Battery over-discharge monitoring system and method based on mobile energy storage charging vehicle

Abstract

The invention relates to the technical field of battery over-discharge monitoring, in particular to a battery over-discharge monitoring system and method based on a mobile energy storage charging vehicle, and the system comprises a battery over-discharge monitoring center, a charging and discharging database, a charging and discharging evaluation and analysis unit, a recording evaluation unit, a management expression unit, a defect offset unit, an over-discharge depth analysis unit, and an early warning management unit. According to the invention, analysis is carried out from two points of the actual discharging process and the historical charging process of the target battery so as to judge whether the actual discharging process of the target battery has an over-discharging behavior and whether the historical charging process has a potential over-discharging risk, so that data support is provided for subsequent target battery management; the over-discharge depth of the target battery is comprehensively evaluated in a multi-angle analysis and multi-angle fusion mode, an over-discharge depth evaluation coefficient is judged and processed, and reasonable-depth over-discharge management is carried out on the target battery according to different feedback information conditions, so that the working stability and safety of the target battery are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery over-discharge monitoring, and particularly to a battery over-discharge monitoring system and method based on a mobile energy storage charging vehicle. Background Art

[0002] Due to energy and environmental considerations, electric vehicles have achieved rapid development under the joint promotion of governments and automobile manufacturers in various countries. Pure electric vehicles have become one of the important development directions of electric vehicles because they can truly achieve "zero emissions". The battery management system BMS manages the battery by measuring parameters such as voltage, current, and temperature of the battery system in real time so that it can maintain a better state and work stably;

[0003] However, in the prior art, it is impossible to monitor the potential risk of over-discharge from the battery charging direction of the mobile energy storage charging vehicle, which is not conducive to the reasonable and in-depth management of the battery of the mobile energy storage charging vehicle, resulting in a decrease in the battery management efficiency and working stability of the mobile energy storage charging vehicle. Moreover, it is impossible to evaluate the over-discharge depth of the battery of the mobile energy storage charging vehicle from a multi-angle manner, which is not conducive to the rational management based on the over-discharge depth of the battery, resulting in an increase in the working safety risk of the battery;

[0004] In view of the above technical defects, a solution is proposed now. Summary of the Invention

[0005] The purpose of the present invention is to provide a battery over-discharge monitoring system and method based on a mobile energy storage charging vehicle to solve the above-mentioned technical defects. The present invention analyzes from two points: the actual discharge process and the historical charging process of the target battery to determine whether there is an over-discharge behavior in the actual discharge process of the target battery and whether there is a potential over-discharge risk in the historical charging process. Furthermore, based on the information feedback, it can be intuitively understood whether the target battery is over-discharged and there is a potential over-discharge risk, so as to provide data support for the subsequent management of the target battery. By means of multi-angle analysis and multi-angle fusion, the over-discharge depth of the target battery is comprehensively evaluated, and the over-discharge depth evaluation coefficient is discriminated and processed. According to different feedback information, the target battery is managed with reasonable depth of over-discharge, so as to improve the working stability and safety of the target battery and reduce the impact of over-discharge on the target battery at the same time.

[0006] The purpose of the present invention can be achieved by the following technical solutions: A battery over-discharge monitoring system based on a mobile energy storage charging vehicle includes a battery over-discharge monitoring center, a charge and discharge database, a charge and discharge evaluation analysis unit, a record evaluation unit, a management performance unit, a defect offset unit, an over-discharge depth analysis unit, and an early warning management unit;

[0007] The battery over-discharge monitoring center is used to retrieve the discharge working condition information of the target battery from the charge and discharge database and send the discharge working condition information to the charge and discharge evaluation analysis unit;

[0008] After receiving the discharge condition information, the charge and discharge evaluation and analysis unit immediately conducts charge and discharge safety monitoring feedback analysis on the discharge condition information, discriminates and processes the obtained over-discharge evaluation difference to obtain a normal signal or an over-discharge signal. At the same time, it discriminates and processes the obtained over-discharge evaluation value to obtain a stable signal or a potential signal;

[0009] When a normal signal or an over-discharge signal is generated, the evaluation unit records the historical discharge information of the target battery used for acquisition, and conducts historical record over-discharge damage evaluation and analysis on the historical discharge information to obtain the battery over-discharge coefficient;

