Method and system for estimating state of charge of battery

Abstract

The invention provides a method and a system for estimating the state of charge of a battery. The method for estimating the state of charge of a battery comprises the following steps: calculating a voltage difference (delta V) from a battery voltage (VBAT) and an open circuit voltage (OCV) by a battery voltameter; adaptively adjusting a gain (K) by a gain control engine according to a battery current (IBAT) and a full charge capacity (FCC); the battery voltameter generates a current charge variation (delta SOCT) according to the voltage difference (delta V) and the adjusted gain; and generating a next time state of charge (SOCT + 1) by an accumulator according to a current state of charge (SOCT) and the current charge variation (delta SOCT).

Description

Technical Field

[0001] The present invention relates to a method and system for estimating the state of charge of a battery, and in particular to a method and system for estimating the state of charge of a battery capable of adaptively adjusting gain. Background Art

[0002] For users of portable electronic devices, the state of charge (SOC) is essential information. For a fully charged battery, the SOC is displayed as 100%. For a fully discharged battery, the SOC is displayed as 0%. It is urgent to use algorithms embedded in portable electronic devices to estimate the SOC. The existing technology often uses a current coulomb integrator to progressively calculate the capacity of the battery charging or discharging, and then calculates the battery's SOC by combining it with the total battery capacity. However, the current coulomb integrator will produce cumulative errors due to inaccurate design or external noise, thereby estimating an inaccurate battery SOC.

[0003] In the battery management systems currently on the market, pure voltage-based battery fuel gauges (Voltaic Gauge) measure the battery voltage and estimate the battery SOC based on the corresponding relationship between the voltage and the battery state of charge (SOC). The advantage of this method is that it is simple and easy to use, and can refer to the open circuit voltage (OCV) curve to achieve stable SOC convergence and avoid divergence.

[0004] However, pure voltage-based battery fuel gauges also have some obvious disadvantages listed below:

[0005] First, the SOC trend is wrong when the current changes dramatically: when the direction of charging and discharging remains unchanged, but the current changes dramatically, the pure voltage battery fuel gauge may provide an incorrect SOC trend and cannot correctly reflect the actual state of charge of the battery.

[0006] Second, the SOC change rate is inaccurate under different environmental conditions: Under different loads, different temperatures, different battery capacities or different degrees of aging, a pure voltage-based fuel gauge may cause an inaccurate SOC change rate and cannot reliably estimate the actual state of the battery.

[0007] Third, it cannot effectively cope with changing operating environments: Although pure voltage-type battery fuel gauges have the advantage of relying on the OCV curve for stable convergence, they cannot fully cope with changes in different loads, temperatures, battery capacities, and aging levels, and cannot provide sufficient compensation to ensure the accuracy of SOC.

[0008] Therefore, existing pure voltage-based battery fuel gauges may produce inaccurate SOC estimation results under certain extreme conditions, which makes it necessary to improve such technologies to solve the above problems.

[0009] In view of this, the present invention aims at addressing the above-mentioned deficiencies in the prior art and proposes a method and system for estimating the state of charge of a battery with adaptively adjustable gain. Summary of the invention

[0010] From one viewpoint, the present invention provides a method for estimating the state of charge (SOC) of a battery, comprising: (a) using a battery fuel gauge (Voltaic Gauge) to calculate a voltage difference (ΔV) based on a battery voltage (VBAT) and an open circuit voltage (OCV); (b) using a gain control engine (Gain Control Engine) to adaptively adjust a gain based on a battery current and a full charge capacity (FCC); (c) the battery fuel gauge generates a current charge change (ΔSOC_T) based on the voltage difference (ΔV) and the adjusted gain; and (d) using an accumulator to generate a next moment state of charge (SOC_T+1) based on the current state of charge (SOC_T) and the current charge change (ΔSOC_T).

[0011] In a preferred implementation, the step (b) further includes: the gain control engine adaptively adjusting the gain according to the gain (K) and the voltage difference (ΔV) before adjustment.

[0012] In a preferred implementation, the step (a), the step (b), the step (c) and the step (d) are performed sequentially, and after the step (d), the charge state at the next moment is used as the current charge state and the process returns to the step (a).

[0013] In a preferred embodiment, in step (b), the gain control engine adjusts the gain by increasing or decreasing a fixed gain difference.

[0014] In a preferred implementation, in the step (b), the gain control engine further adjusts the gain according to a current difference between a battery current (IBAT_T-1) at a previous moment and the battery current (IBAT).

[0015] In a preferred embodiment, in step (b), when the voltage difference does not exceed a preset voltage difference or the battery current does not exceed a preset current, it is defined as a light load condition, and the gain control engine adjusts and maintains the gain as a fixed light load gain.

[0016] In a preferred embodiment, the step (b) includes: using the gain control engine to compare a charge change amount (ΔSOC_T-1) at a previous moment with a change amount target value (ΔSOCI), and adaptively adjusting the gain, wherein the change amount target value is related to the battery current and the full charge capacity (FCC).

[0017] In a preferred embodiment, the full charged capacity (FCC) is related to a load condition, a battery temperature and / or a battery aging degree.

[0018] In a preferred embodiment, the step of generating a charge change according to the voltage difference and the gain includes: estimating a weight according to the battery voltage using a voltage weight model, wherein the voltage weight model is a first preset relationship between the battery voltage and the weight in battery information collected during charging, discharging and relaxing of the battery; estimating a fuzzy pressure difference according to the voltage difference using a pressure difference model, wherein the pressure difference model is a second preset relationship between the voltage difference and the fuzzy pressure difference; and generating the charge change according to the weight, the fuzzy pressure difference and the gain.

[0019] In a preferred embodiment, the method for estimating the state of charge of a battery further includes: collecting the battery information under different charge / discharge currents before generating the state of charge at a next moment.

[0020] In a preferred embodiment, the method for estimating the state of charge of a battery further comprises: establishing the voltage weight model and the voltage difference model by estimating the state of charge and the battery voltage under different charge / discharge currents.

[0021] In a preferred embodiment, the method for estimating the state of charge of a battery further comprises: calculating the weight according to the difference between the battery voltage at the charge / discharge current and at different charge / discharge currents to establish the voltage weight model.

