Energy storage data analysis method and system for new energy electric vehicle

Abstract

The invention relates to the technical field of energy storage analysis of new energy electric vehicles, and provides an energy storage data analysis method and system for a new energy electric vehicle. The method comprises the steps of obtaining and collecting electric energy storage data of a new energy electric vehicle in a current period, analyzing the electric energy storage data, determining the energy storage change condition of an energy storage system of a new energy battery in the period, and determining the working state of the energy storage system of the new energy electric vehicle according to the energy storage change condition, the cycle includes a charging process and at least one discharging process. The energy storage change condition of the user in the period is analyzed by taking the charging and discharging behaviors of the user as the period, so that the individuation degree of energy storage data analysis is improved, and the accuracy of energy storage analysis is further improved.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage analysis for new energy electric vehicles, and in particular to an energy storage data analysis method and system for new energy electric vehicles. Background Art

[0002] As the world pays more and more attention to environmental protection and sustainable development, new energy electric vehicles, as a clean and efficient means of transportation, have received extensive attention and development in recent years. One of the core components of new energy electric vehicles is its energy storage system, namely the battery pack, which is directly related to the endurance, charging efficiency and overall performance of the electric vehicle. Therefore, the effective management and optimization of the energy storage system of new energy electric vehicles is particularly important. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present application provides a method and system for analyzing energy storage data for new energy electric vehicles.

[0004] A method for analyzing energy storage data for a new energy electric vehicle, the method comprising:

[0005] Acquire and collect the electric energy storage data of the new energy electric vehicle in the current cycle; the cycle includes a charging process and at least one discharging process;

[0006] Analyze the electric energy storage data to determine the energy storage changes of the energy storage system of the new energy battery during the cycle;

[0007] According to the energy storage change, the working state of the energy storage system of the new energy electric vehicle is determined.

[0008] In one embodiment of the present application, the electric energy storage data includes the power, voltage, current and temperature data of the energy storage system, and the operation data of the new energy electric vehicle; the acquisition and collection of the electric energy storage data of the new energy electric vehicle in the current cycle includes:

[0009] The power, voltage, current and temperature data of the energy storage system are obtained in real time through the on-board battery management system of the new energy electric vehicle; and the operation data of the new energy electric vehicle is obtained in real time through the vehicle computer system of the new energy electric vehicle.

[0010] In one embodiment of the present application, analyzing the electric energy storage data to determine the energy storage change of the energy storage system of the new energy battery in the cycle includes:

[0011] Inputting the electric energy storage data into a pre-trained energy storage change prediction model for processing, and obtaining the energy storage change situation according to the processing result;

[0012] The energy storage change prediction model is a prediction model trained using electric energy storage data in multiple cycles as a training data set.

[0013] In one embodiment of the present application, analyzing the electric energy storage data to determine the energy storage change of the energy storage system of the new energy battery in the cycle includes:

[0014] Analyzing the power, voltage, current and temperature data during the charging process to obtain the battery power increase rate during the charging process;

[0015] Analyze the power consumption during the discharge process and the operation data of the new energy electric vehicle to obtain the battery power consumption rate during the discharge process;

[0016] According to the battery power increase rate and the battery consumption rate, the energy storage change of the energy storage system of the new energy battery in the current cycle is obtained.

[0017] In one embodiment of the present application, analyzing the amount of electricity during the discharge process and the operation data of the new energy electric vehicle to obtain the battery power consumption rate during the discharge process includes:

[0018] The power data of the energy storage system of the new energy electric vehicle at different speeds, loads and running distances is obtained during the discharge process to obtain the battery power consumption rate.

[0019] In one embodiment of the present application, the cycle includes a charging process, at least one discharging process and at least one stopping process, and the method further includes:

[0020] Analyze the power and temperature data during the shutdown process to obtain the self-discharge rate of the battery during the shutdown process;

[0021] The self-discharge rate of the battery during the stop operation process in multiple cycles is obtained, and data fitting is performed according to the time series to determine the energy storage change of the new energy electric vehicle in the stop operation state.

[0022] In one embodiment of the present application, before determining the working state of the energy storage system of the new energy electric vehicle according to the energy storage change, the method further includes:

[0023] Obtaining energy storage changes in multiple historical cycles and generating an energy storage change prediction curve; obtaining the predicted energy storage change in the current cycle based on the energy storage change prediction curve;

[0024] Determining the working state of the energy storage system of the new energy electric vehicle according to the energy storage change includes:

[0025] The energy storage change condition is compared with the predicted energy storage change condition, and the working state of the energy storage system of the new energy electric vehicle is determined according to the comparison result.