[0010] The management performance unit is used to collect the historical management information of the target battery. At the same time, it conducts over-discharge induction level evaluation and division analysis on the historical management information, discriminates and processes the obtained over-discharge potential evaluation value to obtain the over-discharge assistance coefficient G;

[0011] The defect offset unit is used to collect the own data of the target battery. At the same time, it conducts its own comprehensive evaluation and matching analysis on the own data to obtain the offset evaluation level;

[0012] The over-discharge depth analysis unit is used to retrieve the battery over-discharge coefficient, over-discharge assistance coefficient G, and offset evaluation level of the target battery, and conduct over-discharge depth comprehensive evaluation and analysis to obtain a normal management signal, an intermediate management signal, or a high-level management signal.

[0013] Preferably, the charge and discharge safety monitoring feedback analysis process is as follows:

[0014] Set the battery of the mobile energy storage charging vehicle as the target battery, collect the discharge period of the target battery, and set it as the time threshold. Obtain the discharge condition information of the target battery within the time threshold. The discharge condition information represents the discharge voltage and the discharge cut-off voltage;

[0015] Obtain the value obtained by subtracting the discharge cut-off voltage from the discharge voltage, and set the value obtained by subtracting the discharge cut-off voltage from the discharge voltage as the over-discharge evaluation difference, and conduct discriminant processing on the over-discharge evaluation difference to obtain a normal signal or an over-discharge signal.

[0016] Preferably, after a normal signal is generated, obtain the historical n charging periods of the target battery, where n is a natural number greater than zero. Obtain the charging power and actual charging duration of the target battery within each charging period. Obtain the preset charging duration corresponding to the charging power of the target battery. Set the charging period corresponding to the value obtained by subtracting the preset charging duration from the actual charging duration being greater than the preset threshold as the side feedback value, and set the ratio of the side feedback value to n as the over-discharge evaluation value, and conduct discriminant processing on the over-discharge evaluation value to obtain a stable signal or a potential signal.

[0017] Preferably, the process of evaluating and analyzing the over-discharge damage of the historical record is as follows:

[0018] Obtain the historical discharge information of the target battery within the time threshold. The historical discharge information includes the total number of over-discharges, the total duration of over-discharge, and the total amount of over-discharge. Obtain the product value obtained by multiplying the corresponding values of the total number of discharges, the total duration of over-discharge, and the total amount of over-discharge, and set it as the battery over-discharge coefficient.

[0019] Preferably, the process of evaluating and classifying the over-discharge induction level is as follows:

[0020] Obtain the historical management information of the target battery within the time threshold. The historical management information includes the operation evaluation coefficient and the over-discharge defect index. Compare and analyze the operation evaluation coefficient and the over-discharge defect index with the preset operation evaluation coefficient threshold and the preset over-discharge defect index threshold. Set the number of the operation evaluation coefficient and the over-discharge defect index that are greater than or equal to the preset operation evaluation coefficient threshold and the preset over-discharge defect index threshold as the over-discharge potential evaluation value, and perform discriminant processing on the over-discharge potential evaluation value to obtain the conventional impact, medium impact, and high impact. Set the conventional impact, medium impact, and high impact as the over-discharge assistance coefficient G, where G = 1, 2, 3.

[0021] Preferably, the operation evaluation coefficient represents the product value obtained by multiplying the normalized values of the historical unused total duration and the delayed charging duration of the target battery. The historical unused total duration represents the total duration corresponding to the non-discharge operation or non-charging operation of the target battery. The delayed charging duration represents the total duration between the remaining power of the target battery and the charging time of the target battery at the preset remaining power threshold moment. The over-discharge defect index represents the product value obtained by multiplying the normalized values of the total volume of gas generated during the historical over-discharge total duration of the target battery and the average value of the battery operating temperature.

[0022] Preferably, the process of matching and analyzing the self-comprehensive evaluation is as follows:

[0023] Obtain the self-data of the target battery within the time threshold. The self-data includes the internal resistance change curve and the capacity evaluation value. Obtain the difference between the current internal resistance value and the initial internal resistance value from the internal resistance change curve, and set it as the internal resistance growth value. Set the ratio between the internal resistance growth value and the corresponding value of the input duration as the internal resistance floating coefficient. The input duration represents the duration between the moment when the target battery is put into use and the current moment.