[0022] In a preferred embodiment, the method for estimating the state of charge of a battery further includes: calculating the fuzzy pressure difference according to the charge / discharge current to establish the pressure difference model.

[0023] In a preferred implementation, the method for estimating the state of charge of a battery further includes: according to the state of charge, querying a preset state of charge and open circuit voltage relationship table to generate the open circuit voltage.

[0024] From another perspective, the present invention provides a system for estimating the state of charge of a battery, comprising: a battery fuel gauge (Voltaic Gauge), used to calculate a voltage difference (ΔV) according to a battery voltage (VBAT) and an open circuit voltage (OCV); a gain control engine (Gain Control Engine), used to adaptively adjust a gain according to a battery current (IBAT) and a full charge capacity (FCC); and an accumulator, used to generate a state of charge at a next moment (SOC_T+1) according to a current state of charge (SOC_T) and a current charge change (ΔSOC_T); wherein the battery fuel gauge generates the current charge change (ΔSOC_T) according to the voltage difference (ΔV) and the adjusted gain.

[0025] In a preferred implementation, the gain control engine also adaptively adjusts the gain according to the gain (K) and the voltage difference (ΔV) before adjustment.

[0026] In a preferred embodiment, the gain control engine adjusts the gain in an iterative manner by increasing or decreasing a fixed gain difference.

[0027] In a preferred implementation, the gain control engine further adjusts the fixed gain difference according to a current difference between a battery current (IBAT_T-1) at a previous moment and the battery current (IBAT).

[0028] In a preferred embodiment, the gain control engine defines a light load condition when the voltage difference does not exceed a preset voltage difference or the battery current does not exceed a preset current, and the gain control engine adjusts and maintains the gain to a fixed light load gain.

[0029] In a preferred embodiment, the gain control engine compares the charge variation with a variation target value and adaptively adjusts the gain, wherein the variation target value is related to a reference battery current and a full charge capacity (FCC).

[0030] In a preferred embodiment, the battery fuel gauge includes: a weighted fuzzifier for estimating a weight based on the battery voltage using a voltage weight model, wherein the voltage weight model is a first preset relationship between the battery voltage and the weight in battery information collected during charging, discharging and relaxing of the battery; a pressure difference fuzzifier for estimating a fuzzy pressure difference based on the voltage difference using a pressure difference model, wherein the pressure difference model is a second preset relationship between the voltage difference and the fuzzy pressure difference; a multiplier for performing a multiplication operation on the weight and the fuzzy pressure difference to obtain the product of the weight and the fuzzy pressure difference; and a compensator for compensating or calibrating the product of the weight and the fuzzy pressure difference based on the gain to generate the charge change.

[0031] In a preferred implementation, the weighted fuzzifier and the voltage difference fuzzifier establish the voltage weight model and the voltage difference model according to the corresponding different states of charge and different battery voltages under different charge / discharge currents.

[0032] In a preferred implementation, the weighted fuzzifier calculates the weight according to the difference between the battery voltages at different charging / discharging currents to establish the voltage weight model.

[0033] In a preferred implementation, the voltage difference fuzzifier calculates the fuzzy voltage difference according to the difference between the voltage differences at different charge / discharge currents to establish the voltage difference model.

[0034] In a preferred embodiment, the battery fuel gauge further includes a table lookup device for looking up a preset state of charge and open circuit voltage relationship table according to the state of charge to generate the open circuit voltage.

[0035] In a preferred embodiment, the gain control engine further compensates the gain based on a full charge capacity (FCC), a battery temperature (TBAT) and / or a battery aging degree.

[0036] In a preferred implementation, the accumulator accumulates at least one previous charge change amount by means of an inverse Z transformation of the charge state to generate the current charge state.

[0037] The present invention is superior to the prior art in at least the following aspects:

[0038] 1. Under charging and discharging conditions, the present invention can provide the correct state of charge even when the charge / discharge current varies drastically.

[0039] 2. Compared with the prior art, the present invention provides a more accurate state of charge (SOC) under different battery loads, different battery temperatures, different battery capacities and / or different battery aging levels.

[0040] 3. Compared with the prior art, the present invention has better response under extreme current conditions.

[0041] 4. Compared with the prior art, the present invention provides a simpler and more convenient method to adjust the gain according to the test results to improve the accuracy of the state of charge (SOC).

[0042] The following is a detailed description through specific embodiments to make it easier to understand the purpose, technical content, characteristics and effects achieved by the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A hardware block diagram of a system for estimating the state of charge of a battery according to an embodiment of the present invention is shown.

[0044] Figure 2A A schematic diagram showing the relationship between battery current IBAT and time.

[0045] Figure 2B A schematic diagram showing the relationship between battery voltage VBAT, open circuit voltage OCV and time.

[0046] Figure 3 A block diagram of a hardware system for estimating the state of charge of a battery according to another embodiment of the present invention is shown.

[0047] Figure 4 A hardware block diagram of a system for estimating the state of charge of a battery according to an embodiment of the present invention is shown.

[0048] Figure 5A and Figure 5B A schematic diagram showing the correlation results of the weighted fuzzifier 111 and the pressure difference fuzzifier 112 in the algorithm for estimating the state of charge of the battery.

[0049] Figure 6 An embodiment of a portion of the modeling of the differential pressure fuzzifier 112 is shown.

[0050] Figure 7 Display as Figure 4 Another embodiment of a model establishment of another part of the pressure difference fuzzifier 112 is shown.

[0051] Figure 8 Display as Figure 4 An embodiment of the modeling of the differential pressure fuzzifier 112 is shown.

[0052] Fig. 9 Display as Figure 4 An embodiment of model building of the weighted fuzzifier 111 is shown.

[0053] Fig.10 A hardware block diagram and data table are shown for a system for estimating the state of charge of a battery according to an embodiment of the present invention.

[0054] Fig.11 The experimental results obtained after applying the algorithm described in one embodiment of the present invention to the least mean square optimization are shown.

[0055] Fig.12 Shown in Figure 4 In the illustrated embodiment, experimental results obtained by estimating the state of charge of a battery using the system 100 for estimating the state of charge of a battery are shown.