[0026] In one embodiment of the present application, the above method further includes:

[0027] Acquire charging data of the charging process of the current cycle; compare the charging data with reference charging data, and generate charging suggestions based on the comparison results; the reference charging data includes but is not limited to charging time, charging power, initial charging power and final charging power.

[0028] In one embodiment of the present application, the above method further includes:

[0029] The working state of the energy storage system is compared with the working state of a reference energy storage system, and an energy storage system usage optimization suggestion is generated according to the comparison result.

[0030] A storage data analysis system for a new energy electric vehicle, the system comprising:

[0031] The electric energy storage data acquisition module is used to acquire and collect the electric energy storage data of the new energy electric vehicle in the current cycle; the cycle includes a charging process and at least one discharging process;

[0032] An electric energy storage data analysis module, used to analyze the electric energy storage data and determine the energy storage changes of the energy storage system of the new energy battery in the cycle;

[0033] The working status confirmation module is used to determine the working status of the energy storage system of the new energy electric vehicle according to the energy storage change.

[0034] This application acquires and collects the electric energy storage data of the new energy electric vehicle in the current cycle, analyzes the electric energy storage data, determines the energy storage changes of the energy storage system of the new energy battery in the cycle, and determines the working state of the energy storage system of the new energy electric vehicle according to the energy storage changes, wherein the cycle includes a charging process and at least one discharging process. Taking the user's charging and discharging behavior as a cycle, the user's energy storage changes in the cycle are analyzed to improve the personalization of energy storage data analysis, thereby improving the accuracy of energy storage analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic flow chart of a method for analyzing energy storage data for new energy electric vehicles provided in one embodiment of the present application. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present application more clear, the exemplary embodiments of the present application will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited to the embodiments described here.

[0037] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0038] During the actual use of new energy electric vehicles, the energy storage state of the battery will continue to change with the charging and discharging process. During these processes, the battery's energy storage data will change in real time and reflect the battery's performance status and health. However, traditional battery management systems can often only simply record the battery's charging and discharging data, and lack the ability to conduct in-depth analysis and mining of these data. This leads to inaccurate assessments of the battery's energy storage state and inability to promptly detect potential battery problems, thus affecting the overall performance and safety of new energy electric vehicles. In summary, the present application proposes a method for analyzing energy storage data for new energy electric vehicles, which aims to determine the battery's energy storage changes by deeply analyzing the electric energy storage data of new energy electric vehicles in a certain cycle, and to evaluate the working status of the energy storage system accordingly, thereby providing more scientific and effective support for battery management of new energy electric vehicles.

[0039] In one embodiment, Figure 1 As shown, a method for analyzing energy storage data for new energy electric vehicles is provided, and the method is applied to the control system of a new energy electric vehicle as an example for explanation, including the following steps:

[0040] S110, obtaining and collecting electric energy storage data of the new energy electric vehicle in the current cycle.

[0041] Among them, the cycle includes one charging process and at least one discharging process. The cycle is defined based on the user's actual charging and discharging behavior, and the user's charging behavior is used as the dividing point between cycles. The initial charging power and the final charging power of each charging process are the actual values ​​when the user charges, and are not limited to the recommended charging power. The discharging process refers to the user's power consumption during driving. In some cases, the cycle may also include a stop operation process, during which there may be self-discharge. The discharge level is smaller than that during driving, and can be analyzed separately to find abnormalities.

[0042] Electric energy storage data may include the power, voltage, current and temperature data of the energy storage system, as well as the operation data of new energy electric vehicles. It may also include the power during the charging and discharging process, charging time, and endurance time.

[0043] In a specific implementation, the control system can obtain the electric energy storage data in a time sequence through the battery management system, the vehicle computer system, etc. The control system can determine a cycle from the start of one charging behavior to the end before the next charging behavior.

[0044] S120, analyzing the electric energy storage data to determine the energy storage changes of the new energy battery energy storage system during the cycle.

[0045] The energy storage change can be the energy change range in each process during the charging and discharging process. It can also refer to the rate of change of power during the charging and discharging process. For example, during the charging process, it can be the rate of increase of battery power, and during the discharging process, it can be the rate of power consumption.

[0046] In a specific implementation, the control system can input the electric energy storage data into a pre-trained energy storage change prediction model for processing, and obtain the energy storage change according to the processing result. The energy storage change prediction model can be a prediction model based on time series, and this application does not specifically limit the selection of the model. The control system can also determine the changes in the monitoring values ​​during the charging and discharging process, such as the power value and the power change rate, in a metered manner according to the power, voltage, current and temperature data.

