Battery aging and temperature over-limit fault diagnosis method for energy storage system and energy storage system

Abstract

The present invention discloses a method for diagnosing battery aging and over-temperature faults of an energy storage system and an energy storage system, and relates to the technical field of energy storage systems. The method includes establishing a refrigeration capacity reference model, which includes compressor operating condition reference data, fan operating condition reference data, expansion valve operating condition reference data, and battery pack core temperature reference data; calculating compressor offset value, fan offset value, expansion valve offset value, and core temperature offset value; when the compressor offset value, fan offset value, expansion valve offset value, and core temperature offset value meet any condition, a fault warning signal is issued. The present invention mainly solves the problem of how to make early diagnosis and early warning of battery pack aging faults; the present invention provides early diagnosis and early warning of battery aging and over-temperature faults for energy storage systems, and does not need to rely on complex algorithms, high-end sensors, and maintenance by operators, which can save a lot of economic costs and energy consumption.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage systems and fault diagnosis methods thereof, and in particular to a battery aging and over-temperature fault diagnosis method for energy storage systems and an energy storage system. Background Art

[0002] An energy storage system is a system used to store and release electrical energy. It involves the conversion between electrical energy and chemical energy, as well as the conversion between electrical energy and electrical energy. In the above process, a lot of heat will be generated. If the heat cannot be discharged in time, the temperature of the energy storage system will rise, bringing safety hazards, and thus affecting the performance, life and normal operation of the energy storage system.

[0003] The battery pack is one of the core components of the energy storage system. It has a large amount of heat. In order to control the temperature of the battery pack and improve the charging and discharging efficiency of the battery pack, a thermal management system needs to be configured in the energy storage system to dissipate heat for the battery pack. Among them, the liquid cooling system using phase change refrigeration technology is the most widely used thermal management system solution.

[0004] Battery pack aging is one of the common types of failures, which will affect the performance, operating stability, power consumption and service life of the energy storage system.

[0005] One of the manifestations of battery pack aging is increased heat generation. However, the increased heat generation caused by battery pack aging is often not immediately reflected in the temperature change of the battery pack. The reason is that the thermal management system in the prior art does not consider the diagnosis of battery pack aging. When the temperature of the battery pack rises, the thermal management system will take certain measures (such as increasing the operating power of the compressor, increasing the opening of the expansion valve, increasing the speed of the fan, etc.) to suppress the temperature change of the battery pack, so that the temperature of the battery pack is always maintained in the optimal energy efficiency temperature zone.

[0006] Due to the above reasons, the aging failure of the battery pack of the energy storage system cannot be fed back in time. When the thermal management system is not sufficient to suppress the temperature change of the battery pack, the aging failure of the battery pack has become very serious and a large amount of additional electrical energy has been consumed (extra power consumption from the thermal management system and the extra power consumption of the battery pack).

[0007] In summary, how to use the thermal management system to make early diagnosis and warning of battery pack aging failures and temperature over-limit failures in energy storage systems has become an urgent problem to be solved. Summary of the invention

[0008] The object of the present invention is to provide a battery aging and over-temperature fault diagnosis method and energy storage system for an energy storage system, which can make early diagnosis and warning of battery pack aging faults and over-temperature faults of the energy storage system through a thermal management system.

[0009] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a method for diagnosing battery aging and over-temperature faults of an energy storage system, applied to a thermal management system, the thermal management system being used to dissipate heat for a battery pack in the energy storage system; the thermal management system comprising a compressor, a condenser with a fan, an expansion valve, and a heat exchanger suitable for heat exchange with the battery pack; the refrigerant channels of the compressor, the condenser, the expansion valve, and the heat exchanger are sequentially connected, so that the refrigerant can circulate among the refrigerant channels of the compressor, the condenser, the expansion valve, and the heat exchanger;

[0010] The method includes:

[0011] S1. Select several groups of reference operating environment data;

[0012] S2. After the thermal management system is put into operation, the operating environment data is detected in real time within a preset time. Whenever the operating environment data is the same as the reference operating environment data, or whenever the deviation between the operating environment data and the reference operating environment data is within a preset range, the compressor operating condition data, the fan operating condition data, the expansion valve operating condition data and the battery pack core temperature data at that moment are collected;