[0056] Fig.13 A flow chart of a method for estimating the state of charge of a battery according to an embodiment of the present invention is shown.

[0057] Explanation of symbols in the figure

[0058] 100: System for estimating the state of charge of a battery

[0059] 110: Battery Fuel Gauge

[0060] 111: Weighted Fuzzer

[0061] 112: Pressure difference fuzzer

[0062] 113: Multiplier

[0063] 114: Compensator

[0064] 115: Optimizer

[0065] 116: Table Lookup

[0066] 117: Subtractor

[0067] 120: Gain Control Engine

[0068] 130: Accumulator

[0069] 310, 320, 410, 420, 610, 620: Table

[0070] 330, 430, 630: curve chart

[0071] 340, 440: Normalized curve graph

[0072] 510: Pressure difference model, combined with graph 340 and graph 440

[0073] 640: Voltage Weight Model Curve

[0074] 710: Data Sheet

[0075] 810: Algorithm, similar to system 100 for estimating battery state of charge

[0076] 812: Least Mean Square Optimization Function Block

[0077] 816: optimizer, connected to the least mean square optimization function block 812

[0078] 820: A curve diagram showing the battery voltage VBAT corresponding to the algorithm 810

[0079] 830: curve diagram showing the state of charge SOC corresponding to algorithm 810

[0080] 910: Graph showing the error in state of charge (SOC) at a standard charge / discharge rate of 0.5C

[0081] 920: Graph showing the error in state of charge (SOC) at a standard charge / discharge rate of 0.25C

[0082] 930: Graph showing the error in SOC at a partial charge / discharge rate of 0.5C

[0083] 1000: Method, method for estimating battery state of charge

[0084] 1002, 1004, 1006, 1008: Steps

[0085] AGS: Battery aging

[0086] FCC: Full Charge Capacity

[0087] IBAT: Battery current

[0088] IBATth: preset current

[0089] K: Gain

[0090] OCV: Open Circuit Voltage

[0091] SOC: State of Charge

[0092] SOC_T: Current state of charge

[0093] SOC_T+1: state of charge at the next moment

[0094] TBAT: Battery temperature

[0095] VBAT: Battery voltage

[0096] ΔV: Voltage difference

[0097] ΔSOC_T: Current charge change

[0098] W: Weight

[0099] fΔV: Fuzzy pressure difference

[0100] WfΔV: product of weight and fuzzy pressure difference

[0101] Z-1: inverse Z transformation DETAILED DESCRIPTION

[0102] The drawings in the present invention are all schematic, and are mainly intended to show the coupling relationship between various circuits and the relationship between various signal waveforms. The circuits, signal waveforms and frequencies are not drawn according to scale.

[0103] The present invention relates to a method and system for estimating the state of charge (SOC) of a battery when the battery is in at least one of the following states: charging, discharging and relaxing. The present invention is a method and system for estimating the state of charge (SOC) of a battery using a battery voltage (VBAT) and a battery current (IBAT).

[0104] Figure 1 A hardware system block diagram for estimating the state of charge of a battery according to an embodiment of the present invention is shown. Figure 1 As shown, the present embodiment provides a system 100 for estimating the state of charge of a battery. The system 100 for estimating the state of charge of a battery includes a battery fuel gauge 110, a gain control engine 120, and an accumulator 130. The battery fuel gauge 110 is used to calculate the voltage difference ΔV according to the battery voltage VBAT and the open circuit voltage OCV. The gain control engine 120 is used to adaptively adjust the gain K according to the battery current IBAT and the full charge capacity FCC, and provide it to the battery fuel gauge 110. The battery fuel gauge 110 generates a current charge change ΔSOC_T according to the voltage difference ΔV and the adjusted gain K. The accumulator 130 is used to generate the next state of charge SOC_T+1 according to the current state of charge SOC_T and the current charge change ΔSOC_T.

[0105] According to the present invention, the open circuit voltage OCV, the voltage difference ΔV, the battery voltage VBAT, and the current state of charge SOC_T are iteratively calculated, and the gain K is compensated by the gain control engine 120 to generate the current state of charge change ΔSOC_T.

[0106] Different from the traditional method based solely on voltage, the prior art directly uses the battery voltage VBAT and the open circuit voltage OCV to generate the next state of charge SOC_T+1, which easily leads to a sudden jump in the state of charge. The voltage and current compensation gain combined with the sensing architecture of the present invention can effectively prevent such sudden jumps and maintain the stability of the state of charge through a more stable architecture.

[0107] One of the advantages of the present invention is that it avoids the sudden change of state of charge caused by the traditional pure voltage algorithm, achieves a smoother and more stable state of charge estimation, and performs precise compensation through the gain control engine to adapt to different operating conditions.

[0108] In one embodiment, the gain control engine 120 adaptively adjusts the gain based on, in addition to the battery current IBAT and the full charge capacity FCC, a comparison of the gain K and the voltage difference ΔV before adjustment, such as but not limited to the product.

[0109] In one embodiment, the gain control engine 120 adjusts the gain K by increasing or decreasing a fixed gain difference in an iterative manner. For example, in the case of executing a procedure for estimating the state of charge of the battery once per cycle, that is, there is a cycle between the previous moment, the current moment, and the next moment. In each cycle, the gain control engine 120 increases or decreases the gain K before adjustment by a fixed gain difference according to the battery current IBAT and the full charge capacity FCC, or further according to the gain K before adjustment (the gain K before adjustment is defined as the gain K at the previous moment, and the gain K after adjustment is the current gain K) and the voltage difference ΔV to generate the current gain K, and repeats multiple cycles to continuously adjust the gain K, so as to dynamically maintain the adjusted gain K.

[0110] In one embodiment, the gain control engine 120 further adjusts the gain according to the current difference between the battery current IBAT_T-1 at the last moment and the current battery current IBAT. Figure 2A A schematic diagram showing the relationship between battery current IBAT and time. Figure 2A As shown, when the battery current IBAT_T-1 at the previous moment is a non-light load current and relatively high, and the current battery current IBAT is a light load current and relatively low, the current difference ΔI exceeds the preset current difference threshold, and the system 100 for estimating the state of charge of the battery is judged to operate in a light load condition or a non-light load condition to adjust the gain K. It should be noted that the so-called current and current difference refer to the absolute value of the current or the current difference. Of course, in another embodiment, it is also possible to directly judge whether the system 100 for estimating the state of charge of the battery is operating in a light load condition or a non-light load condition based on the absolute value of the battery current IBAT.