[0024] Obtain the actual maximum energy storage capacity value corresponding to the target battery at the current moment, set the difference between the actual maximum energy storage capacity value and the initial actual maximum energy storage capacity as the capacity degradation value, set the ratio of the capacity degradation value to the input duration as the capacity degradation coefficient, and set the product value obtained by multiplying the capacity degradation coefficient by the corresponding value of the environmental promotion value as the capacity evaluation value. The environmental promotion value represents the overlapping duration between the duration when the environmental temperature exceeds the preset temperature and the duration when the environmental humidity exceeds the preset humidity within the input duration;

[0025] Compare and analyze the internal resistance floating coefficient and the capacity evaluation value with the preset internal resistance floating coefficient and the capacity evaluation value threshold, set the number of the internal resistance floating coefficient and the capacity evaluation value that are greater than or equal to the preset internal resistance floating coefficient and the capacity evaluation value threshold as the self-offset coefficient, obtain the preset offset value corresponding to the self-offset coefficient located in the preset self-offset coefficient interval, and set it as the offset evaluation level.

[0026] Preferably, the over-discharge depth comprehensive evaluation analysis process is as follows:

[0027] Set the value obtained by multiplying the battery over-discharge coefficient, the over-discharge assistance coefficient G, and the value corresponding to the offset evaluation level as the over-discharge depth evaluation coefficient, and perform discrimination processing on the over-discharge depth evaluation coefficient to obtain a normal management signal, an intermediate management signal, or a high-level management signal.

[0028] The beneficial effects of the present invention are as follows:

[0029] (1) The present invention analyzes from two points of the actual discharge process and the historical charging process of the target battery to determine whether there is an over-discharge behavior in the actual discharge process of the target battery and whether there is a potential over-discharge risk in the historical charging process. Furthermore, based on the information feedback, it can directly understand whether the target battery is over-discharged and has a potential over-discharge risk, so as to provide data support for the subsequent management of the target battery

[0030] (2) The present invention analyzes from three points of historical records, historical management performance, and its own changes through the way of information feedback, that is, comprehensively evaluates the over-discharge depth of the target battery through multi-angle analysis and multi-angle fusion. At the same time, through the fusion evaluation, the over-discharge depth evaluation coefficient is obtained, and discrimination processing is performed on the over-discharge depth evaluation coefficient to obtain different feedback information, and reasonable-depth over-discharge management is carried out on the target battery according to different feedback information situations, so as to improve the working stability and safety of the target battery, and at the same time reduce the impact of over-discharge on the target battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The following further describes the present invention with reference to the drawings;

[0032] Figure 1 is the system flow block diagram of the present invention;

[0033] Figure 2 This is the reference analysis diagram of the method of the present invention. Specific implementation mode

[0034] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0035] Embodiment 1:

[0036] Please refer to Figures 1 to 2 As shown, the present invention is a battery over-discharge monitoring system based on a mobile energy storage charging vehicle, including a battery over-discharge monitoring center, a charge-discharge database, a charge-discharge evaluation and analysis unit, a recording and evaluation unit, a management performance unit, a defect deviation unit, an over-discharge depth analysis unit, and an early warning management unit. The charge-discharge database is in one-way communication connection with the battery over-discharge monitoring center, the battery over-discharge monitoring center is in one-way communication connection with the charge-discharge evaluation and analysis unit, the charge-discharge evaluation and analysis unit is in one-way communication connection with the recording and evaluation unit, the management performance unit, the defect deviation unit, and the early warning management unit, the recording and evaluation unit, the management performance unit, and the defect deviation unit are all in one-way communication connection with the over-discharge depth analysis unit, and the over-discharge depth analysis unit is in one-way communication connection with the early warning management unit;

[0037] The battery over-discharge monitoring center is used to retrieve the discharge working condition information of the target battery from the charge-discharge database and send the discharge working condition information to the charge-discharge evaluation and analysis unit;

[0038] After receiving the discharge working condition information, the charge-discharge evaluation and analysis unit immediately conducts charge-discharge safety monitoring feedback analysis on the discharge working condition information. On the one hand, it helps to intuitively understand whether there is an over-discharge behavior of the target battery, and on the other hand, it helps to judge whether there is a potential over-discharge hazard for the target battery. The specific charge-discharge safety monitoring feedback analysis process is as follows:

[0039] Set the battery of the mobile energy storage charging vehicle as the target battery, collect the discharge period of the target battery, and set it as the time threshold, and obtain the discharge working condition information of the target battery within the time threshold. The discharge working condition information represents the discharge voltage and the discharge cut-off voltage;