[0013] S3, using each group of the reference operating environment data as an independent variable, and using the compressor operating condition data, the fan operating condition data, the expansion valve operating condition data and the battery pack core temperature data collected when the corresponding operating environment data is collected as dependent variables, to establish a refrigeration capacity reference model;

[0014] The refrigeration capacity reference model at least includes: corresponding compressor operating condition reference data, fan operating condition reference data, expansion valve operating condition reference data and battery pack cell temperature reference data under each group of reference operating environment data;

[0015] S4. After the refrigeration capacity reference model is established, during the operation of the thermal management system, real-time data of the operating environment, real-time data of the compressor operating condition, real-time data of the fan operating condition, real-time data of the expansion valve operating condition, and real-time data of the battery pack core temperature are collected in real time;

[0016] S5. Whenever the real-time operating environment data is the same as the reference operating environment data, or whenever the deviation between the operating environment data and the reference operating environment data is within a preset range, the offset value between the real-time data of the compressor operating condition at that moment and the corresponding reference data of the compressor operating condition is calculated, which is recorded as the compressor offset value, and the offset value between the real-time data of the fan operating condition at that moment and the corresponding reference data of the fan operating condition is calculated, which is recorded as the fan offset value, and the offset value between the real-time data of the expansion valve operating condition at that moment and the corresponding reference data of the expansion valve operating condition is calculated, which is recorded as the expansion valve offset value, and the offset value between the real-time data of the battery pack cell temperature at that moment and the corresponding reference data of the battery pack cell temperature is calculated, which is recorded as the cell temperature offset value;

[0017] S6: When the compressor offset value, the fan offset value, the expansion valve offset value, and the battery core temperature offset value meet any of the following conditions, a fault warning signal is issued:

[0018] a. Under all the reference operating environment data, any one of the compressor offset value, the fan offset value and the expansion valve offset value is greater than a preset threshold;

[0019] b. Under all the reference operating environment data, the compressor offset value, the fan offset value and the expansion valve offset value are all greater than a preset threshold value;

[0020] c. Under all the reference operating environment data, the weighted sum of the compressor offset value, the fan offset value and the expansion valve offset value is greater than a preset threshold;

[0021] d. Under all the reference operating environment data, the operating environment real-time data, the compressor operating condition real-time data and the fan operating condition real-time data simultaneously reach the rated maximum value;

[0022] e. Under any of the reference operating environment data, the operating environment real-time data, the compressor operating condition real-time data and the fan operating condition real-time data simultaneously reach the rated maximum value, but the battery cell temperature offset value is still greater than the preset threshold value;

[0023] S7. Repeat steps S4 to S6.

[0024] In the above technical solution, the reference operating environment data, the operating environment data and the operating environment real-time data all include the ambient temperature (° C.) and the battery pack operating current (%).

[0025] In the above technical solution, the compressor operating condition data, the compressor operating condition reference data and the compressor operating condition real-time data are all the rotational speed frequency (Hz) of the compressor.

[0026] In the above technical solution, the refrigeration capacity reference model includes a compressor operating condition reference sub-model; the compressor operating condition reference sub-model is specifically: a regression model that uses each group of reference operating environment data as an independent variable and the compressor operating condition data collected when the corresponding operating environment data is used as a dependent variable.

[0027] In the above technical solution, the fan operating condition data, the fan operating condition reference data and the fan operating condition real-time data are all the power (W) of the fan.

[0028] In the above technical solution, the cooling capacity reference model includes a fan operating condition reference sub-model; the fan operating condition reference sub-model is specifically: a regression model which takes each group of the reference operating environment data as an independent variable, and takes the fan operating condition data collected when the corresponding operating environment data is used as a dependent variable.

[0029] In the above technical solution, the expansion valve operating condition data, the expansion valve operating condition reference data and the expansion valve operating condition real-time data are all the opening degree (step) of the expansion valve.