[0111] In another embodiment, the gain control engine 120 may also define a light load condition when the voltage difference ΔV does not exceed the preset voltage difference or the battery current IBAT does not exceed the preset current IBATth, and the gain control engine 120 adjusts and maintains the gain K as a fixed light load gain. From another perspective, when the light load condition occurs, after the gain K is maintained at the fixed light load gain, the gain control engine 120 no longer adaptively adjusts the gain K, or periodically calibrates the gain K at a relatively long period. Figure 2B A schematic diagram showing the relationship between battery voltage VBAT, open circuit voltage OCV and time. Figure 2B As shown, in one embodiment, the voltage difference ΔV1 exceeds the preset voltage difference or the battery current IBAT does not exceed the preset current IBATth, which is defined as a non-light load condition, and the voltage difference ΔV2 does not exceed the preset voltage difference, which is defined as a light load condition. Figure 2A In the illustrated embodiment, the battery current IBAT is negative.

[0112] According to one embodiment of the present invention, under non-light load conditions, when the voltage difference ΔV is large enough, the battery current IBAT is used to dominate the calculation of the state of charge change ΔSOC. The battery voltage VBAT and the battery current IBAT are combined with the sensing architecture to track and adaptively adjust the gain K by controlling the gain K, thereby optimizing the calculation of the state of charge change ΔSOC and providing good transient response and short-term accuracy. Its performance is comparable to that of a Coulomb Counter, but it does not rely on charge count to calculate the state of charge SOC, avoiding cumulative errors and saving power, without the need for full-time Continuous Analog-to-Digital Converter (CADC) conversion.

[0113] Under light load conditions, since the change in the battery current IBAT measurement is small, the CADC error percentage increases, so the weight of the gain K is reduced, and the battery voltage dominates the calculation of the state of charge change ΔSOC, which is implemented in an adaptive manner using the voltage difference ΔV. The gain control engine 120 can also periodically calibrate the state of charge SOC in a relatively long period to provide a long-term stable state of charge SOC estimation.

[0114] It should be noted that the CADC error percentage indicates the percentage of the error generated in the process of converting the simulation signal to the digital signal due to the limitation of the conversion accuracy or other influencing factors. Specifically, when CADC converts the simulation signal (such as battery voltage or current) into a digital signal, the conversion process may be affected by resolution, noise or quantization error, resulting in an error between the digital signal and the actual simulation signal. This error is usually expressed as a percentage in order to quantify and analyze the accuracy of CADC. In the battery management system, the error percentage of CADC will affect the measurement accuracy of voltage, current or other parameters, and thus affect the estimation accuracy of the battery state of charge SOC.

[0115] In summary, according to the present invention, under non-light load conditions, the battery current IBAT is used to dominate the calculation of the state of charge change ΔSOC, achieving an accuracy comparable to that of a coulomb counter and avoiding the problems of cumulative error and power consumption. Under light load conditions, the battery voltage VBAT is used to dominate the calculation of the state of charge change ΔSOC, and the natural driving force is used to maintain a long-term stable state of charge SOC, thereby further improving the reliability and stability of the system.

[0116] Figure 3 A hardware system block diagram for estimating the state of charge of a battery according to another embodiment of the present invention is shown. Figure 3 As shown, this embodiment provides a system 100 for estimating the state of charge of a battery. The system 100 for estimating the state of charge of a battery includes a battery fuel gauge 110, a gain control engine 120, and an accumulator 130.

[0117] In the present embodiment, the gain control engine 120 compares the charge change ΔSOC_T-1 at the last moment with the change target value ΔSOCI, and adapts the gain K, wherein the change target value ΔSOCI is related to the battery current IBAT and the full charge capacity FCC. In one embodiment, the change target value ΔSOCI is positively correlated to the battery current IBAT. The voltage difference ΔV is positively correlated to the difference between the battery voltage VBAT and the open circuit voltage OCV. In one embodiment, the change target value is more related to the full charge capacity FCC. For example, the change target value ΔSOCI is negatively correlated to the full charge capacity FCC, and the change target value ΔSOCI is negatively correlated to a quotient of the full charge capacity FCC divided by the battery current IBAT. For example, when the charge change ΔSOC_T-1 at the last moment is lower than the change target value ΔSOCI, the gain K is increased; and when the charge change ΔSOC_T-1 at the last moment is higher than the change target value ΔSOCI, the gain K is decreased.

[0118] It should be noted that Full Charged Capacity (FCC) refers to the maximum amount of electricity that a battery can store when fully charged. Full Charged Capacity FCC is related to load conditions, battery temperature TBAT and / or battery aging degree AGS. Full Charged Capacity FCC will gradually decrease with the use and aging of the battery, and is one of the important indicators for evaluating the health and performance of the battery. This is well known to those skilled in the art and will not be elaborated here.

[0119] Figure 4 A hardware block diagram of a system for estimating the state of charge of a battery according to an embodiment of the present invention is shown. Figure 4 As shown, this embodiment provides a more specific embodiment of a system 100 for estimating the state of charge of a battery. In this embodiment, the system 100 for estimating the state of charge of a battery includes a battery fuel gauge 110, a gain control engine 120, and an accumulator 130. The battery fuel gauge 110 includes a weighted fuzzifier 111, a pressure difference fuzzifier 112, a multiplier 113, a compensator 114, an optimizer 115, a table lookup 116, and a subtractor 117.

[0120] The weighted fuzzifier 111 estimates the weight W using a voltage weight model according to the battery voltage VBAT, wherein the voltage weight model is a first preset relationship between the battery voltage VBAT and the weight W in the battery information collected during charging, discharging and relaxing of the battery. The voltage difference fuzzifier 112 is used to estimate the fuzzy voltage difference fΔV using a voltage difference model according to the voltage difference ΔV, wherein the voltage difference model is a second preset relationship between the voltage difference ΔV and the fuzzy voltage difference fΔV. The multiplier 133 is used to perform a multiplication operation on the weight W and the fuzzy voltage difference fΔV to obtain a product WfΔV of the weight and the fuzzy voltage difference. The compensator 114 compensates or calibrates the product WfΔV of the weight W and the fuzzy voltage difference fΔV according to the gain K to generate a charge change ΔSOC. In one embodiment, the optimizer 115 can apply an additional gain to the weighted charge change ΔSOC for optimization.

