Intelligent battery management system and method based on passive balancing

Abstract

The present invention discloses an intelligent battery management system and method based on passive balancing, which relates to the technical field of battery management. The method includes: real-time acquisition of the cell status information of the target battery group, wherein the cell status information includes cell voltage information, cell current information, and cell temperature information; acquiring the cell characteristic data of the target battery group, and configuring the balancing interval according to the cell characteristic data, including the balancing trigger voltage and the balancing cutoff voltage; interactively acquiring the temperature rise information of the target battery group, and combining the cell temperature information, calling the adaptive strategy for strategy allocation, wherein the adaptive strategy includes the forward-looking balancing strategy and the trigger-type balancing strategy; based on the adaptive strategy allocation result, according to the cell status information, combined with the balancing interval, the target battery group is intelligently managed. Then the technical effect of smooth passive balancing heat generation and reducing the difficulty of heat control is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management, and in particular to an intelligent battery management system and method based on passive balancing. Background Art

[0002] The battery pack is composed of multiple single cells (battery cells). Due to production process, use environment, aging and other reasons, the capacity and voltage of each single cell (battery cell) may be inconsistent. This inconsistency will lead to a decline in the overall performance of the battery pack, shorten the battery life, and even cause safety problems.

[0003] In the Battery Management System (BMS), battery balancing technology is the key to ensure the safe and efficient operation of the battery pack. Existing battery balancing calculations include passive balancing and active balancing. Among them, active balancing has less energy dissipation, but the circuit cost is high and the control is complex. Passive balancing is relatively low in cost and simple to control, so it is more widely used, but there are still technical problems such as difficulty in heat control and affecting charging efficiency. Summary of the invention

[0004] The present invention provides an intelligent battery management system and method based on passive balancing to solve the technical problem in the prior art that heat control is difficult and affects charging efficiency, and achieves the technical effect of smooth passive balanced heat generation and reducing the difficulty of heat control.

[0005] In a first aspect, the present invention provides an intelligent battery management system based on passive balancing, wherein the system comprises:

[0006] The information sensing module is used to collect and obtain the battery cell status information of the target battery pack in real time, wherein the battery cell status information includes battery cell voltage information, battery cell current information, and battery cell temperature information.

[0007] A trigger constraint module is used to obtain the cell characteristic data of the target battery pack and configure the balancing interval according to the cell characteristic data, including the balancing trigger voltage and the balancing cutoff voltage.

[0008] An adaptive matching module, the adaptive matching module is used to interactively obtain the temperature rise information of the target battery pack, and call the adaptive strategy to perform strategy allocation in combination with the battery cell temperature information, wherein the adaptive strategy includes a forward-looking balancing strategy and a triggered balancing strategy;

[0009] A management execution module is used to perform intelligent management of the target battery group based on the adaptive strategy allocation result, according to the battery cell status information, and in combination with the balancing interval.

[0010] In a second aspect, the present invention further provides an intelligent battery management method based on passive balancing, wherein the method comprises:

[0011] Real-time acquisition of the cell status information of the target battery pack, wherein the cell status information includes cell voltage information, cell current information, and cell temperature information; acquiring the cell characteristic data of the target battery pack, and configuring the balancing interval according to the cell characteristic data, including the balancing trigger voltage and the balancing cutoff voltage; interactively acquiring the temperature rise information of the target battery pack, and in combination with the cell temperature information, calling the adaptive strategy for strategy allocation, wherein the adaptive strategy includes a forward-looking balancing strategy and a trigger balancing strategy; based on the adaptive strategy allocation result, according to the cell status information, in combination with the balancing interval, intelligent management of the target battery pack is performed.

[0012] The present invention discloses an intelligent battery management system and method based on passive balancing, including: real-time collection of the cell status information of the target battery group, including cell voltage information, cell current information and cell temperature information; obtaining the cell characteristic data of the target battery group, and configuring the balancing interval according to these data, including the balancing trigger voltage and the balancing cutoff voltage; interactively obtaining the temperature rise information of the target battery group, and combining the cell temperature information, calling the adaptive strategy for strategy allocation, wherein the adaptive strategy includes the forward-looking balancing strategy and the trigger balancing strategy; based on the adaptive strategy allocation result, according to the cell status information and combined with the balancing interval, the target battery group is intelligently managed. The intelligent battery management system and method based on passive balancing disclosed by the present invention solves the technical problem that heat control is difficult and affects charging efficiency, and achieves the technical effect of smooth passive balancing heat generation and reducing the difficulty of heat control. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a structural schematic diagram of an intelligent battery management system based on passive balancing of the present invention;

[0014] Figure 2 It is a flow chart of the intelligent battery management method based on passive balancing of the present invention.

[0015] Explanation of the reference numerals: information perception module 11 , trigger constraint module 12 , adaptive matching module 13 , management execution module 14 . DETAILED DESCRIPTION

[0016] The technical solution provided in the embodiments of the present invention is to solve the technical problem that heat control is difficult and affects charging efficiency in the prior art. The overall idea adopted is as follows:

[0017] First, the cell status information of the target battery pack is acquired in real time, wherein the cell status information includes cell voltage information, cell current information, and cell temperature information. Next, the cell characteristic data of the target battery pack is acquired, and according to the cell characteristic data, the balancing interval is configured, including the balancing trigger voltage and the balancing cutoff voltage. Then, the temperature rise information of the target battery pack is acquired interactively, and in combination with the cell temperature information, the adaptive strategy is called to perform strategy allocation, wherein the adaptive strategy includes a forward-looking balancing strategy and a trigger-type balancing strategy. Finally, based on the adaptive strategy allocation result, the target battery pack is intelligently managed according to the cell status information and in combination with the balancing interval.