[0030] In the above technical solution, the refrigeration capacity reference model includes an expansion valve operating condition reference sub-model; the expansion valve operating condition reference sub-model is specifically: a regression model which takes each group of the reference operating environment data as an independent variable, and takes the expansion valve operating condition data collected when the corresponding operating environment data is used as a dependent variable.

[0031] In the above technical solution, in step S5:

[0032] The compressor offset value is specifically:

[0033]

[0034] Wherein, Δf1 is the difference between the real-time data of the compressor operating condition and the reference data of the compressor operating condition;

[0035] The fan offset value is specifically:

[0036]

[0037] Wherein, Δf2 is the difference between the real-time data of the fan operating condition and the reference data of the fan operating condition;

[0038] The expansion valve offset value is specifically:

[0039]

[0040] Wherein, Δf3 is the difference between the real-time data of the expansion valve operating condition and the reference data of the expansion valve operating condition.

[0041] An energy storage system employs the above-mentioned method for diagnosing battery aging and over-temperature faults of the energy storage system.

[0042] Compared with the prior art, the beneficial effects of the present invention are as follows: the battery aging and over-temperature fault diagnosis method of the energy storage system and the energy storage system of the present invention establish a refrigeration capacity reference model by collecting compressor operating condition data, fan operating condition data, expansion valve operating condition data and battery pack core temperature data. In the subsequent operation of the thermal management system, real-time data of the operating environment, real-time data of the compressor operating condition, real-time data of the fan operating condition, real-time data of the expansion valve operating condition and real-time data of the battery pack core temperature are collected in real time, and compared with the data in the refrigeration capacity reference model, so as to warn of battery pack aging fault and over-temperature fault; the battery aging and over-temperature fault diagnosis method of the energy storage system and the energy storage system of the present invention can provide early diagnosis and warning of battery aging and over-temperature faults for the energy storage system, without relying on complex algorithms, high-end sensors and maintenance by operators, which can save a lot of economic costs and energy consumption, and avoid further expansion of energy storage system faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a system structure diagram of the thermal management system in the present invention.

[0044] The accompanying drawings are marked as follows: 1. compressor; 2. condenser; 3. fan; 4. expansion valve; 5. heat exchanger; 10. battery pack. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] This embodiment provides a battery aging and over-temperature fault diagnosis method for an energy storage system, which is applied to a thermal management system to provide early diagnosis and warning of battery pack aging faults and over-temperature faults for the energy storage system.

[0047] The thermal management system is used to dissipate heat for the battery pack in the energy storage system; see Figure 1 Specifically, the thermal management system includes a compressor 1 , a condenser 2 with a fan 3 , an expansion valve 4 , and a heat exchanger 5 suitable for performing heat exchange with a battery pack 10 .

[0048] Among them, the compressor 1 is a compressor 1 used for compressing refrigerant in the refrigeration system, specifically a variable frequency compressor; the condenser 2 is a condenser used for condensing refrigerant in the refrigeration system, which dissipates heat through its own fan 3; the expansion valve 4 is an expansion valve 4 used for throttling refrigerant in the refrigeration system, specifically an electronic expansion valve.

[0049] It should be noted that the heat exchanger 5 is an evaporator in the refrigeration system for evaporating the refrigerant and thereby absorbing heat; in some possible embodiments, the heat exchange method between the heat exchanger 5 and the battery pack 10 is liquid cooling, that is, the heat of the battery pack 10 is absorbed by the liquid cooling medium in the liquid cooling unit, and the heat of the liquid cooling medium is absorbed by the heat exchanger 5 of this embodiment; in other possible embodiments, the heat exchange method between the heat exchanger 5 and the battery pack 10 is direct cooling, that is, the heat exchanger 5 is directly attached to the battery pack 10, so that the heat exchanger and the battery pack 10 directly exchange heat.

[0050] The refrigerant channels of the compressor 1, condenser 2, expansion valve 4 and heat exchanger 5 are connected in sequence, so that the refrigerant can circulate among the refrigerant channels of the compressor 1, condenser 2, expansion valve 4 and heat exchanger 5. With this arrangement, the refrigeration function of the thermal management system can be realized.

[0051] It is understandable that the thermal management system or its upper system at least includes a control device, such as a programmable controller, an embedded system and an industrial computer.

