current battery level, and the charging parameters includes: Based on the current battery level and the charging parameters, the charging stage of the charging device is determined; Based on the charging stage, different strategies for determining the remaining charging time are determined. The remaining charging time is determined based on the capacity data, the charging parameters, and the remaining charging time determination strategy.

3. The determination method according to claim 2, characterized in that, Determining the charging stage of the charging device based on the current battery level and the charging parameters includes: In response to the charging parameters satisfying the first condition, the charging stage is determined to be a constant current fast charging stage, where the first condition is used to characterize the condition that the current is stable and the power meets the standard in the charging parameters. In response to the charging parameters satisfying the second condition, the charging stage is determined to be a constant current buffer stage. The second condition is used to characterize the condition in the charging parameters where the current is stable but the power does not reach the fast charging threshold. In response to the current battery level being greater than a power threshold and the charging parameters meeting a third condition, the charging stage is determined to be the final decay stage, whereby the third condition characterizes the condition that the power and current in the charging parameters are decaying.

4. The determination method according to claim 3, characterized in that, The strategy for determining different remaining charging time based on the charging stage includes: In response to the charging stage being the constant current fast charging stage, the remaining charging time determination strategy is determined to be the first strategy. In response to the charging phase being the constant current buffering phase, the remaining charging duration determination strategy is determined to be the second strategy. In response to the charging phase being the final decay phase, the remaining charging duration determination strategy is determined to be the third strategy.

5. The determination method according to claim 2, characterized in that, The method of determining the remaining charging time based on the capacity data, the charging parameters, and the remaining charging time determination strategy includes: Based on the capacity data and the current battery level of the charging device, the remaining charging capacity is determined; The remaining charging time is determined based on the remaining charging capacity, the charging parameters, and the remaining charging time determination strategy.

6. The determination method according to claim 5, characterized in that, The method for determining the remaining charging time based on the remaining charging capacity, the charging parameters, and the remaining charging time determination strategy includes: In response to the remaining charging time determination strategy being the first strategy, the effective charging power is determined based on the charging parameters, and the effective charging power is used to characterize the real and stable power transmission efficiency. The remaining charging time is determined based on the effective charging power and the remaining charging capacity. In response to the remaining charging time determination strategy being the second strategy, a decay trend is determined based on the charging parameters, and the decay trend is used to characterize the dynamic decay trend of the charging parameters as the charging process progresses. Based on the attenuation trend and the remaining charging capacity, the remaining charging time is determined; In response to the remaining charging time determination strategy being the third strategy, the rate of change is determined based on the charging parameters, wherein the rate of change characterizes the rate at which power changes with the amount of electricity. The remaining charging time is determined based on the rate of change and the remaining charging capacity.

7. The determination method according to claim 1, characterized in that, Before outputting the remaining charging time, the method further includes: Based on the historical charging data of the charging device, the deviation between the predicted remaining charging time and the actual remaining charging time of the charging device is determined. Based on the deviation value, the optimization coefficients are determined; Based on the optimization coefficient, the remaining charging time is optimized.

8. The determination method according to claim 1, characterized in that, Before outputting the remaining charging time, the method further includes: Determine the model of the charging device; Based on the model of the charging device, correction parameters are determined. These correction parameters are used to characterize the features associated with the charging device model that affect the estimation of charging rate and duration. Based on the correction parameters, the remaining charging time is corrected.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, When the processor executes the computer program, it implements the method for determining the remaining charging time of the device as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for determining the remaining charging time of the device as described in any one of claims 1 to 8.

Images