[0018] The above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods of the specification to better understand the above technical solution. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments used only to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. In addition, it should be noted that, for the convenience of description, only the parts related to the present invention are shown in the drawings, rather than all of them.

[0019] Embodiment 1

[0020] Figure 1 The figure is a flow chart of an intelligent battery management system based on passive balancing according to the present invention, wherein the system comprises:

[0021] The information sensing module 11 is used to collect and obtain the battery cell status information of the target battery pack in real time, wherein the battery cell status information includes battery cell voltage information, battery cell current information, and battery cell temperature information.

[0022] Optionally, the main function of the information sensing module 11 is to collect and obtain the cell status information of the target battery pack in real time. The collected information will be used to analyze the operating status of the battery pack to ensure the efficient and safe operation of the battery management system.

[0023] Optionally, a high-precision voltage sensor is used to detect the voltage information of each battery cell in real time through a resistor voltage divider circuit. The battery cell voltage information reflects the voltage level of each battery cell in the target battery pack. Exemplarily, it includes collecting the battery cells for a preset number of consecutive times through D / A conversion, and then calculating the average value of the multiple collected voltages and outputting it as the battery cell voltage information.

[0024] Optionally, the charge and discharge current of the battery cell is detected by a Hall effect sensor or a shunt resistor, and the current data of each battery cell is recorded to obtain the battery cell current information. The battery cell current information is used to analyze the current changes during the charging and discharging process to ensure that the battery pack operates within a safe current range.

[0025] Specifically, the current information collection method varies depending on the series and parallel connection of the battery pack. For series connection, only the current at one location needs to be measured; for parallel connection, the current of each branch needs to be measured separately; for mixed connection, the current of each series group and parallel branch needs to be measured separately to achieve accurate collection of current information of multiple cells in the target battery pack.

[0026] Optionally, the temperature of the battery cell is monitored in real time by a high-precision temperature sensor such as a thermocouple or thermistor to obtain the battery cell temperature information. By obtaining the battery cell temperature information and monitoring the temperature of each battery cell, it helps to ensure that the battery operates within the optimal temperature range, extend battery life and improve safety.

[0027] Specifically, to obtain the battery cell temperature information, first, the battery cell temperature is continuously collected for a preset number of times through D / A conversion, and then the highest temperature value among the multiple collections is obtained and output as the battery cell voltage information.

[0028] Optionally, the information perception module 11 also includes an integrated data processing component and a data transmission component. The integrated data processing component is used to process the collected battery cell status information in real time and perform preliminary analysis and filtering. The data transmission component is used to transmit the processed data to the control center of the battery management system via wired or wireless means.

[0029] Real-time multi-parameter monitoring of battery cell status provides a high-quality data basis for subsequent management decisions, improves the response speed and accuracy of the battery management system, and ensures the overall safety of the battery pack.

[0030] The trigger constraint module 12 is used to obtain the cell characteristic data of the target battery pack, and configure the balancing interval according to the cell characteristic data, including the balancing trigger voltage and the balancing cut-off voltage.

[0031] Specifically, the main function of the trigger constraint module 12 is to obtain the cell characteristic data of the target battery pack and configure the balancing interval according to these data, wherein the balancing interval includes the balancing trigger voltage and the balancing cutoff voltage, and the balancing interval specifies the trigger and termination thresholds of passive balancing. By accurately setting the balancing trigger voltage and the balancing cutoff voltage, it is ensured that the balancing interval is set within the safe voltage range, and the balancing operation is performed at the best time, thereby improving the balancing efficiency of the battery pack and the safety of the cells.

[0032] In some embodiments, obtaining cell characteristic data of a target battery pack and configuring a balancing interval according to the cell characteristic data, the execution steps include:

[0033] Obtain cell specification data of the target battery pack, and extract cell characteristic data, wherein the cell characteristic data at least includes a discharge cut-off voltage, a charge cut-off voltage, and a maximum tolerance voltage.

[0034] The equalization cut-off voltage is configured according to the charging cut-off voltage.

[0035] Based on the maximum tolerance voltage and in combination with the safety limit of the target battery pack, the equalization trigger voltage is configured, wherein the equalization trigger voltage is less than the maximum tolerance voltage.

[0036] The balancing interval is configured with the balancing trigger voltage as the upper limit of the interval and the balancing cut-off voltage as the lower limit of the interval.

[0037] Optionally, first, obtain the cell specification data of the target battery pack from the battery pack manufacturer or technical data, wherein the cell specification data includes basic parameters and operating characteristics of the cell, such as voltage range, capacity, maximum charge and discharge current, etc.

[0038] Specifically, the cell characteristic data is extracted from the acquired cell specification data, and the cell characteristic data at least includes the discharge cut-off voltage, that is, the lowest voltage at which the cell can operate safely during the discharge process; the charge cut-off voltage, that is, the highest voltage at which the cell can operate safely during the charging process. If the cell voltage reaches the charge cut-off voltage, the cell can be considered to be fully charged; the maximum tolerance voltage, that is, the highest voltage value that the cell can withstand. Above this voltage, the battery cell may be damaged. The maximum tolerance voltage is greater than the charge cut-off voltage.