[0052] The battery aging and over-temperature fault diagnosis method of the energy storage system of this embodiment includes:

[0053] S1. Select several groups of reference operating environment data;

[0054] S2. After the thermal management system is put into operation, the operating environment data is detected in real time within a preset time. Whenever the operating environment data is the same as the reference operating environment data, or whenever the deviation between the operating environment data and the reference operating environment data is within a preset range (for example, the deviation is less than 2%), the compressor operating condition data, the fan operating condition data, the expansion valve operating condition data and the battery pack core temperature data at that moment are collected;

[0055] S3, using each group of reference operating environment data as an independent variable, and using the compressor operating condition data, fan operating condition data, expansion valve operating condition data and battery pack core temperature data collected when the corresponding operating environment data is used as a dependent variable, to establish a refrigeration capacity reference model;

[0056] The refrigeration capacity reference model at least includes: corresponding compressor operating condition reference data, fan operating condition reference data, expansion valve operating condition reference data and battery pack cell temperature reference data under each set of reference operating environment data;

[0057] S4. After the refrigeration capacity reference model is established, during the operation of the thermal management system, real-time data of the operating environment, real-time data of the compressor operating condition, real-time data of the fan operating condition, real-time data of the expansion valve operating condition, and real-time data of the battery cell temperature are collected in real time;

[0058] S5. Whenever the real-time operating environment data is the same as the reference operating environment data, or whenever the deviation between the operating environment data and the reference operating environment data is within a preset range (for example, the deviation is less than 2%), the offset value between the real-time data of the compressor operating condition at that moment and the corresponding reference data of the compressor operating condition is calculated, which is recorded as the compressor offset value, and the offset value between the real-time data of the fan operating condition at that moment and the corresponding reference data of the fan operating condition is calculated, which is recorded as the fan offset value, and the offset value between the real-time data of the expansion valve operating condition at that moment and the corresponding reference data of the expansion valve operating condition is calculated, which is recorded as the expansion valve offset value, and the offset value between the real-time data of the battery pack cell temperature at that moment and the corresponding reference data of the battery pack cell temperature is calculated, which is recorded as the cell temperature offset value;

[0059] S6, when the compressor offset value, fan offset value, expansion valve offset value and battery core temperature offset value meet any of the following conditions, a fault warning signal is issued:

[0060] a. Under all reference operating environment data, any one of the compressor offset value, the fan offset value and the expansion valve offset value is greater than a preset threshold;

[0061] b. Under all reference operating environment data, the compressor offset value, the fan offset value and the expansion valve offset value are all greater than the preset threshold value;

[0062] c. Under all reference operating environment data, the weighted sum of the compressor offset value, the fan offset value and the expansion valve offset value is greater than a preset threshold;

[0063] d. Under all reference operating environment data, the real-time operating environment data, the real-time compressor operating condition data and the real-time fan operating condition data simultaneously reach the rated maximum value;

[0064] e. Under any reference operating environment data, the operating environment real-time data, the compressor operating condition real-time data and the fan operating condition real-time data reach the rated maximum value at the same time, but the cell temperature offset value is still greater than the preset threshold value;

[0065] S7. Repeat steps S4 to S6.

[0066] The issuance of a fault warning signal indicates that the current cooling capacity of the thermal management system is higher than the reference value (compressor operating condition reference data, fan operating condition reference data, expansion valve operating condition reference data and battery pack cell temperature reference data). The energy storage system may have a battery aging fault or a temperature over-limit fault (but the temperature change is suppressed by the thermal management system). The operators of the energy storage system can focus on detecting and eliminating the above faults.

[0067] Specifically, the reference operating environment data, the operating environment data and the operating environment real-time data all include the ambient temperature (° C.) and the battery pack operating current (%).

[0068] It can be understood that the collection of ambient temperature can be achieved through a temperature sensor installed near the system or in the computer room / chassis. The temperature sensor realizes signal connection with the host computer (i.e., the control device) through an analog output interface or a communication interface, thereby realizing the collection and transmission of the ambient temperature.