[0047] S130, determining the working state of the energy storage system of the new energy electric vehicle according to the change of energy storage.

[0048] The working state of the energy storage system can be a qualitative state, such as a normal state, a monitoring state or an abnormal state; or a quantitative state, such as scoring the state. The working state of the energy storage system can also be evaluated qualitatively or quantitatively for each process of the cycle.

[0049] In a specific implementation, the control system can determine the working status of the energy storage system and whether the user's use of the energy storage system needs to be improved by comparing the status of the energy storage system with historical cycles or with reference cycles.

[0050] In the above energy storage data analysis method for new energy electric vehicles, the energy storage data of the new energy electric vehicle in the current cycle is acquired and analyzed to determine the energy storage changes of the energy storage system of the new energy battery in the cycle, and the working state of the energy storage system of the new energy electric vehicle is determined according to the energy storage changes, wherein the cycle includes a charging process and at least one discharging process. The user's charging and discharging behavior is used as a cycle to analyze the energy storage changes of the user in the cycle, thereby improving the personalization of the energy storage data analysis and thus improving the accuracy of the energy storage analysis.

[0051] In one embodiment, the electric energy storage data includes the power, voltage, current and temperature data of the energy storage system, and the operation data of the new energy electric vehicle. The step of determining to obtain and collect the electric energy storage data of the new energy electric vehicle in the current cycle in S110 includes:

[0052] The power, voltage, current and temperature data of the energy storage system are obtained in real time through the on-board battery management system of the new energy electric vehicle; and the operation data of the new energy electric vehicle is obtained in real time through the vehicle computer system of the new energy electric vehicle.

[0053] In this embodiment, in one cycle, the battery-related data and the operation data of the electric vehicle are collected in real time, and analysis and energy storage system monitoring can be performed in real time to provide timely abnormal warnings.

[0054] In one embodiment, the step of analyzing the electric energy storage data to determine the energy storage change of the energy storage system of the new energy battery in the cycle in step S120 includes:

[0055] The electric energy storage data is input into the pre-trained energy storage change prediction model for processing, and the energy storage change situation is obtained according to the processing result;

[0056] Among them, the energy storage change prediction model is a prediction model trained based on the electric energy storage data in multiple cycles as a training data set. The energy storage change prediction model is a prediction based on the cycle as the basic unit, and its output result is the energy storage change in the future cycle. The energy storage change prediction model can be a prediction model based on time series, and this application does not specifically limit the selection of the model. The energy storage change situation can include the start and end time of the next cycle, as well as the changes in the energy storage system in each process of the cycle.

[0057] The solution of the above embodiment, by predicting energy storage changes through a pre-trained energy storage change prediction model, can deeply explore the relationship between various influencing factors. The output of the model can be used as a reference value to compare with other methods to calculate whether the energy storage change situation is obviously abnormal.

[0058] In one embodiment, the step of determining in S120 to analyze the electric energy storage data and determine the energy storage change of the energy storage system of the new energy battery in the cycle includes:

[0059] The power, voltage, current and temperature data during the charging process are analyzed to obtain the battery power increase rate during the charging process; the power, voltage, current and temperature data during the discharging process, as well as the operation data of the new energy electric vehicle are analyzed to obtain the battery power consumption rate during the discharging process; based on the battery power increase rate and the battery consumption rate, the energy storage change of the energy storage system of the new energy battery in the current cycle is obtained.

[0060] In this embodiment, the rate of increase of the battery power is a comprehensive influence of multiple parameters such as power, voltage, current and temperature, and there is also mutual influence between the above parameters. The control system obtains the rate of increase of the battery power during the charging process based on the relationship between the pre-set parameters. It is also possible to calculate based on the power change rate and the charging time to obtain the change in power per unit time during the charging process as the rate of increase of the battery power during the charging process. It should be noted that when comparing, the data obtained by the same calculation method should be compared to avoid data anomalies.

[0061] Similarly, the battery power consumption rate is a comprehensive influence of multiple parameters such as power and temperature, and is closely related to the operation data of the electric vehicle. The control system can obtain the battery power consumption rate during the discharge process based on the relationship between the pre-set parameters. The battery power consumption rate can also be obtained based on the changes in the power data of the energy storage system at different speeds, loads and running distances of new energy electric vehicles.

[0062] In some embodiments, the control system can collect the rate of change of the electric quantity during the charging process and the discharging process in real time, and when it obviously exceeds a preset change threshold, a timely warning can be issued.