[0039] Optionally, the equalization cutoff voltage is configured according to the charging cutoff voltage, wherein the equalization cutoff voltage is usually set to be slightly lower than the charging cutoff voltage to ensure sufficient passive equalization during the charging process and prevent the cell voltage from being greater than the equalization cutoff voltage after slow charging due to the voltage hysteresis characteristics of the cell. For example, if the charging cutoff voltage is 4.2V, the equalization cutoff voltage can be set to 4.1V.

[0040] Optionally, the equalization trigger voltage is configured based on the maximum tolerance voltage and the safety limit of the target battery pack. The equalization trigger voltage should be lower than the maximum tolerance voltage to ensure that the safe voltage range of the battery cell is not exceeded during the equalization process, thereby protecting the safety of the battery cell. Among them, the safety limit refers to the voltage buffer range reserved for the battery cell under different usage environments, which is determined in combination with factors such as the service life, operating temperature, and discharge rate of the battery cell. Exemplarily, the above safety is expressed as a fixed voltage value. If the maximum tolerance voltage is 4.3V and the safety limit is specified as 0.2V, the equalization trigger voltage can be set below 4.1V.

[0041] Furthermore, a balancing interval is configured with the balancing trigger voltage as the interval lower limit and the balancing cutoff voltage as the interval upper limit. The balancing interval defines that the balancing operation is performed when the cell voltage is within the interval to ensure that the cell voltage remains within a safe range and improve the overall performance and safety of the battery pack.

[0042] The adaptive matching module 13 is used to interactively obtain the temperature rise information of the target battery pack, and call the adaptive strategy to perform strategy allocation in combination with the battery cell temperature information, wherein the adaptive strategy includes a forward-looking balancing strategy and a triggered balancing strategy.

[0043] Optionally, the main function of the adaptive matching module 13 is to interactively obtain the temperature rise information of the target battery pack, and combine the cell temperature information to call the adaptive strategy for strategy allocation. The temperature rise information refers to the temperature change of the battery pack during the charging and discharging process, and the temperature rise information is obtained through the temperature monitoring record of the target battery.

[0044] Specifically, the adaptive strategies include forward-looking balancing strategies and triggered balancing strategies. The forward-looking balancing strategy predicts the temperature change trend and performs balancing operations in advance. It is suitable for charging management scenarios with high requirements on charging efficiency and rate, high computing power of the charging management system, large battery pack capacity, and high thermal management requirements. The triggered balancing strategy achieves battery cell balancing through a predetermined trigger mechanism. It does not require complex calculations and predictions. It is suitable for charging management scenarios with low computing power, small battery pack capacity, looser thermal management requirements, and low charging efficiency requirements.

[0045] By adaptively matching the corresponding balancing strategies for different applications, it helps to ensure efficient balancing of the battery pack under different temperature conditions.

[0046] In some embodiments, the temperature rise information of the target battery pack is interactively obtained, and combined with the battery cell temperature information, the adaptive strategy is called to perform strategy allocation, and the execution steps include:

[0047] A policy allocation constraint is configured, wherein the policy allocation constraint includes a temperature constraint and a temperature rise constraint.

[0048] A threshold determination is performed on the battery cell temperature information based on the temperature constraint to obtain a first determination result.

[0049] A threshold determination is performed on the temperature rise information based on the temperature rise constraint to obtain a second determination result.

[0050] If either the first judgment result or the second judgment result is not satisfied, the forward-looking balancing strategy is output as the adaptive strategy allocation result; if both the first judgment result and the second judgment result are satisfied, the triggered balancing strategy is output as the adaptive strategy allocation result.

[0051] Optionally, first, based on the control requirements of the target battery pack, define the policy allocation constraints, including temperature constraints and temperature rise constraints. The temperature constraint defines the temperature control limit of the battery cell or the battery cell environment. If the temperature of the battery cell or the battery cell environment is greater than or equal to the temperature constraint, it can be considered that the temperature level of the battery pack is high and thermal management or heat release regulation is required. The temperature rise constraint sets a safe range for the battery pack temperature change rate. If the temperature rise rate of the battery cell is greater than or equal to the temperature rise constraint, it means that the battery cell is heating up too fast and the heat generation rate needs to be controlled.

[0052] Optionally, the battery cell temperature information is obtained to determine whether it is within a preset temperature constraint range, and a first determination result is obtained; specifically, if the battery cell temperature information is within the temperature constraint range, the determination result is satisfied, otherwise it is deemed unsatisfied;

[0053] Optionally, the temperature rise information is obtained to determine whether it is within a preset temperature rise constraint range, and a second judgment result is obtained; specifically, if the temperature rise information is within the temperature rise constraint range, the judgment result is satisfied, otherwise it is deemed unsatisfied.

[0054] Specifically, the adaptive strategy is determined by combining the first discrimination result and the second discrimination result. If either the first discrimination result or the second discrimination result is not satisfied, the forward-looking balancing strategy is output as the adaptive strategy allocation result. The forward-looking balancing strategy performs balancing operations in advance, thereby dispersing the heat generated by the passive balancing and preventing the battery pack temperature or temperature rise from exceeding the safe range.

[0055] Specifically, the adaptive strategy is determined by combining the first and second discrimination results. If both the first and second discrimination results are satisfied, the triggered balancing strategy is output as the adaptive strategy allocation result. The triggered balancing strategy will perform balancing operations when the cell temperature and temperature rise are within a safe range. In this case, it means that the target battery pack has sufficient thermal management capacity and can bear higher discharge heat generation.