[0069] It can be understood that the collection of the battery pack operating current can be extracted from the operating data fed back by the battery management chip / power management chip of the battery pack to the upper computer (i.e., the control device); or the battery pack operating current can be directly transmitted to the upper computer (i.e., the control device) through the current transmitter in the energy storage system, thereby realizing the collection; in this embodiment, the battery pack operating current is a percentage value, specifically the ratio of the battery pack operating current to the maximum current of the battery pack.

[0070] It can be understood that the collection of battery cell temperature can be extracted from the operating data fed back by the battery management chip / power management chip of the battery pack to the upper computer (i.e., the control device); or the battery cell temperature can be directly transmitted to the upper computer (i.e., the control device) through the temperature sensor in the energy storage system, thereby realizing collection.

[0071] Specifically, the compressor operating condition data, the compressor operating condition reference data, and the compressor operating condition real-time data are all the rotational speed frequency (Hz) of the compressor.

[0072] In fact, the rotational frequency (Hz) of the compressor can be directly obtained by the control device based on the operating information fed back by the signal line of the compressor, or it can be obtained by calculating physical quantities such as the input power, output power, input current and output current of the compressor.

[0073] Specifically, the refrigeration capacity reference model includes a compressor operating condition reference sub-model; the compressor operating condition reference sub-model is specifically: a regression model that takes each group of reference operating environment data as an independent variable and takes the compressor operating condition data collected when the corresponding operating environment data is used as a dependent variable.

[0074] In fact, by using computer mathematical software, inputting several groups of reference operating environment data (as independent variables, including ambient temperature (°C) and battery pack operating current (%)), as well as the compressor operating condition data collected when the corresponding operating environment data is collected (as the dependent variable), and performing linear fitting or nonlinear fitting according to the actual operating characteristics of the thermal management system, the compressor operating condition reference sub-model can be obtained.

[0075] Specifically, the fan operating condition data, the fan operating condition reference data and the fan operating condition real-time data are all the power (W) of the fan.

[0076] In fact, the power (W) of the fan can be directly obtained by the control device based on the operating information fed back by the signal line of the fan, or it can be obtained by calculating physical quantities such as the fan's input power, output power, input current and output current.

[0077] Specifically, the cooling capacity reference model includes a fan operating condition reference sub-model; the fan operating condition reference sub-model is specifically: a regression model that uses each group of reference operating environment data as an independent variable and the fan operating condition data collected when the corresponding operating environment data is used as a dependent variable.

[0078] In fact, by using computer mathematical software, inputting several groups of reference operating environment data (as independent variables, including ambient temperature (°C) and battery pack operating current (%)), as well as the fan operating condition data collected when the corresponding operating environment data is obtained (as the dependent variable), and performing linear fitting or nonlinear fitting according to the actual operating characteristics of the thermal management system, a reference sub-model of the fan operating condition can be obtained.

[0079] Specifically, the expansion valve operating condition data, the expansion valve operating condition reference data and the expansion valve operating condition real-time data are all the opening degrees (steps) of the expansion valve.

[0080] In fact, the opening degree (step) of the expansion valve can be directly obtained by the control device based on the operating information fed back by the signal line of the expansion valve.

[0081] Specifically, the refrigeration capacity reference model includes an expansion valve operating condition reference sub-model; the expansion valve operating condition reference sub-model is specifically: a regression model that uses each group of reference operating environment data as an independent variable and the expansion valve operating condition data collected when the corresponding operating environment data is used as a dependent variable.

[0082] In fact, by using computer mathematical software, inputting several groups of reference operating environment data (as independent variables, including ambient temperature (°C) and battery pack operating current (%)), as well as the expansion valve operating condition data collected when the corresponding operating environment data is obtained (as the dependent variable), and performing linear fitting or nonlinear fitting according to the actual operating characteristics of the thermal management system, the expansion valve operating condition reference sub-model can be obtained.

[0083] In step S5:

[0084] Compressor offset values, specifically:

[0085]

[0086] Wherein, Δf1 is the difference between the real-time data of the compressor operating condition and the reference data of the compressor operating condition;

[0087] Fan offset value, specifically:

[0088]

[0089] Among them, Δf2 is the difference between the real-time data of the fan operating condition and the reference data of the fan operating condition;

[0090] Expansion valve offset value, specifically:

[0091]

[0092] Wherein, Δf3 is the difference between the real-time data of the expansion valve operating condition and the reference data of the expansion valve operating condition.