[0121] In this embodiment, the accumulator 130 accumulates the weighted charge change ΔSOC by, for example but not limited to, an inverse Z transformation to determine an estimated state of charge SOC. Then, the estimated state of charge SOC is fed back to the lookup table 116 to generate an estimated open circuit voltage OCV. The lookup table 116 is used to query a preset state of charge and open circuit voltage relationship table according to the state of charge SOC to generate the open circuit voltage OCV. The system 100 for estimating the state of charge of the battery repeatedly performs the above steps to estimate the state of charge SOC.

[0122] Figure 5A and Figure 5B A schematic diagram showing the correlation results of the weighted fuzzifier 111 and the pressure difference fuzzifier 112 in the algorithm for estimating the state of charge of the battery. Figure 5A and Figure 5B It shows the relevant results in estimating the state of charge (SOC) of the battery before estimating the current state of charge (SOC).

[0123] Figure 5A The relationship between the battery voltage VBAT and the state of charge SOC measurement results under different charging conditions is shown. The charging condition OCV means that the battery can be charged 2% per hour; the charging condition 0.5C means that the battery can be charged 50% per hour; the charging condition 0.25C means that the battery can be charged 25% per hour. Figure 5A It shows that under the same state of charge SOC, the higher the charging rate, the higher the battery voltage VBAT.

[0124] Figure 5B It shows the relationship between the battery voltage VBAT and the state of charge SOC measurement results under different discharge conditions. The discharge condition OCV means that the battery can be discharged by 2% every hour; the discharge condition 0.5C means that the battery can be discharged by 50% every hour; the discharge condition 0.25C means that the battery can be discharged by 25% every hour; the discharge condition 0.15C means that the battery can be discharged by 15% every hour; the discharge condition 0.1C means that the battery can be discharged by 10% every hour. Figure 5B It shows that at the same state of charge SOC value, when the discharge rate is higher, the battery voltage VBAT is lower. The following will explain how to establish Figure 4 The differential pressure fuzzifier 112 is shown.

[0125] Figure 6 An embodiment of a partial build of a pressure drop model of the pressure drop fuzzifier 112 is shown. Figure 6 The table 310, the table 320, the curve chart 330 and the curve chart 340 are included. The table 310 includes Figure 5A The captured data. For example, when the state of charge SOC value is 80%, for the charging situation that the battery can be charged 2% per hour, the battery voltage VBAT is 4000mV. For the charging situation that the battery can be charged 25% per hour, the battery voltage VBAT is 4179 mV. In addition, when the state of charge SOC value is 60%, for the charging situation that the battery can be charged 2% per hour, the battery voltage VBAT is 3850 mV. For the charging situation that the battery can be charged 25% per hour, the battery voltage VBAT is 4023 mV.

[0126] Table 320 is generated based on the information in Table 310. For example, when the state of charge SOC value is 80%, the open circuit voltage OCV of the battery (which means that the battery can be charged 2% per hour) is used as a reference. The voltage difference between the battery open circuit voltage OCV and the battery voltage VBAT at a charging condition of 0.25C (which means that the battery can be charged 25% per hour) is 179 mV (that is, the result of subtracting 4000 mV from 4179 mV). Similarly, when the state of charge SOC value is 60%, the voltage difference between the battery open circuit voltage OCV and the battery voltage VBAT at a charging condition of 0.25C (which means that the battery can be charged 25% per hour) is 173 mV (that is, the result of subtracting 3850 mV from 4023 mV). By repeating the above steps, Table 320 can be obtained. In addition, according to Table 320, the relationship 330 between the voltage difference and the charging rate under different states of charge SOC can be obtained. After normalizing the relationship 330 , a curve 340 can be obtained.

[0127] Figure 7 Display as Figure 4 Another embodiment of modeling of a portion of the pressure difference model of the pressure difference fuzzifier 112 is shown. Figure 7 The table 410, the table 420, the curve chart 430 and the curve chart 440 are included. The table 410 includes Figure 5B The captured data. For example, when the state of charge SOC value is 80%, for the discharge condition that the battery can be discharged by 2% every hour, the battery voltage VBAT is 4000mV. For the discharge condition that the battery can be discharged by 10% every hour, the battery voltage VBAT is 3964 mV. In addition, when the state of charge SOC value is 60%, for the discharge condition that the battery can be discharged by 2% every hour, the battery voltage VBAT is 3850 mV. For the discharge condition that the battery can be discharged by 10% every hour, the battery voltage VBAT is 3795 mV.

[0128] Table 420 is generated based on the information in Table 410. For example, when the state of charge SOC value is 80%, the battery open circuit voltage OCV (which means that the battery can be discharged 2% per hour) is used as a benchmark. The voltage difference between the battery open circuit voltage OCV and the battery voltage VBAT at the discharge condition of 0.1C (which means that the battery can be discharged 10% per hour) is 36 mV (that is, the result of subtracting 3964 mV from 4000 mV). Similarly, when the state of charge SOC value is 60%, the voltage difference between the battery open circuit voltage OCV and the battery voltage VBAT at the discharge condition of 0.25C (which means that the battery can be discharged 25% per hour) is 55 mV (that is, the result of subtracting 3795 mV from 3850 mV). By repeating the above steps, Table 420 can be obtained. In addition, according to Table 420, the relationship 430 between the voltage difference and the discharge rate under different states of charge SOC can be obtained. After normalizing the relationship 430 , a curve 440 can be obtained.

[0129] Figure 8 Display as Figure 4 FIG. 4 is an embodiment of the pressure difference modeling of the pressure difference fuzzifier 112. By combining the curves 340 and 440, this embodiment replaces Figure 4 The voltage drop fuzzifier 112 shown establishes a voltage drop model 510. The voltage drop model 510 shows that when the absolute value of the voltage difference ΔV between the battery open circuit voltage OCV and the battery voltage VBAT during charging / discharging is higher, the charging / discharging current is higher (corresponding to Figure 4 The charge change ΔSOC is shown, so there is a V-shaped relationship between the two.