[0056] The management execution module 14 is used to perform intelligent management of the target battery group based on the adaptive strategy allocation result, according to the battery cell status information, and in combination with the balancing interval.

[0057] In some embodiments, based on the adaptive strategy allocation result, according to the cell state information, and in combination with the balancing interval, intelligent management of the target battery group is performed, and the execution steps include:

[0058] If the adaptive strategy allocation result is the triggered balancing strategy, a balancing trigger judgment is performed based on the cell voltage information and the balancing interval, and cells whose cell voltage is greater than the balancing trigger voltage are marked as cells to be balanced, to obtain a balancing target set.

[0059] Based on the balancing target set, the discharge MOSFET corresponding to the battery cell to be balanced is controlled to perform discharge control, wherein the discharge MOSFET is connected in series with a discharge resistor and then connected in parallel with the battery cell.

[0060] The cell voltage value of the target battery pack is continuously monitored and collected, and if the cell voltage value is less than the equalization cut-off voltage, the discharge MOSFET of the corresponding cell is disconnected.

[0061] Continuously monitor and collect multiple cells of the target battery pack to obtain updated cell status information, and perform iterative balancing trigger judgment based on the updated cell status information until the balancing target set is the full set of multiple cells of the target battery pack, then disconnect the charging MOSFET.

[0062] Optionally, if the adaptive strategy allocation result is a triggered balancing strategy, the balancing trigger judgment is performed based on the cell voltage information and the balancing interval, and the cells whose voltage is greater than the balancing trigger voltage are marked as cells to be balanced, and all cells to be balanced are stored as a balancing target set. In other words, cells whose cell voltage is greater than the balancing trigger voltage can be considered as cells that have been charged and need to be balanced by discharging to avoid overvoltage and damage to the cells or triggering OVP overvoltage protection.

[0063] Optionally, the cells to be balanced are discharged by controlling the on and off of the discharge MOSFET on the discharge circuit connected in parallel with the cells to be balanced, wherein each cell to be balanced corresponds to a discharge MOSFET, and the discharge MOSFET is connected in series with the discharge resistor and then connected in parallel with the cell. Exemplarily, the switching state of the discharge MOSFET is controlled by a PWM (pulse width modulation) signal to adjust the discharge power, achieve balanced discharge of the cells, and gradually reduce the cell voltage to a balanced state. The greater the voltage deviation of the cell and the higher the charging rate, the higher the duty cycle and the higher the discharge power.

[0064] Optionally, the cell voltage values ​​of the target battery pack are continuously monitored and collected. When the voltage value of a certain cell is less than the balancing trigger voltage, the discharge MOSFET of the corresponding cell is disconnected to stop the discharge operation. At this time, the cell will continue to charge as the charging MOSFET is turned on and off, and the cell voltage rises until the cell voltage is greater than the balancing trigger voltage again, and the above-mentioned discharge control is performed again.

[0065] Furthermore, the multiple cells of the target battery pack are continuously monitored and collected to obtain updated cell status information, and the balancing trigger is determined based on the updated cell status information, and the cells that need to be balanced are re-determined, and the discharge is iteratively controlled. Repeat the above steps until the balancing target set is the full set of multiple cells of the target battery pack, that is, all cells have reached a balanced state, then it can be considered that the target battery pack has reached a balanced state and charging is completed, disconnect the charging MOSFET of the main power supply circuit, and end the balancing process.

[0066] In some embodiments, based on the adaptive strategy allocation result, according to the cell state information, and in combination with the balancing interval, intelligent management of the target battery group is performed, and the execution step further includes:

[0067] If the adaptive strategy allocation result is the forward-looking balancing strategy, historical battery pack data is interactively acquired, where the historical battery pack data includes total capacity data and initial SOC data of a plurality of battery cells.

[0068] Based on the historical battery pack data and the cell status information, an estimated charging curve set is calculated and obtained.

[0069] Based on the battery cell specification data, a standard charging curve is extracted, and terminal correction is performed on the estimated charging curve set according to the standard charging curve to obtain a corrected charging curve set.

[0070] The modified charging curve set is traversed, and the end point of the modified charging curve with the lowest slope is used as the energy replenishment base point, and the discharge control parameters of the multiple battery cells are calculated and obtained, and the output is a forward-looking balancing parameter set.

[0071] Discharging of multiple discharge MOSFETs of multiple battery cells is controlled according to the forward-looking balancing parameter set until the energy replenishment base point is reached.

[0072] Optionally, historical battery pack data is stored in the management storage unit of the template battery pack, including total capacity data and initial SOC data of multiple cells, wherein the total capacity data refers to the total capacity of the latest calibrated cell that can be charged from the discharge cut-off voltage to the charge cut-off voltage. The initial SOC data refers to the current state of charge of the cell.

[0073] Optionally, based on historical battery pack data and cell status information, an estimated charging curve set is calculated. First, based on the total capacity data and initial SOC data in the historical battery pack data, the capacity of the battery cell to be charged is calculated, that is, the amount of electricity that needs to be charged to fully charge the battery cell; then, based on the cell voltage information and cell current information in the cell status information, the charging speed of the battery cell is calculated, and the charging speed is expressed as the amount of charge charged per unit time; then, based on the cell specification data, the corresponding standard charging curve is extracted, and the terminal correction is performed on the estimated charging curve set.