[0093] Specifically, in step S6, the compressor offset value is greater than a preset threshold value, and the specific judgment method is: the compressor offset value>30%.

[0094] Specifically, in step S6, the fan offset value is greater than a preset threshold value, and the specific judgment method is: the fan offset value>30%.

[0095] Specifically, in step S6, the expansion valve offset value is greater than a preset threshold value, and the specific judgment method is: the expansion valve offset value>30%.

[0096] Specifically, in step S5, the compressor offset value is:

[0097] Battery cell temperature offset value (°C) = battery pack battery cell temperature real-time data (°C) - battery pack battery cell temperature reference data (°C).

[0098] Specifically, in step S6, the cell temperature offset value is greater than a preset threshold value, which is a numerical value assigned artificially according to engineering experience based on factors such as the battery pack type and scale of the energy storage system, and the geographical conditions of the energy storage system (such as local climate, sunshine time, latitude, altitude, etc.). For example, it can be defined as 5°C, 10°C, 15°C and 20°C.

[0099] It should be noted that in step S6, the weighted sum of the compressor offset value, the fan offset value and the expansion valve offset value is greater than the preset threshold value, specifically: a weighting coefficient is assigned to each of the compressor offset value, the fan offset value and the expansion valve offset value (the weighting coefficient is a numerical value assigned artificially according to engineering experience), and the product of the compressor offset value and its weighting coefficient is added, and the product of the fan offset value and its weighting coefficient is added, and the product of the expansion valve offset value and its weighting coefficient is added to obtain the weighted sum value; the preset threshold value is also a numerical value assigned artificially according to engineering experience.

[0100] The following will use a specific case to further illustrate the technical solution of the present invention:

[0101] According to the needs, a certain place establishes an 8kW energy storage system. The battery pack of the energy storage system adopts the thermal management system of this embodiment to dissipate heat, and the heat exchange method between the heat exchanger and the battery pack is liquid cooling.

[0102] The battery pack of the energy storage system is equipped with a total of 16 battery clusters, and the calorific value of each battery cluster is 0.5kW. The full-load calorific value of the battery pack in the energy storage system is 16×0.5=8kW, the self-heating of the compressor is 0.5kW, and the self-heating of the water pump in the liquid cooling unit is 0.5kW; when the energy storage system is running at full load, the maximum calorific value (also the maximum cooling capacity of the thermal management system) is 8kW+0.5kW+0.5kW=9kW; when the energy storage system is running at half load, the calorific value (also the cooling capacity of the thermal management system) is 4kW+0.5kW+0.5kW=5kW.

[0103] In the summer of this place, 4 sets of reference operating environment data were selected:

[0104] 1. When the ambient temperature is the lowest in a day, the battery pack operating current is 50%;

[0105] 2. When the ambient temperature is the lowest in a day, the battery pack operating current is at its maximum value;

[0106] 3. When the ambient temperature is the highest during the day, the battery pack operating current is 50%;

[0107] 4. When the ambient temperature is highest during the day, the battery pack operating current is at its maximum value.

[0108] After the energy storage system and the thermal management system of this embodiment are put into operation, with one day as the "preset time" in step S2, the control device collects operating environment data, compressor operating condition data, fan operating condition data, expansion valve operating condition data and battery pack core temperature data in real time, as shown in the following table:

[0109]

[0110] On the same day, if the operating environment data is the same as the reference operating environment data for multiple times, or whenever the deviation between the operating environment data and the reference operating environment data is within the preset range for multiple times, the compressor operating condition data, fan operating condition data, expansion valve operating condition data and battery cell temperature data at that moment are collected each time, and the average value is taken with the previous data to iterate the data in the above table. After the "preset time" is over, the refrigeration capacity reference model can be obtained.

[0111] The reference model of cooling capacity obtained in this case is as follows:

[0112]

[0113]

[0114] During the operation of the thermal management system, real-time data on the operating environment, real-time data on the operating conditions of the compressor, real-time data on the operating conditions of the fan, real-time data on the operating conditions of the expansion valve, and real-time data on the temperature of the battery cells are collected in real time.