[0130] Fig. 9 Display as Figure 4 An embodiment of the voltage weight model establishment of the weighted fuzzifier 111 is shown. Fig. 9 The table 610 includes a table 620, a curve diagram 630 (showing the relationship between the battery voltage VBAT and the weight W), and a curve diagram 640 (showing the voltage weight model). The table 610 includes Figure 5BThe captured data. For example, when the state of charge SOC value is 90%, for the discharge situation that the battery can be discharged by 2% per hour, the battery voltage VBAT is 4100 mV. For the discharge situation that the battery can be discharged by 10% per hour, the battery voltage VBAT is 4065 mV. In addition, when the state of charge SOC value is 80%, for the discharge situation that the battery can be discharged by 2% per hour, the battery voltage VBAT is 4000 mV. For the discharge situation that the battery can be discharged by 15% per hour, the battery voltage VBAT is 3952 mV. In addition, when the state of charge SOC value is 70%, for the discharge situation that the battery can be discharged by 2% per hour, the battery voltage VBAT is 3900 mV. For the discharge situation that the battery can be discharged by 25% per hour, the battery voltage VBAT is 3811 mV.

[0131] Table 620 is generated based on the information in Table 610. For example, when the state of charge SOC value is 90%, the discharge condition OCV (which means that the battery can be discharged 2% every hour) is used as a benchmark. The weight of the battery voltage of 4.1 V and the battery can be discharged 10% every hour is equal to 0.29 (this is calculated by 10 / (4100-4065)). The weight of the battery voltage of 4.0 V and the battery can be discharged 15% every hour is equal to 0.31 (this is calculated by 15 / (4000-3952)). The weight of the battery voltage of 3.9 V and the battery can be discharged 25% every hour is equal to 0.28 (this is calculated by 25 / (3900-3811)). By repeating the above steps, Table 620 can be obtained. In addition, according to Table 620, the relationship 630 between the battery voltage VBAT and the weight W (as shown in Figure 2) under the discharge current can be obtained. After the relationship 630 is normalized, the voltage weight model 640 required by the weighted fuzzifier 111 shown in FIG. 2 can be obtained.

[0132] Fig.10 The hardware block diagram and data table required for the system for estimating the state of charge of a battery according to one embodiment of the present invention are shown. Fig.10 As shown, Figure 8 The pressure difference model 510 is shown with Fig. 9 The voltage weight model 640 is shown embedded in the system 100 for estimating the state of charge of a battery. Since the battery is in a discharged state, the graph 440 that is part of the voltage difference model 510 is drawn. In addition, the present embodiment provides a data table 710 corresponding to each node in the system 100 for estimating the state of charge of a battery.

[0133] According to the voltage weight model 640 , the weight W may be between 0.8 and 1.8 depending on the value of the battery voltage VBAT. In this embodiment, when the value of the battery voltage VBAT is 3.894 Volts, the weight W applied to the output of the voltage drop fuzzifier 112 is 0.9.

[0134] The voltage difference ΔV is used as an input to the voltage difference fuzzifier 112. The voltage difference ΔV is obtained by subtracting the open circuit voltage OCV of the battery from the battery voltage VBAT. The state of charge SOC calculated by the battery state of charge estimation system 100 is input to the open circuit voltage (OCV) lookup table 116. As shown in the voltage difference fuzzifier 112, when the absolute value of the voltage difference ΔV is larger, the absolute value of the charge change ΔSOC output by the battery fuel gauge 110 is larger. The curve 440 shows that when the voltage difference ΔV is, for example, -100 mV, the charge change ΔSOC is -0.25.

[0135] As described above, the charge variation ΔSOC calculated by the pressure difference fuzzifier 112 is weighted by the output weight W of the weighted fuzzifier 111 and optimized by the optimizer 115. In one embodiment, after the weighting, the optimizer 115 generates a gain K according to the least mean square optimization method and the actual data of battery charging / discharging and the adaptive adjustment of the battery current IBAT by the gain control engine 120. The gain K is used to calculate the weighted charge variation ΔSOC.

[0136] Next, the system 100 for estimating the state of charge of the battery adds the weighted charge change ΔSOC to the accumulator 130 (for example, but not limited to, using the inverse Z transformation of the state of charge SOC) to determine a new state of charge SOC. The new state of charge SOC is fed back to the table lookup 116 of the open circuit voltage OCV, wherein this step is repeated. Table 710 shows samples of three batteries, each separated by 36 seconds. Based on the above content about the system 100 for estimating the state of charge of the battery, the operation mode of the system 100 for estimating the state of charge of the battery in this embodiment is: first determine the voltage difference, and apply multiple fuzzy calculation methods to the voltage difference, and then adaptively adjust the gain according to the gain control engine 120.

[0137] Fig.11 The experimental results obtained after applying the algorithm described in one embodiment of the present invention to the least mean square optimization are shown. Fig.11As shown, the algorithm 810 is similar to the system 100 for estimating the state of charge of a battery, and the difference between the two is that the algorithm 810 has an additional least mean square optimization function block 812. The battery voltage VBAT and the state of charge SOC corresponding to the algorithm 810 are shown in the graph 820 and the graph 830 respectively. The least mean square optimization function block 812 receives the ideal value of the state of charge SOC measured by the external measuring instrument in the graph 830 and the estimated state of charge SOC provided by the system 100 for estimating the state of charge of a battery in the graph 830. The least mean square optimization function block 812 gradually adjusts the optimizer 816. According to the adjustment made by the least mean square optimization function block 812, different gains (gain #1 to gain #3) are applied to the optimizer 816. As a result, for example, gain #1 is the best result among the three, so gain #1 is selected as an optimal gain K. It should be noted that, in this embodiment, for ease of understanding, the adaptive adjustment of the gain K by the gain control engine 120 according to the battery current IBAT is omitted in order to illustrate the least mean square optimization operation.