[0074] Specifically, the battery cell charging process is mostly a three-stage charging, including trickle charging (low-voltage pre-charging), constant current charging, and constant voltage charging. After the battery cell voltage reaches the preset voltage value, the constant current charging ends and the constant voltage charging stage begins. As the charging process continues, the charging current slowly decreases from the maximum value, and the charging speed gradually decreases. Therefore, it is necessary to correct the estimated charging curve that does not reduce the speed under ideal conditions.

[0075] Exemplary. Select the standard charging curve corresponding to the current charging rate (such as when the charging current is 0.3C), then intercept the standard charging curve based on the initial SOC data, and scale and stretch the intercepted standard charging curve segment, and fit the constant current charging stage in the standard charging curve segment with the constant current charging stage in the estimated charging curve by the least squares method. Finally, replace the end of the estimated curve with the end of the standard curve in the fitting result to obtain a corrected charging curve set.

[0076] Optionally, traverse the set of corrected charging curves to obtain the corrected charging curve with the lowest slope, which corresponds to the slowest charging cell in the target battery pack. Next, take the end point of the corrected charging curve with the lowest slope as the energy replenishment base point, which represents the time node when the overall charging of the battery pack is completed. Then, take the slowest charging cell as the target, and adjust the actual charging speed of other cells by changing the passively balanced discharge rate so that their charging speed matches that of the slowest cell. Finally, according to the required discharge rate, calculate the switching frequency and duty cycle of the PWM signal, obtain the discharge control parameters of multiple cells, and output them as a forward-looking balancing parameter set. Among them, the actual charging speed = charging speed - discharge rate, and the discharge control parameter is the switching frequency and duty cycle of the PWM signal of the discharge MOSFET corresponding to the passively balanced discharge rate.

[0077] Specifically, the slope of the constant current charging stage in the corrected charging curve is the actual charging speed of the battery cell. When the charging speed is constant, the actual charging speed of the battery cell can be changed by increasing or decreasing the passive balancing discharge rate, so that all cells are fully charged at the same time when the slowest cell is fully charged, thereby improving the balance and charging efficiency of the battery pack.

[0078] Through the above steps, intelligent management of battery packs based on forward-looking balancing strategies can be achieved to ensure that all cells are fully charged at the same time when the slowest charging cell is fully charged. The forward-looking balancing strategy has the technical effect of making the discharge heat generation during passive balancing more gentle, thereby reducing the battery pack temperature and the difficulty of temperature management, thereby increasing the battery pack life and charging speed.

[0079] Specifically, by accurately calculating and controlling the discharge process, the discharge heat generation can be more uniform and gentle, avoiding excessive heat generation in the battery cell during the discharge process, making the temperature distribution of the entire battery pack more uniform, thereby reducing local overheating of the battery cell and effectively reducing the aging rate of the battery cell.

[0080] In addition, the forward-looking equalization strategy also helps reduce the burden on the temperature management system and reduces the dependence on the cooling system, thereby simplifying the design and control of temperature management. At the same time, at a lower and more stable temperature, the battery pack can withstand a higher charging current without damaging the battery cells, which helps to increase the charging speed and reduce the charging time.

[0081] In some implementations, the intelligent management of the target battery pack is performed, and the execution step further includes:

[0082] Based on the battery cell status information, the real-time operating condition of the target battery pack is determined.

[0083] If the real-time operating condition is charging the target battery pack, a charging operation fault is identified based on the fault identifier. If the charging operation fault identification result is that a charging fault exists, the charging MOSFET is turned off. If there is no charging fault, the fault identifier that only appears in the discharge operation state is cleared and the charging MOSFET is turned on.

[0084] If the real-time operating condition is the discharge of the target battery pack, a discharge operation fault is identified based on the fault identifier. If the discharge operation fault identification result is that a discharge fault exists, the discharge MOSFET is turned off. If there is no discharge fault, the fault identifier that only appears in the charging operation state is cleared and the discharge MOSFET is turned on.

[0085] Optionally, the above-mentioned fault identification includes a charging fault identification and a discharging fault identification. Exemplarily, the charging fault identification includes overvoltage, equalization, overtemperature, and overcurrent, and the discharging fault identification includes undervoltage, low SOC, overtemperature, and overcurrent. Among them, the overcurrent in the charging fault identification is opposite to the overcurrent in the discharging fault identification, that is, the positive and negative current values ​​indicate the current direction, that is, the charging and discharging state.

[0086] Optionally, the real-time operating condition of the target battery pack includes a charging condition and a discharging condition.

[0087] Optionally, if the real-time working condition is charging the target battery pack: perform charging operation fault identification based on the fault identification, and if the charging operation fault identification result is that there is a charging fault, turn off the charging MOSFET and stop the charging operation. If the charging operation fault identification result is that there is no charging fault, clear the fault identification that only appears in the discharge operation state to avoid erroneous fault identification, turn on the charging MOSFET, and continue the charging operation.

[0088] Optionally, if the real-time operating condition is the target battery pack discharge: perform a discharge operation fault determination based on the fault identifier, and if the discharge operation fault determination result is that there is a discharge fault, turn off the discharge MOSFET and stop the discharge operation to facilitate fault diagnosis and disposal. Correspondingly, if the discharge operation fault determination result is that there is no discharge fault, clear the fault identifier that only appears in the charging operation state, turn on the discharge MOSFET, and continue the discharge operation.