[0040] Obtain the value obtained by subtracting the discharge cut-off voltage from the discharge voltage, and set the value obtained by subtracting the discharge cut-off voltage from the discharge voltage as the over-discharge evaluation difference, and conduct discriminant processing on the over-discharge evaluation difference:

[0041] If the over-discharge evaluation difference is greater than or equal to the preset over-discharge evaluation difference threshold, a normal signal is generated;

[0042] If the over-discharge evaluation difference is less than the preset over-discharge evaluation difference threshold, an over-discharge signal is generated;

[0043] After a normal signal is generated, the historical n charging periods of the target battery are obtained, where n is a natural number greater than zero. The charging power and actual charging duration of the target battery in each charging period are obtained. The preset charging duration corresponding to the charging power of the target battery is obtained. The charging period in which the value obtained by subtracting the preset charging duration from the actual charging duration is greater than the preset threshold is set as the side feedback value. The ratio of the side feedback value to n is set as the over-discharge evaluation value, and the over-discharge evaluation value is subjected to discrimination processing:

[0044] If the over-discharge evaluation value is less than the preset over-discharge evaluation value threshold, a stable signal is generated;

[0045] If the over-discharge evaluation value is greater than or equal to the preset over-discharge evaluation value threshold, a potential signal is generated. The stable signal or potential signal is sent to the early warning management unit. After receiving the stable signal or potential signal, the early warning management unit immediately performs the preset early warning operation corresponding to the stable signal or potential signal. On the one hand, it helps to intuitively understand whether there is an over-discharge behavior of the target battery. On the other hand, it helps to judge whether there is a potential over-discharge hazard for the target battery;

[0046] In the embodiment of the present invention, the discharge cut-off voltage represents the lowest working voltage value at which the discharge voltage drops to a value where the target battery is not suitable for further discharging.

[0047] Embodiment Two:

[0048] When a normal signal or an over-discharge signal is generated, analysis is performed from three aspects: historical records, historical management performance, and its own changes, so as to perform targeted over-discharge management on the target battery through information fusion to reduce the working risk of the target battery. That is, the recording and evaluation unit is used to collect the historical discharge information of the target battery and perform an over-discharge damage evaluation analysis on the historical discharge information. The specific process of the over-discharge damage evaluation analysis of the historical record is as follows:

[0049] The historical discharge information of the target battery within the time threshold is obtained. The historical discharge information includes the total number of over-discharges, the total duration of over-discharges, and the total amount of over-discharges;

[0050] The product value obtained by multiplying the corresponding values of the total number of discharges, the total duration of over-discharges, and the total amount of over-discharges is obtained, and the product value obtained by multiplying the corresponding values of the total number of discharges, the total duration of over-discharges, and the total amount of over-discharges is set as the battery over-discharge coefficient. It should be noted that from the perspective of historical over-discharge analysis, the depth of over-discharge damage caused by over-discharge to the target battery is understood to provide data support for subsequent over-discharge monitoring;

[0051] In an embodiment of the present invention, when it is obtained that the discharge voltage of the target battery is lower than the preset discharge voltage during the discharge process, the corresponding number of discharges is set as the over-discharge times;

[0052] The total over-discharge duration represents the sum of the continuous discharge durations during which the discharge voltage of the target battery is lower than the preset discharge voltage during the discharge process;

[0053] The management performance unit is used to collect the historical management information of the target battery, and at the same time, conduct an over-discharge induction level evaluation and division analysis on the historical management information. The specific over-discharge induction level evaluation and division analysis process is as follows:

[0054] Obtain the historical management information of the target battery within the time threshold. The historical management information includes the operation evaluation coefficient and the over-discharge defect index. Compare and analyze the operation evaluation coefficient and the over-discharge defect index with the preset operation evaluation coefficient threshold and the preset over-discharge defect index threshold. Set the number of the operation evaluation coefficient and the over-discharge defect index that are greater than or equal to the preset operation evaluation coefficient threshold and the preset over-discharge defect index threshold as the over-discharge potential evaluation value, and conduct a discrimination process on the over-discharge potential evaluation value:

[0055] If the over-discharge potential evaluation value = 0, it is determined as a normal influence;

[0056] If the over-discharge potential evaluation value = 1, it is determined as an intermediate influence;