[0063] The solution of the above-mentioned embodiment collects different parameters to determine the rate of change of electric quantity through different situations of the charging process and the discharging process, thereby improving the accuracy of obtaining the change situation of energy storage.

[0064] In one embodiment, one cycle includes one charging process, at least one discharging process and at least one stopping process, and the methods of the above embodiments further include:

[0065] The power and temperature data during the stop operation process are analyzed to obtain the self-discharge rate of the battery during the stop operation process; the self-discharge rate of the battery during the stop operation process in multiple cycles is obtained, and the data is fitted according to the time series to determine the energy storage change of the new energy electric vehicle in the stop operation state.

[0066] In this embodiment, considering that the stopping process of the new energy electric vehicle takes a long time, and the self-discharge amount is smaller than that in the running stage, it is difficult to monitor abnormal conditions. Therefore, the self-discharge of the new energy electric vehicle during the stopping process is monitored as an independent process. The control system can obtain the self-discharge rate of the battery based on the power and temperature data during the stopping process. Therefore, the energy storage change can include the battery power increase rate, battery consumption rate and self-discharge rate.

[0067] The control system can perform data fitting of the self-discharge rate of the battery during the stop operation process in multiple historical cycles according to the time series, and determine the energy storage changes of the new energy electric vehicle when it is stopped, so that users can timely understand the working status of the energy storage system when it is stopped.

[0068] In one embodiment, the step of determining the working state of the energy storage system of the new energy electric vehicle according to the energy storage change in S130 includes:

[0069] Obtain energy storage changes in multiple historical cycles and generate an energy storage change prediction curve; obtain the predicted energy storage change in the current cycle based on the energy storage change prediction curve; compare the energy storage change with the predicted energy storage change, and determine the working state of the energy storage system of the new energy electric vehicle based on the comparison result.

[0070] In this embodiment, the control system can use the cycle as the basic unit, obtain the energy storage changes in multiple historical cycles, and generate a prediction curve. The predicted energy storage changes output by the prediction curve can be used as a reference value for comparison with the energy storage changes monitored in the current cycle. For example, the control system can pre-set the deviation threshold of each process. If the deviation is within the threshold range, the working state of the energy storage system in the charging process or discharging process corresponding to the cycle is normal.

[0071] The solution of the above embodiment improves the accuracy of judging the working state of the energy storage system by determining the prediction curve and generating the predicted energy storage change as a reference value.

[0072] In one embodiment, the method of each of the above embodiments further includes:

[0073] Acquire charging data of the charging process of the current cycle; compare the charging data with reference charging data, and generate charging suggestions based on the comparison results; the reference charging data includes but is not limited to charging time, charging power, initial charging power and final charging power.

[0074] In this embodiment, a cycle is determined based on the user's charging and discharging habits, and the user's frequent charging and discharging can be detected. Frequent charging and discharging will cause the battery to be overcharged, increase the number of battery charging times, and thus damage the battery life. It is necessary to guide the charging and discharging behavior.

[0075] Specifically, the control system can compare the charging duration, charging power, initial charging capacity and final charging capacity of the current cycle with reference charging data to generate charging suggestions and send them to the user to prompt the user to correct the charging and discharging usage methods.

[0076] In one embodiment, the methods of the above embodiments further include: comparing the working state of the energy storage system with the working state of a reference energy storage system, and generating energy storage system usage optimization suggestions according to the comparison results.

[0077] In this embodiment, the reference energy storage system working state can be the energy storage system working state of a vehicle of the same model as the new energy electric vehicle, or it can be laboratory test data. The use optimization suggestions can include charging process optimization suggestions, discharging process optimization suggestions, and stopping operation process optimization suggestions. For example, the control system can remind the user to shorten the charging time during the charging process or drive at a suitable speed during the discharging process based on the comparison.

[0078] In some embodiments, the control system can obtain the energy storage changes of a preset number of charge and discharge cycles and generate an energy storage system work report; in response to a user query request, the energy storage system work report is sent to the display module so that the user can visually understand the usage habits of the energy storage system, promptly remind the user to correct the usage method, and improve user interaction efficiency.

[0079] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the present application.

[0080] In one embodiment, a system for analyzing energy storage data for a new energy electric vehicle is provided, the system comprising:

[0081] The electric energy storage data acquisition module is used to acquire and collect the electric energy storage data of the new energy electric vehicle in the current cycle; the cycle includes a charging process and at least one discharging process;

[0082] An electric energy storage data analysis module, used to analyze the electric energy storage data and determine the energy storage changes of the energy storage system of the new energy battery in the cycle;

[0083] The working status confirmation module is used to determine the working status of the energy storage system of the new energy electric vehicle according to the energy storage change.