[0089] Through the above-mentioned working condition identification and fault handling steps, the charging and discharging conditions of the battery pack can be monitored in real time, and the corresponding MOSFET can be turned off in time when a fault occurs, avoiding damage to the battery pack caused by continued operation of the fault. At the same time, it helps to detect and handle the fault in time to avoid safety accidents. By clearing unnecessary fault identifiers, it ensures that the system does not accidentally trigger the fault handling mechanism under normal operating conditions, thereby improving system operation efficiency.

[0090] In some implementations, the system further includes:

[0091] If the balance target set is an empty set, the duty cycle of the charging MOSFET is increased to improve the charging speed.

[0092] If the balance target set is not an empty set, the duty cycle of the charging MOSFET is reduced to reduce the charging speed.

[0093] Optionally, if the target set for balancing is an empty set, it means that there are no fully charged cells in the target battery pack, that is, the voltages of all cells are not in the balancing range, and no balancing operation is required. Then, the duty cycle is increased to increase the charging current, thereby speeding up the charging speed.

[0094] Optionally, if the balancing target set is not an empty set, it means that at this time, the voltage of some cells is in the balancing range and needs to be balanced. Then the duty cycle of the charging MOSFET is reduced accordingly, and the charging current is reduced by reducing the duty cycle, thereby slowing down the charging speed and avoiding the aggravation of the imbalance between the cells.

[0095] Optionally, based on the maximum discharge rate of the discharge resistor or discharge circuit connected in parallel with the battery cell, the upper limit of the duty cycle of the charging MOSFET is calculated. The upper limit of the duty cycle of the charging MOSFET is used to control the charging rate to be no greater than the maximum discharge rate of the passive balancing circuit, thereby ensuring the effective implementation of passive balancing.

[0096] The above method steps adjust the duty cycle of the charging MOSFET according to the state of the balancing target set to speed up the charging speed when balancing is not required and slow down the charging speed when balancing is required, giving more time to the balancing process, which helps to more efficiently achieve voltage balancing between battery cells, thereby realizing dynamic optimization of the charging process.

[0097] In summary, the intelligent battery management system based on passive balancing provided by the present invention has the following technical effects:

[0098] The cell status information of the target battery pack is acquired through real-time collection, wherein the cell status information includes cell voltage information, cell current information, and cell temperature information; the cell characteristic data of the target battery pack is acquired, and according to the cell characteristic data, the balancing interval is configured, including the balancing trigger voltage and the balancing cutoff voltage; the temperature rise information of the target battery pack is acquired interactively, and combined with the cell temperature information, the adaptive strategy is called for strategy allocation, wherein the adaptive strategy includes a forward-looking balancing strategy and a trigger balancing strategy; based on the adaptive strategy allocation result, according to the cell status information, combined with the balancing interval, the target battery pack is intelligently managed to achieve smooth passive balanced heat generation and reduce the difficulty of heat control.

[0099] Embodiment 2

[0100] Figure 2 FIG. 1 is a flow chart of the intelligent battery management method based on passive balancing of the present invention. Figure 2 The intelligent battery management method based on passive balancing shown in the figure can be applied to Figure 1 The structure of the intelligent battery management system based on passive balancing.

[0101] Based on the same concept as the intelligent battery management system based on passive balancing in the above embodiment, the present invention also provides an intelligent battery management method based on passive balancing, which includes:

[0102] The battery cell status information of the target battery pack is acquired in real time, wherein the battery cell status information includes battery cell voltage information, battery cell current information, and battery cell temperature information.

[0103] The cell characteristic data of the target battery pack is obtained, and according to the cell characteristic data, a balancing interval is configured, including a balancing trigger voltage and a balancing cutoff voltage.

[0104] The temperature rise information of the target battery pack is interactively acquired, and combined with the battery cell temperature information, an adaptive strategy is called to perform strategy allocation, wherein the adaptive strategy includes a forward-looking balancing strategy and a triggered balancing strategy.

[0105] Based on the adaptive strategy allocation result, the target battery group is intelligently managed according to the cell status information and the balancing interval.

[0106] The step of acquiring the cell characteristic data of the target battery pack and configuring the balancing interval according to the cell characteristic data includes:

[0107] Obtain cell specification data of the target battery pack, and extract cell characteristic data, wherein the cell characteristic data at least includes a discharge cut-off voltage, a charge cut-off voltage, and a maximum tolerance voltage.

[0108] The equalization cut-off voltage is configured according to the charging cut-off voltage.

[0109] Based on the maximum tolerance voltage and in combination with the safety limit of the target battery pack, the equalization trigger voltage is configured, wherein the equalization trigger voltage is less than the maximum tolerance voltage.

[0110] The balancing interval is configured with the balancing trigger voltage as the upper limit of the interval and the balancing cut-off voltage as the lower limit of the interval.

[0111] Furthermore, based on the adaptive strategy allocation result, according to the cell state information, combined with the balancing interval, intelligent management of the target battery group is performed, including:

[0112] If the adaptive strategy allocation result is the triggered balancing strategy, a balancing trigger judgment is performed based on the cell voltage information and the balancing interval, and cells whose cell voltage is greater than the balancing trigger voltage are marked as cells to be balanced, to obtain a balancing target set.

[0113] Based on the balancing target set, the discharge MOSFET corresponding to the battery cell to be balanced is controlled to perform discharge control, wherein the discharge MOSFET is connected in series with a discharge resistor and then connected in parallel with the battery cell.