[0138] Fig.12 Shown in Figure 4 In the illustrated embodiment, experimental results obtained by estimating the state of charge of a battery using the system 100 for estimating the state of charge of a battery are shown. Fig.12 Three graphs 910, 920, and 930 are included, which show the error of the estimated state of charge SOC under different charging / discharging conditions. Graph 910 shows that at a standard charge / discharge rate of 0.5C, the error of the estimated state of charge SOC is between -3% and +3%. Graph 920 shows that at a standard charge / discharge rate of 0.25C, the error of the estimated state of charge SOC is also between -3% and +3%. Graph 930 shows that at a partial charge / discharge rate of 0.5C, the error of the estimated state of charge SOC is between -4% and +4%. Therefore, graphs 910, 920, and 930 can show the accuracy of the system 100 for estimating the state of charge of the battery.

[0139] Fig.13A flow chart of a method for estimating the state of charge of a battery according to an embodiment of the present invention is shown. This embodiment provides a method 1000 for estimating the state of charge SOC of a battery, the steps of which include: First, a voltage difference (ΔV) is calculated according to a battery voltage (VBAT) and an open circuit voltage (OCV) by a battery fuel gauge (VoltaicGauge) (step 1002). Then, a gain is adaptively adjusted according to a battery current (IBAT) and a full charge capacity (FCC) by a gain control engine (Gain Control Engine) (step 1004). Then, the battery fuel gauge generates a charge change (ΔSOC) according to the voltage difference (ΔV) and the gain (step 1006). Then, a state of charge (SOC_T+1) at the next moment is generated according to a current state of charge (SOC_T) and the charge change (ΔSOC) (step 1008). Then, the state of charge (SOC_T+1) at the next moment is used as the current state of charge (SOC_T), and the process returns to step 1002 to repeat the operation.

[0140] It should be noted that Fig.13 The embodiment shown is an iterative method. When the state of charge needs to be estimated, the gain is dynamically adjusted and corrected in an iterative manner. Therefore, after step 1008 is completed, the state of charge at the next moment (SOC_T+1) is used as the current state of charge (SOC_T), and the process returns to step 1002 to repeat the operation; when the state of charge does not need to be estimated or the gain does not need to be adjusted (for example, in one embodiment, a fixed gain is used when the load is light and the gain is not dynamically adjusted), the process of method 1000 is stopped or paused.

[0141] In one embodiment, the step of adaptively adjusting a gain according to a battery current (IBAT) using a gain control engine (Gain Control Engine) (step 1004) further includes: adaptively adjusting the gain according to the gain (K) and the voltage difference (ΔV) before adjustment using the gain control engine.

[0142] In one embodiment, in the step (step 1004 ) of adaptively adjusting a gain according to a battery current (IBAT) using a gain control engine, the gain control engine adjusts the gain by increasing or decreasing a fixed gain difference.

[0143] In one embodiment, in the step (step 1004) of adaptively adjusting a gain according to a battery current (IBAT) using a gain control engine, the gain control engine further adjusts the gain according to a current difference between a battery current (IBAT_T-1) at a previous moment and the battery current (IBAT).

[0144] In one embodiment, in the step (step 1004) of adaptively adjusting a gain according to a battery current (IBAT) using a gain control engine, when the voltage difference does not exceed a preset voltage difference, it is defined as a light load condition, and the gain control engine adjusts and maintains the gain to a fixed light load gain.

[0145] In one embodiment, the step of adaptively adjusting a gain according to a battery current (IBAT) using a gain control engine (Gain Control Engine) (step 1004) includes: using the gain control engine to compare a charge change at a previous moment (ΔSOC_T-1) with a change target value (ΔSOCI), and adaptively adjusting the gain, wherein the change target value is related to the battery current and the full charge capacity (FCC).

[0146] In one embodiment, the full charge capacity (FCC) is related to a load condition, a battery temperature (TBAT) and / or a battery aging level (AGS).

[0147] In one embodiment, the step of generating a charge change according to the voltage difference and the gain includes: estimating a weight according to the battery voltage using a voltage weight model, wherein the voltage weight model is a first preset relationship between the battery voltage and the weight in battery information collected during charging, discharging and relaxing of the battery; estimating a fuzzy pressure difference according to the voltage difference using a pressure difference model, wherein the pressure difference model is a second preset relationship between the voltage difference and the fuzzy pressure difference; and generating the charge change according to the weight, the fuzzy pressure difference and the gain.

[0148] In one embodiment, the method 1000 for estimating the state of charge of a battery further includes: before generating the state of charge (SOC_T+1) at a next time, collecting the battery information under different charging / discharging currents.

[0149] In one embodiment, the method 1000 for estimating the state of charge of a battery further includes: establishing the voltage weight model and the voltage difference model by estimating the state of charge and the battery voltage under different charge / discharge currents.

[0150] In one embodiment, the method 1000 for estimating the state of charge of a battery further includes: calculating the weight according to the difference between the battery voltage at the charge / discharge current and at different charge / discharge currents to establish the voltage weight model.

[0151] In one embodiment, the method 1000 for estimating the state of charge of a battery further includes: calculating the fuzzy pressure difference according to the charge / discharge current to establish the pressure difference model.

[0152] In one embodiment, the method 1000 for estimating the state of charge of a battery further includes: according to the state of charge, querying a preset state of charge and open circuit voltage relationship table to generate the open circuit voltage.

[0153] In order to establish the model used in the method of the present invention, the present invention uses a standard charging and discharging process to collect battery information. For example, the present invention observes the state of charge SOC and the battery voltage VBAT through different charging and discharging currents. Therefore, based on these observations, the present invention is able to establish a partner function (or relationship) between the following two: (1) a voltage difference between the battery voltage VBAT and an estimated open circuit voltage (OCV) of the battery; and (2) a charge change ΔSOC used to adjust the estimated state of charge SOC. In addition, based on these observations, the present invention is able to establish another partner function (or relationship) between a weight applied between the charge change ΔSOC and the battery voltage VBAT. These two partner functions form a set of standard models that can be optimized based on specific battery charging and discharging information. Specific battery data is most commonly used user experience. Furthermore, an optimal gain can be obtained through a minimized least square error algorithm, and the gain is adaptively adjusted based on the sensed battery current IBAT, thereby further fine-tuning the charge change ΔSOC. In addition, the gain control engine adaptively adjusts the gain according to the battery current IBAT, so that the present invention can still provide a correct state of charge under charging and discharging conditions even when the charging / discharging current changes drastically; and can further provide a more accurate state of charge SOC according to different battery loads, different battery temperatures, different battery capacities and / or different battery aging levels.