[0084] In one embodiment, the system further comprises a display module for displaying the working status of the energy storage system of the new energy electric vehicle.

[0085] For the specific definition of the energy storage data analysis system for new energy electric vehicles, please refer to the definition of the energy storage data analysis method for new energy electric vehicles mentioned above, which will not be repeated here. Each module in the above-mentioned energy storage data analysis device for new energy electric vehicles can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0086] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods.

[0087] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for analyzing energy storage data for new energy electric vehicles, characterized in that: The method comprises: Acquire and collect the electric energy storage data of the new energy electric vehicle in the current cycle; the cycle includes a charging process and at least one discharging process; Analyze the electric energy storage data to determine the energy storage changes of the energy storage system of the new energy battery during the cycle; According to the energy storage change, the working state of the energy storage system of the new energy electric vehicle is determined.

2. The method according to claim 1, characterized in that The electric energy storage data includes the power, voltage, current and temperature data of the energy storage system, and the operation data of the new energy electric vehicle; The acquisition and collection of electric energy storage data of the new energy electric vehicle in the current cycle includes: The on-board battery management system of new energy electric vehicles can be used to obtain the power, voltage, current and temperature data of the energy storage system in real time; And, the operation data of the new energy electric vehicle is obtained in real time through the vehicle computer system of the new energy electric vehicle.

3. The method according to claim 2, characterized in that The analyzing the electric energy storage data to determine the energy storage change of the energy storage system of the new energy battery in the cycle includes: Inputting the electric energy storage data into a pre-trained energy storage change prediction model for processing, and obtaining the energy storage change situation according to the processing result; The energy storage change prediction model is a prediction model trained using electric energy storage data in multiple cycles as a training data set.

4. The method according to claim 2, characterized in that: The analyzing the electric energy storage data to determine the energy storage change of the energy storage system of the new energy battery in the cycle includes: Analyzing the power, voltage, current and temperature data during the charging process to obtain the battery power increase rate during the charging process; Analyze the power consumption during the discharge process and the operation data of the new energy electric vehicle to obtain the battery power consumption rate during the discharge process; According to the battery power increase rate and the battery consumption rate, the energy storage change of the energy storage system of the new energy battery in the current cycle is obtained.

5. The method according to claim 4, characterized in that The analyzing the amount of electricity during the discharge process and the operation data of the new energy electric vehicle to obtain the battery power consumption rate during the discharge process includes: The power data of the energy storage system of the new energy electric vehicle at different speeds, loads and running distances is obtained during the discharge process to obtain the battery power consumption rate.

6. The method according to claim 4, characterized in that The cycle includes a charging process, at least one discharging process and at least one stopping process, and the method further includes: Analyze the power and temperature data during the shutdown process to obtain the self-discharge rate of the battery during the shutdown process; The self-discharge rate of the battery during the stop operation process in multiple cycles is obtained, and data fitting is performed according to the time series to determine the energy storage change of the new energy electric vehicle in the stop operation state.

7. The method according to any one of claims 1 to 5, characterized in that: Before determining the working state of the energy storage system of the new energy electric vehicle according to the energy storage change, the method further includes: Obtaining energy storage changes in multiple historical cycles and generating an energy storage change prediction curve; obtaining the predicted energy storage change in the current cycle based on the energy storage change prediction curve; Determining the working state of the energy storage system of the new energy electric vehicle according to the energy storage change includes: The energy storage change condition is compared with the predicted energy storage change condition, and the working state of the energy storage system of the new energy electric vehicle is determined according to the comparison result.

8. The method according to any one of claims 1 to 5, characterized in that: Also includes: Acquiring charging data of the charging process of the current cycle; comparing the charging data with reference charging data, and generating charging suggestions according to the comparison result; The reference charging data includes but is not limited to charging time, charging power, initial charging power and final charging power.

9. The method according to any one of claims 1 to 5, characterized in that: Also includes: The working state of the energy storage system is compared with the working state of a reference energy storage system, and an energy storage system usage optimization suggestion is generated according to the comparison result.

10. An energy storage data analysis system for new energy electric vehicles, characterized in that: The system comprises: The electric energy storage data acquisition module is used to acquire and collect the electric energy storage data of the new energy electric vehicle in the current cycle; the cycle includes a charging process and at least one discharging process; An electric energy storage data analysis module, used to analyze the electric energy storage data and determine the energy storage changes of the energy storage system of the new energy battery in the cycle; The working status confirmation module is used to determine the working status of the energy storage system of the new energy electric vehicle according to the energy storage change.

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