[0057] If the over-discharge potential evaluation value = 2, it is determined as a high-level influence. Among them, the corresponding over-discharge potential interferences of the normal influence, the intermediate influence, and the high-level influence increase in turn. Set the normal influence, the intermediate influence, and the high-level influence as the over-discharge assistance coefficient G, G = 1, 2, 3, that is, G = 1, the over-discharge assistance coefficient represents the normal influence, G = 2, the over-discharge assistance coefficient represents the intermediate influence, G = 3, the over-discharge assistance coefficient represents the high-level influence;

[0058] In an embodiment of the present invention, the operation evaluation coefficient represents the product value obtained by multiplying the historical unused total duration of the target battery by the delayed charging duration after data normalization processing. It should be noted that the larger the value of the operation evaluation coefficient, the greater the risk of abnormal self-performance of the target battery and the greater the over-discharge risk;

[0059] The historical unused total duration represents the total duration corresponding to the target battery without performing discharge or charge operations, and the delayed charging duration represents the total duration between the remaining power of the target battery and the charging time of the target battery at the moment of the preset remaining power threshold;

[0060] In an embodiment of the present invention, the over-discharge defect index is the product value obtained by multiplying the total volume of gas generated during the total historical over-discharge duration of the target battery by the value obtained by normalizing the average value of the battery operating temperature. It should be noted that the over-discharge defect index is a comprehensive evaluation result reflecting the performance of the target battery's historical over-discharge. The larger the value of the over-discharge defect index, the greater the over-discharge risk of the target battery.

[0061] Embodiment Three:

[0062] The defect offset unit is used to collect the self-data of the target battery and perform a self-comprehensive evaluation and matching analysis on the self-data to understand the current self-defect situation of the target battery. The specific self-comprehensive evaluation and matching analysis process is as follows:

[0063] Obtain the self-data of the target battery within the time threshold. The self-data includes the internal resistance change curve and the capacity evaluation value;

[0064] In an embodiment of the present invention, the difference between the current internal resistance value and the initial internal resistance value is obtained from the internal resistance change curve, and it is set as the internal resistance growth value. The ratio between the internal resistance growth value and the corresponding value of the input duration is set as the internal resistance floating coefficient. The input duration represents the duration between the moment when the target battery is put into use and the current moment;

[0065] In an embodiment of the present invention, the actual maximum energy storage capacity value corresponding to the current moment of the target battery is obtained. The difference between the actual maximum energy storage capacity value and the initial actual maximum energy storage capacity is set as the capacity degradation value. The ratio between the capacity degradation value and the input duration is set as the capacity degradation coefficient. The product value obtained by multiplying the capacity degradation coefficient by the corresponding value of the environmental promotion value is set as the capacity evaluation value. The environmental promotion value represents the overlapping duration between the duration when the environmental temperature exceeds the preset temperature and the duration when the environmental humidity exceeds the preset humidity within the input duration;

[0066] Compare and analyze the internal resistance floating coefficient and the capacity evaluation value with the preset internal resistance floating coefficient and the capacity evaluation value threshold. Set the number of the internal resistance floating coefficient and the capacity evaluation value that are greater than or equal to the preset internal resistance floating coefficient and the capacity evaluation value threshold as the self-offset coefficient, and compare and analyze the self-offset coefficient with the preset self-offset coefficient interval. Obtain the preset offset value corresponding to the self-offset coefficient located in the preset self-offset coefficient interval, and set the preset offset factor corresponding to the self-offset coefficient located in the preset self-offset coefficient interval as the offset evaluation level;

[0067] It should be noted that the preset offset value of the first preset self-offset coefficient interval is less than the preset offset value of the second preset self-offset coefficient interval, and the preset offset value of the second preset self-offset coefficient interval is less than the preset offset value of the third preset self-offset coefficient interval, and so on;

[0068] The over-discharge depth analysis unit is used to retrieve the battery over-discharge coefficient, over-discharge assistance coefficient G, and offset evaluation level of the target battery, and conduct a comprehensive evaluation and analysis of the over-discharge depth. The specific process of the comprehensive evaluation and analysis of the over-discharge depth is as follows:

[0069] Multiply the values corresponding to the battery over-discharge coefficient, over-discharge assistance coefficient G, and offset evaluation level to obtain the over-discharge depth evaluation coefficient, and conduct discrimination processing on the over-discharge depth evaluation coefficient:

[0070] If the over-discharge depth evaluation coefficient is less than the minimum value in the preset over-discharge depth evaluation coefficient range, a normal management signal is generated;

[0071] If the over-discharge depth evaluation coefficient belongs to the preset over-discharge depth evaluation coefficient range, an intermediate management signal is generated;

[0072] If the over-discharge depth evaluation coefficient is greater than the maximum value in the preset over-discharge depth evaluation coefficient range, a high-level management signal is generated. Among them, the over-discharge management degrees corresponding to the normal management signal, intermediate management signal, and high-level management signal increase in sequence. Send the normal management signal or intermediate management signal or high-level management signal to the early warning management unit. After receiving the normal management signal or intermediate management signal or high-level management signal, the early warning management unit immediately performs the preset early warning operations corresponding to the normal management signal or intermediate management signal or high-level management signal, so as to conduct reasonable-depth over-discharge management on the target battery according to the information feedback situation, so as to improve the working stability and safety of the target battery, and at the same time reduce the impact of over-discharge on the target battery.

[0073] Embodiment 4:

[0074] A battery over-discharge monitoring method based on a mobile energy storage charging vehicle includes the following steps:

[0075] Step 1: Retrieve the discharge working condition information of the target battery, conduct charge and discharge safety monitoring feedback analysis on the discharge working condition information, conduct discrimination processing on the obtained over-discharge evaluation difference. If a normal signal is obtained, go to Step 2; if an over-discharge signal is obtained, feedback and output;

[0076] Step 2: Analyze the potential over-discharge risk of the target battery by means of information feedback, judge whether the target battery has a potential over-discharge risk, and feedback and output the obtained stable signal or potential signal;

[0077] Step 3: Based on the historical record over-discharge damage evaluation analysis of the historical discharge information under information feedback, obtain the battery over-discharge coefficient, and substitute the battery over-discharge coefficient into Step 6;

[0078] Step 4: Analyze and classify the over-discharge induction level of historical management information in a progressive manner, discriminate and process the obtained over-discharge potential evaluation value, obtain the over-discharge assistance coefficient G, and substitute it into Step 6;

[0079] Step 5: Collect the own data of the target battery, and at the same time conduct an analysis of the comprehensive evaluation and matching of the own data to obtain the offset evaluation level, and substitute the offset evaluation level into Step 6;

[0080] Step 6: Based on the battery over-discharge coefficient, the over-discharge assistance coefficient G, and the offset evaluation level, conduct a fusion analysis to obtain the over-discharge depth evaluation coefficient, and conduct a discrimination process on the over-discharge depth evaluation coefficient to obtain a normal management signal, or an intermediate management signal, or a high-level management signal and output feedback;

[0081] In summary, the present invention analyzes from two points: the actual discharge process and the historical charging process of the target battery, to determine whether there is an over-discharge behavior in the actual discharge process of the target battery and whether there is a potential over-discharge risk in the historical charging process. Furthermore, based on the information feedback, it can intuitively understand whether the target battery is over-discharged and has a potential over-discharge risk, so as to provide data support for the subsequent management of the target battery;

[0082] And through the way of information feedback, it analyzes from three points: historical records, historical management performance, and its own changes, that is, comprehensively evaluates the over-discharge depth of the target battery through multi-angle analysis and multi-angle fusion. At the same time, through the fusion evaluation, the over-discharge depth evaluation coefficient is obtained, and a discrimination process is carried out on the over-discharge depth evaluation coefficient to obtain different feedback information, and reasonable-depth over-discharge management is carried out on the target battery according to different feedback information situations, so as to improve the working stability and safety of the target battery, and at the same time reduce the impact of over-discharge on the target battery.

[0083] The setting of the size of the threshold is for the convenience of comparison. Regarding the size of the threshold, it depends on the amount of sample data and the base quantity set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values;

[0084] The size of the coefficient is a specific value obtained by quantifying each parameter for the convenience of subsequent comparison. Regarding the size of the coefficient, it depends on the amount of sample data and the corresponding operation coefficient initially set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values.

[0085] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and all should be covered within the protection scope of the present invention.