[0114] The cell voltage value of the target battery pack is continuously monitored and collected, and if the cell voltage value is less than the equalization cut-off voltage, the discharge MOSFET of the corresponding cell is disconnected.

[0115] Continuously monitor and collect multiple cells of the target battery pack to obtain updated cell status information, and perform iterative balancing trigger judgment based on the updated cell status information until the balancing target set is the full set of multiple cells of the target battery pack, then disconnect the charging MOSFET.

[0116] Furthermore, based on the adaptive strategy allocation result, according to the cell state information, combined with the balancing interval, intelligent management of the target battery group is performed, which also includes:

[0117] If the adaptive strategy allocation result is the forward-looking balancing strategy, historical battery pack data is interactively acquired, where the historical battery pack data includes total capacity data and initial SOC data of a plurality of battery cells.

[0118] Based on the historical battery pack data and the cell status information, an estimated charging curve set is calculated and obtained.

[0119] Based on the battery cell specification data, a standard charging curve is extracted, and terminal correction is performed on the estimated charging curve set according to the standard charging curve to obtain a corrected charging curve set.

[0120] The modified charging curve set is traversed, and the end point of the modified charging curve with the lowest slope is used as the energy replenishment base point, and the discharge control parameters of the multiple battery cells are calculated and obtained, and the output is a forward-looking balancing parameter set.

[0121] Discharging of multiple discharge MOSFETs of multiple battery cells is controlled according to the forward-looking balancing parameter set until the energy replenishment base point is reached.

[0122] Furthermore, the temperature rise information of the target battery pack is interactively obtained, and combined with the battery cell temperature information, the adaptive strategy is called to perform strategy allocation, and the execution steps include:

[0123] A policy allocation constraint is configured, wherein the policy allocation constraint includes a temperature constraint and a temperature rise constraint.

[0124] A threshold determination is performed on the battery cell temperature information based on the temperature constraint to obtain a first determination result.

[0125] A threshold determination is performed on the temperature rise information based on the temperature rise constraint to obtain a second determination result.

[0126] If either the first judgment result or the second judgment result is not satisfied, the forward-looking balancing strategy is output as the adaptive strategy allocation result; if both the first judgment result and the second judgment result are satisfied, the triggered balancing strategy is output as the adaptive strategy allocation result.

[0127] Furthermore, the intelligent management of the target battery pack is performed, and the execution steps of the method further include:

[0128] Based on the battery cell status information, the real-time operating condition of the target battery pack is determined.

[0129] If the real-time operating condition is charging the target battery pack, a charging operation fault is identified based on the fault identifier. If the charging operation fault identification result is that a charging fault exists, the charging MOSFET is turned off. If there is no charging fault, the fault identifier that only appears in the discharge operation state is cleared and the charging MOSFET is turned on.

[0130] If the real-time operating condition is the discharge of the target battery pack, a discharge operation fault is identified based on the fault identifier. If the discharge operation fault identification result is that a discharge fault exists, the discharge MOSFET is turned off. If there is no discharge fault, the fault identifier that only appears in the charging operation state is cleared and the discharge MOSFET is turned on.

[0131] Furthermore, the execution step of the method further includes:

[0132] If the balance target set is an empty set, the duty cycle of the charging MOSFET is increased to improve the charging speed.

[0133] If the balance target set is not an empty set, the duty cycle of the charging MOSFET is reduced to reduce the charging speed.

[0134] It should be understood that the embodiments mentioned in this specification focus on their differences from other embodiments. The specific embodiments in the aforementioned embodiment one are also applicable to the intelligent battery management method based on passive balancing described in embodiment two. For the sake of brevity of the specification, they will not be further elaborated here.

[0135] It should be understood that the embodiments disclosed in the present invention and the above description can enable those skilled in the art to use the present invention to implement the present invention. At the same time, the present invention is not limited to the above-mentioned embodiments. It should be understood that those skilled in the art can still modify the technical solutions recorded in the above-mentioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. Intelligent battery management system based on passive balancing, characterized in that: The system comprises: An information sensing module, the information sensing module is used to collect and obtain the battery cell status information of the target battery pack in real time, wherein the battery cell status information includes battery cell voltage information, battery cell current information, and battery cell temperature information; A trigger constraint module, the trigger constraint module is used to obtain the cell characteristic data of the target battery pack, and configure the balancing interval according to the cell characteristic data, including the balancing trigger voltage and the balancing cutoff voltage; An adaptive matching module, the adaptive matching module is used to interactively obtain the temperature rise information of the target battery pack, and combine the battery cell temperature information to call the adaptive strategy for strategy allocation, wherein the adaptive strategy includes a forward-looking balancing strategy and a triggered balancing strategy. The forward-looking balancing strategy is to perform balancing operations in advance according to the temperature change trend prediction, and the triggered balancing strategy is to achieve battery cell balancing through a predetermined trigger mechanism; A management execution module, the management execution module is used to perform intelligent management of the target battery group based on the adaptive strategy allocation result, according to the battery cell state information, and in combination with the balancing interval; Interactively obtain the temperature rise information of the target battery pack, and combine the battery cell temperature information to call the adaptive strategy for strategy allocation. The execution steps include: Configure a policy allocation constraint, wherein the policy allocation constraint includes a temperature constraint and a temperature rise constraint; Performing a threshold determination on the battery cell temperature information based on the temperature constraint to obtain a first determination result; Performing a threshold determination on the temperature rise information based on the temperature rise constraint to obtain a second determination result; If either the first judgment result or the second judgment result is not satisfied, the forward-looking balancing strategy is output as the adaptive strategy allocation result; if both the first judgment result and the second judgment result are satisfied, the triggered balancing strategy is output as the adaptive strategy allocation result.