[0115] One day, one set of data reflected:

[0116]

[0117] It can be seen that under the above four sets of real-time operating environment data, the compressor offset value, the fan offset value and the expansion valve offset value are all greater than 30%, which meets the judgment condition of step S6, indicating that the cooling capacity of the thermal management system is relatively high (possibly to suppress the temperature change caused by battery aging failure), and a fault warning signal needs to be issued; in addition, among the real-time operating environment data 4, the real-time operating environment data, the real-time data of the compressor operating condition and the real-time data of the fan operating condition reach the rated maximum value at the same time, but the battery cell temperature offset value is still greater than the preset threshold value (for example, 15°C), which also meets the judgment condition of step S6, indicating that the battery pack may have thermal runaway (i.e., a temperature over-limit failure has occurred), and a fault warning signal also needs to be issued.

[0118] It is understandable that the control device sends a fault warning signal through its own interactive device, or the control device sends a fault warning signal to its host computer to warn the operator of the energy storage system or thermal management system of battery pack aging failure and temperature exceeding limit failure.

[0119] This embodiment also provides an energy storage system, which applies the above-mentioned battery aging and temperature over-limit fault diagnosis method of the energy storage system.

[0120] The battery aging and over-temperature fault diagnosis method and energy storage system of the energy storage system of the present embodiment establish a refrigeration capacity reference model by collecting compressor operating condition data, fan operating condition data, expansion valve operating condition data and battery pack core temperature data. In the subsequent operation of the thermal management system, real-time data of the operating environment, real-time data of the compressor operating condition, real-time data of the fan operating condition, real-time data of the expansion valve operating condition and real-time data of the battery pack core temperature are collected in real time, and compared with the data in the refrigeration capacity reference model, so as to warn of battery pack aging fault and over-temperature fault. The battery aging and over-temperature fault diagnosis method and energy storage system of the energy storage system of the present embodiment can provide early diagnosis and warning of battery aging and over-temperature fault for the energy storage system, without relying on complex algorithms, high-end sensors and maintenance by operators, which can save a lot of economic costs and energy consumption, and avoid further expansion of energy storage system faults.

[0121] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for diagnosing battery aging and over-temperature faults in an energy storage system, which is applied to a thermal management system, wherein the thermal management system is used to dissipate heat for a battery pack in the energy storage system; The thermal management system includes a compressor, a condenser with a fan, an expansion valve, and a heat exchanger suitable for performing heat exchange with the battery pack; The refrigerant channels of the compressor, the condenser, the expansion valve, and the heat exchanger are connected in sequence, so that the refrigerant can circulate among the refrigerant channels of the compressor, the condenser, the expansion valve, and the heat exchanger; It is characterized in that The method includes: S1. Select several groups of reference operating environment data; S2. After the thermal management system is put into operation, the operating environment data is detected in real time within a preset time. Whenever the operating environment data is the same as the reference operating environment data, or whenever the deviation between the operating environment data and the reference operating environment data is within a preset range, the compressor operating condition data, the fan operating condition data, the expansion valve operating condition data and the battery pack core temperature data at that moment are collected; S3, using each group of the reference operating environment data as an independent variable, and using the compressor operating condition data, the fan operating condition data, the expansion valve operating condition data and the battery pack core temperature data collected when the corresponding operating environment data is collected as dependent variables, to establish a refrigeration capacity reference model; The refrigeration capacity reference model at least includes: corresponding compressor operating condition reference data, fan operating condition reference data, expansion valve operating condition reference data and battery pack cell temperature reference data under each group of reference operating environment data; S4. After the refrigeration capacity reference model is established, during the operation of the thermal management system, real-time data of the operating environment, real-time data of the compressor operating condition, real-time data of the fan operating condition, real-time data of the expansion valve operating condition, and real-time data of the battery pack core temperature are collected in real time; S5. Whenever the real-time operating environment data is the same as the reference operating environment data, or whenever the deviation between the operating environment data and the reference operating environment data is within a preset range, the offset value between the real-time data of the compressor operating condition at that moment and the corresponding reference data of the compressor operating condition is calculated, which is recorded as the compressor offset value, and the offset value between the real-time data of the fan operating condition at that moment and the corresponding reference data of the fan operating condition is calculated, which is recorded as the fan offset value, and the offset value between the real-time data of the expansion valve operating condition at that moment and the corresponding reference data of the expansion valve operating condition is calculated, which is recorded as the expansion valve offset value, and the offset value between the real-time data of the battery pack cell temperature at that moment and the corresponding reference data of the battery pack cell temperature is calculated, which is recorded as the cell temperature offset value; S6: When the compressor offset value, the fan offset value, the expansion valve offset value, and the battery core temperature offset value meet any of the following conditions, a fault warning signal is issued: a. Under all the reference operating environment data, any one of the compressor offset value, the fan offset value and the expansion valve offset value is greater than a preset threshold; b. Under all the reference operating environment data, the compressor offset value, the fan offset value and the expansion valve offset value are all greater than a preset threshold value; c. Under all the reference operating environment data, the weighted sum of the compressor offset value, the fan offset value and the expansion valve offset value is greater than a preset threshold; d. Under all the reference operating environment data, the operating environment real-time data, the compressor operating condition real-time data and the fan operating condition real-time data simultaneously reach the rated maximum value; e. Under any of the reference operating environment data, the operating environment real-time data, the compressor operating condition real-time data and the fan operating condition real-time data simultaneously reach the rated maximum value, but the battery cell temperature offset value is still greater than the preset threshold value; S7. Repeat steps S4 to S6.

2. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to claim 1, characterized in that: The reference operating environment data, the operating environment data and the operating environment real-time data all include the ambient temperature and the battery pack operating current; The unit of the ambient temperature is °C, and the unit of the battery pack operating current is %.

3. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to claim 1, characterized in that: The compressor operating condition data, the compressor operating condition reference data and the compressor operating condition real-time data are all rotational speed frequencies of the compressor; The unit of the rotational speed frequency of the compressor is Hz.

4. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to claim 3, characterized in that: The refrigeration capacity reference model includes a compressor operating condition reference sub-model; The compressor operating condition reference sub-model is specifically a regression model that uses each group of the reference operating environment data as an independent variable and uses the compressor operating condition data collected when the corresponding operating environment data is collected as a dependent variable.

5. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to claim 1, characterized in that: The fan operating condition data, the fan operating condition reference data and the fan operating condition real-time data are all the power of the fan; The unit of the fan power is W.

6. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to claim 5, characterized in that: The cooling capacity reference model includes a fan operating condition reference sub-model; The fan operating condition reference sub-model is specifically a regression model that uses each group of the reference operating environment data as an independent variable and uses the fan operating condition data collected when the corresponding operating environment data is collected as a dependent variable.

7. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to claim 1, characterized in that: The expansion valve operating condition data, the expansion valve operating condition reference data and the expansion valve operating condition real-time data are all the opening degree of the expansion valve; The unit of the opening degree of the expansion valve is step.

8. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to claim 7, characterized in that: The refrigeration capacity reference model includes an expansion valve operating condition reference sub-model; The expansion valve operating condition reference sub-model is specifically a regression model that uses each group of the reference operating environment data as an independent variable and uses the expansion valve operating condition data collected when the corresponding operating environment data is used as a dependent variable.

9. The method for diagnosing battery aging and over-temperature faults of an energy storage system according to any one of claims 1 to 8, characterized in that: In step S5: The compressor offset value is specifically: Wherein, Δf1 is the difference between the real-time data of the compressor operating condition and the reference data of the compressor operating condition; The fan offset value is specifically: Wherein, Δf2 is the difference between the real-time data of the fan operating condition and the reference data of the fan operating condition; The expansion valve offset value is specifically: Wherein, Δf3 is the difference between the real-time data of the expansion valve operating condition and the reference data of the expansion valve operating condition.

10. An energy storage system, characterized in that: A battery aging and over-temperature fault diagnosis method for an energy storage system according to any one of claims 1 to 9 is applied.

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