Claims

1. The battery over-discharge monitoring system based on mobile energy storage charging vehicle is characterized by: It includes battery over-discharge monitoring center, charge and discharge database, charge and discharge evaluation and analysis unit, record evaluation unit, management performance unit, defect offset unit, over-discharge depth analysis unit and early warning management unit; The battery over-discharge monitoring center is used to retrieve the discharge condition information of the target battery from the charge and discharge database, and send the discharge condition information to the charge and discharge evaluation and analysis unit; After receiving the discharge condition information, the charge-discharge evaluation and analysis unit immediately performs charge-discharge safety monitoring feedback analysis on the discharge condition information, discriminates and processes the obtained over-discharge evaluation difference to obtain a normal signal or an over-discharge signal, and discriminates and processes the obtained over-discharge evaluation value to obtain a stable signal or a potential signal; When a normal signal or an over-discharge signal is generated, the recording and evaluation unit is used to collect the historical discharge information of the target battery, and perform historical record over-discharge damage evaluation and analysis on the historical discharge information to obtain the battery over-discharge coefficient; The management performance unit is used to collect the historical management information of the target battery, and at the same time, perform over-discharge induction level assessment and classification analysis on the historical management information, perform discrimination processing on the obtained over-discharge potential assessment value, and obtain the over-discharge assistance coefficient G; The defect offset unit is used to collect the target battery's own data, and at the same time conducts comprehensive evaluation matching analysis on its own data to obtain the offset evaluation level; The over-discharge depth analysis unit is used to retrieve the battery over-discharge coefficient, over-discharge boost coefficient G and offset evaluation level of the target battery, and conduct a comprehensive evaluation and analysis of the over-discharge depth to obtain a conventional management signal, an intermediate management signal or an advanced management signal.

2. The battery over-discharge monitoring system based on a mobile energy storage charging vehicle according to claim 1 is characterized in that: The charging and discharging safety monitoring feedback analysis process is as follows: The battery of the mobile energy storage charging vehicle is set as the target battery, the discharge period of the target battery is collected and set as the time threshold, and the discharge condition information of the target battery within the time threshold is obtained, and the discharge condition information represents the discharge voltage and the discharge cut-off voltage; A value obtained by subtracting the discharge cut-off voltage from the discharge voltage is obtained, and the value obtained by subtracting the discharge cut-off voltage from the discharge voltage is set as an over-discharge evaluation difference value, and the over-discharge evaluation difference value is discriminated and processed to obtain a normal signal or an over-discharge signal.

3. The battery over-discharge monitoring system based on a mobile energy storage charging vehicle according to claim 2 is characterized in that: After a normal signal is generated, n historical charging periods of the target battery are obtained, where n is a natural number greater than zero, the charging capacity and actual charging duration of the target battery in each charging period are obtained, and the preset charging duration corresponding to the charging capacity of the target battery is obtained. The charging period corresponding to a value obtained by subtracting the preset charging duration from the actual charging time is greater than a preset threshold and is set as a side feedback value. The ratio of the side feedback value to n is set as an over-discharge assessment value, and the over-discharge assessment value is discriminated and processed to obtain a stable signal or a potential signal.

4. The battery over-discharge monitoring system based on a mobile energy storage charging vehicle according to claim 1 is characterized in that: The historical record over-discharge damage assessment and analysis process is as follows: The historical discharge information of the target battery within the time threshold is obtained, and the historical discharge information includes the total number of over-discharges, the total over-discharge duration, and the total over-discharge amount; the product value obtained by multiplying the corresponding values ​​of the total number of discharges, the total over-discharge duration, and the total over-discharge amount is obtained, and the product value is set as the battery over-discharge coefficient.

5. The battery over-discharge monitoring system based on a mobile energy storage charging vehicle according to claim 1 is characterized in that: The over-discharge induction level assessment and analysis process is as follows: The historical management information of the target battery within the time threshold is obtained, the historical management information includes an operation evaluation coefficient and an over-discharge defect index, the operation evaluation coefficient and the over-discharge defect index are compared and analyzed with a preset operation evaluation coefficient threshold and a preset over-discharge defect index threshold, the number of operation evaluation coefficients and over-discharge defect indices that are greater than or equal to the preset operation evaluation coefficient threshold and the preset over-discharge defect index threshold is set as an over-discharge potential evaluation value, the over-discharge potential evaluation value is discriminated and processed to obtain conventional impact, intermediate impact and advanced impact, and the conventional impact, intermediate impact and advanced impact are set as the over-discharge boosting coefficient G, G=1, 2, 3.