2. The intelligent battery management system based on passive balancing according to claim 1, characterized in that: Acquiring the cell characteristic data of the target battery pack and configuring the balancing interval according to the cell characteristic data, the execution steps include: Obtaining cell specification data of a target battery pack and extracting cell characteristic data, wherein the cell characteristic data at least includes a discharge cut-off voltage, a charge cut-off voltage, and a maximum tolerance voltage; According to the charging cut-off voltage, configuring the equalization cut-off voltage; Based on the maximum tolerance voltage and in combination with the safety limit of the target battery pack, the equalization trigger voltage is configured, wherein the equalization trigger voltage is less than the maximum tolerance voltage; The balancing interval is configured with the balancing trigger voltage as the upper limit of the interval and the balancing cut-off voltage as the lower limit of the interval.

3. The intelligent battery management system based on passive balancing as claimed in claim 2, characterized in that: Based on the adaptive strategy allocation result, according to the cell status information and in combination with the balancing interval, intelligent management of the target battery group is performed, and the execution steps include: If the adaptive strategy allocation result is the triggered balancing strategy, a balancing trigger judgment is performed based on the cell voltage information and in combination with the balancing interval, and the cell whose voltage is greater than the balancing trigger voltage is marked as a cell to be balanced, and a balancing target set is obtained; Based on the balancing target set, controlling the discharge MOSFET corresponding to the battery cell to be balanced to perform discharge control, wherein the discharge MOSFET is connected in series with a discharge resistor and then connected in parallel with the battery cell; Continuously monitoring and collecting the cell voltage value of the target battery pack, if the cell voltage value is less than the equalization cut-off voltage, disconnecting the discharge MOSFET of the corresponding cell; Continuously monitor and collect multiple cells of the target battery pack to obtain updated cell status information, and perform iterative balancing trigger judgment based on the updated cell status information until the balancing target set is the full set of multiple cells of the target battery pack, then disconnect the charging MOSFET.

4. The intelligent battery management system based on passive balancing as claimed in claim 3, characterized in that: Based on the adaptive strategy allocation result, according to the cell state information and in combination with the balancing interval, intelligent management of the target battery group is performed, and the execution step further includes: If the adaptive strategy allocation result is the forward-looking balancing strategy, interactively acquiring historical battery pack data, the historical battery pack data including total capacity data and initial SOC data of multiple battery cells; Based on the historical battery pack data and the battery cell status information, calculating and obtaining an estimated charging curve set; Based on the battery cell specification data, a standard charging curve is extracted, and terminal correction is performed on the estimated charging curve set according to the standard charging curve to obtain a corrected charging curve set; Traversing the set of corrected charging curves, taking the end point of the corrected charging curve with the lowest slope as the energy replenishment base point, calculating and obtaining discharge control parameters of multiple battery cells, and outputting them as a forward-looking balancing parameter set; Discharging of multiple discharge MOSFETs of multiple battery cells is controlled according to the forward-looking balancing parameter set until the energy replenishment base point is reached.

5. The intelligent battery management system based on passive balancing according to claim 1, characterized in that: The intelligent management of the target battery pack includes the following steps: Based on the battery cell status information, determining the real-time operating condition of the target battery pack; If the real-time operating condition is charging of the target battery pack, a charging operation fault is identified based on the fault identifier. If the charging operation fault identification result is that a charging fault exists, the charging MOSFET is turned off. If there is no charging fault, the fault identifier that only appears in the discharge operation state is cleared, and the charging MOSFET is turned on. If the real-time operating condition is the discharge of the target battery pack, a discharge operation fault is identified based on the fault identifier. If the discharge operation fault identification result is that a discharge fault exists, the discharge MOSFET is turned off. If there is no discharge fault, the fault identifier that only appears in the charging operation state is cleared and the discharge MOSFET is turned on.

6. The intelligent battery management system based on passive balancing as claimed in claim 3, characterized in that: The execution steps of the system also include: If the balancing target set is an empty set, increasing the duty cycle of the charging MOSFET to improve the charging speed; If the balance target set is not an empty set, the duty cycle of the charging MOSFET is reduced to reduce the charging speed.

7. An intelligent battery management method based on passive balancing, characterized in that: The method is applied to the intelligent battery management system based on passive balancing according to any one of claims 1 to 6, and the method comprises: Real-time acquisition of battery cell status information of the target battery pack, wherein the battery cell status information includes battery cell voltage information, battery cell current information, and battery cell temperature information; Acquire cell characteristic data of the target battery pack, and configure a balancing interval according to the cell characteristic data, including a balancing trigger voltage and a balancing cutoff voltage; Interactively obtain the temperature rise information of the target battery pack, and combine the battery cell temperature information to call the adaptive strategy for strategy allocation, wherein the adaptive strategy includes a forward-looking balancing strategy and a triggered balancing strategy. The forward-looking balancing strategy is to perform balancing operations in advance according to the temperature change trend prediction, and the triggered balancing strategy is to achieve battery cell balancing through a predetermined trigger mechanism; Based on the adaptive strategy allocation result, according to the cell state information and in combination with the balancing interval, intelligent management of the target battery group is performed.

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