6. The battery over-discharge monitoring system based on a mobile energy storage charging vehicle according to claim 5 is characterized in that: The operation evaluation coefficient represents the product of the total historical unused time of the target battery and the delayed charging time after data normalization processing, the total historical unused time represents the total time corresponding to the target battery not performing a discharge operation or a charging operation, and the delayed charging time represents the sum of the remaining power of the target battery and the time from the preset remaining power threshold moment to the target battery charging moment; the over-discharge defect index represents the product of the total volume of gas generated within the total historical over-discharge time of the target battery and the average value of the battery operating temperature after data normalization processing.

7. The battery over-discharge monitoring system based on a mobile energy storage charging vehicle according to claim 1 is characterized in that: The self-comprehensive evaluation matching analysis process is as follows: Obtain the target battery's own data within the time threshold, including the internal resistance change curve and the capacity evaluation value; obtain the difference between the current internal resistance value and the initial internal resistance value from the internal resistance change curve, and set it as the internal resistance growth value; set the ratio between the internal resistance growth value and the value corresponding to the input time as the internal resistance floating coefficient, and the input time represents the time from the time when the target battery is put into use to the current time; The actual maximum energy storage capacity value corresponding to the target battery at the current moment is obtained, the difference between the actual maximum energy storage capacity value and the initial actual maximum energy storage capacity is set as the capacity degradation value, the ratio between the capacity degradation value and the input time is set as the capacity degradation coefficient, and the product value obtained by multiplying the capacity degradation coefficient and the corresponding value of the environmental promotion value is set as the capacity evaluation value, and the environmental promotion value represents the overlap time between the time corresponding to the ambient temperature exceeding the preset temperature and the time corresponding to the ambient humidity exceeding the preset humidity during the input time; The internal resistance floating coefficient and capacity evaluation value are compared and analyzed with the preset internal resistance floating coefficient and capacity evaluation value thresholds, and the number of internal resistance floating coefficients and capacity evaluation values ​​that are greater than or equal to the preset internal resistance floating coefficient and capacity evaluation value thresholds is set as the self-offset coefficient, and the preset offset value corresponding to the self-offset coefficient in the preset self-offset coefficient interval is obtained, and it is set as the offset evaluation level.

8. The battery over-discharge monitoring system based on a mobile energy storage charging vehicle according to claim 1 is characterized in that: The comprehensive evaluation and analysis process of over-discharge depth is as follows: The value obtained by multiplying the battery over-discharge coefficient, the over-discharge assist coefficient G and the numerical values ​​corresponding to the offset evaluation level is set as the over-discharge depth evaluation coefficient, and the over-discharge depth evaluation coefficient is discriminated and processed to obtain a conventional management signal, an intermediate management signal or an advanced management signal.

9. A battery over-discharge monitoring method based on a mobile energy storage charging vehicle, the method being applied to the battery over-discharge monitoring system based on a mobile energy storage charging vehicle described in 1-8, characterized in that: The following steps are involved: Step 1: retrieve the discharge condition information of the target battery, perform charge and discharge safety monitoring feedback analysis on the discharge condition information, and perform discrimination processing on the obtained over-discharge evaluation difference. If a normal signal is obtained, proceed to step 2. If an over-discharge signal is obtained, feedback output is performed; Step 2: Perform a potential over-discharge risk analysis on the target battery by means of information feedback to determine whether the target battery has a potential over-discharge risk, and output the obtained stable signal or potential signal as feedback; Step 3: Based on the historical record of over-discharge damage evaluation and analysis of the historical discharge information under information feedback, the battery over-discharge coefficient is obtained, and the battery over-discharge coefficient is substituted into step 6; Step 4: Perform over-discharge induction level assessment and analysis on historical management information in a progressive manner, perform discrimination processing on the obtained over-discharge potential assessment value, obtain the over-discharge assistance coefficient G and substitute it into step 6; Step 5: Collect the target battery's own data, and perform comprehensive evaluation matching analysis on the data to obtain the offset evaluation level, and substitute the offset evaluation level into step 6; Step six: Based on the fusion analysis of the battery over-discharge coefficient, the over-discharge assist coefficient G and the offset evaluation level, the over-discharge depth evaluation coefficient is obtained, and the over-discharge depth evaluation coefficient is discriminated and processed to obtain a conventional management signal, an intermediate management signal or an advanced management signal and output feedback.

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