[0154] The present invention has been described above with respect to the preferred embodiment, but the above description is only to make it easy for those skilled in the art to understand the content of the present invention, and is not used to limit the scope of rights of the present invention. The various embodiments described are not limited to individual applications, but can also be used in combination. For example, two or more embodiments can be used in combination, and part of the components in one embodiment can also be used to replace the corresponding components in another embodiment. In addition, under the same spirit of the present invention, those skilled in the art can think of various equivalent changes and various combinations. For example, the present invention refers to "processing or calculating or generating an output result according to a certain signal", which is not limited to the signal itself, but also includes, when necessary, converting the signal to voltage and current, current and voltage, and / or ratio conversion, and then processing or calculating according to the converted signal to generate an output result. It can be seen that under the same spirit of the present invention, those skilled in the art can think of various equivalent changes and various combinations, and there are many combinations, which are not listed one by one here. Therefore, the scope of the present invention should cover the above and all other equivalent changes.

Claims

1. A method for estimating a state of charge of a battery, comprising: (a) using a battery fuel gauge to calculate a voltage difference (ΔV) based on a battery voltage (VBAT) and an open circuit voltage (OCV); (b) adaptively adjusting a gain (K) according to a battery current (IBAT) and a full charge capacity (FCC) using a gain control engine; (c) generating a current charge change (ΔSOC_T) by the battery fuel gauge according to the voltage difference (ΔV) and the adjusted gain (K); and (d) Using an accumulator to generate a state of charge (SOC_T+1) at a next moment according to a current state of charge (SOC_T) and the current charge change (ΔSOC_T).

2. The method for estimating the state of charge of a battery as claimed in claim 1, wherein: The step (b) further includes: using the gain control engine to adaptively adjust the gain according to the gain (K) and the voltage difference (ΔV) before adjustment.

3. The method for estimating the state of charge of a battery as claimed in claim 1, wherein: The step (a), the step (b), the step (c) and the step (d) are performed in sequence, and after the step (d), the charge state at the next moment is used as the current charge state, and the process returns to the step (a).

4. The method for estimating the state of charge of a battery as claimed in claim 3, wherein: In the step (b), the gain control engine adjusts the gain by increasing or decreasing a fixed gain difference.

5. The method for estimating the state of charge of a battery as claimed in claim 4, wherein: In the step (b), the gain control engine further adjusts the gain according to a current difference between a battery current (IBAT_T-1) at a previous moment and the battery current (IBAT).

6. The method for estimating the state of charge of a battery as claimed in claim 1, wherein: In the step (b), when the voltage difference does not exceed a preset voltage difference or the battery current does not exceed a preset current, it is defined as a light load condition, and the gain control engine adjusts and maintains the gain as a fixed light load gain.

7. The method for estimating the state of charge of a battery as claimed in claim 1, wherein: The step (b) includes: using the gain control engine to compare a charge change amount (ΔSOC_T-1) at a previous moment with a change amount target value (ΔSOCI), and adaptively adjusting the gain, wherein the change amount target value is related to the battery current and the full charge capacity (FCC).

8. The method for estimating the state of charge of a battery as claimed in claim 1, wherein: The full charge capacity (FCC) is related to a load condition, a battery temperature (TBAT) and / or a battery aging level (AGS).

9. The method for estimating the state of charge of a battery as claimed in claim 1, wherein: The step (c) comprises: estimating a weight using a voltage weight model according to the battery voltage, wherein the voltage weight model is a first predetermined relationship between the battery voltage and the weight in battery information collected during charging, discharging, and relaxation of the battery; estimating a fuzzy pressure difference using a pressure difference model according to the voltage difference, wherein the pressure difference model is a second preset relationship between the voltage difference and the fuzzy pressure difference; and The charge variation is generated according to the weight, the fuzzy pressure difference and the gain.

10. The method for estimating the state of charge of a battery as claimed in claim 9, wherein: Also includes: Before generating the state of charge (SOC_T+1) at the next moment, the battery information is collected under different charging / discharging currents.

11. The method for estimating the state of charge of a battery as claimed in claim 9, wherein: Also includes: The voltage weight model and the voltage difference model are established by estimating the state of charge and the battery voltage under different charge / discharge currents.

12. The method for estimating the state of charge of a battery as claimed in claim 11, wherein: Also includes: The voltage weight model is established by calculating the weight according to the difference between the battery voltage at the charge / discharge current and at different charge / discharge currents.

13. The method for estimating the state of charge of a battery as claimed in claim 11, wherein: Also includes: The fuzzy pressure difference is calculated according to the charge / discharge current to establish the pressure difference model.

14. The method for estimating the state of charge of a battery as claimed in claim 1, wherein: Also includes: According to the state of charge, a preset state of charge and open circuit voltage relationship table is searched to generate the open circuit voltage.

15. A system for estimating the state of charge of a battery, comprising: a battery fuel gauge for calculating a voltage difference (ΔV) according to a battery voltage (VBAT) and an open circuit voltage (OCV); a gain control engine for adaptively adjusting a gain (K) according to a battery current (IBAT) and a full charge capacity (FCC); and An accumulator, for generating a state of charge at a next moment (SOC_T+1) according to a current state of charge (SOC_T) and a current charge change (ΔSOC_T); The battery fuel gauge generates the current charge change (ΔSOC_T) according to the voltage difference (ΔV) and the adjusted gain (K).

16. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The gain control engine also adaptively adjusts the gain according to the gain (K) and the voltage difference (ΔV) before adjustment.

17. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The gain control engine adjusts the gain in an iterative manner by increasing or decreasing a fixed gain difference.

18. The system for estimating the state of charge of a battery as claimed in claim 17, wherein: The gain control engine further adjusts the gain according to a current difference between a battery current (IBAT_T-1) at a previous moment and the battery current (IBAT).

19. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The gain control engine defines a light load condition when the voltage difference does not exceed a preset voltage difference or the battery current does not exceed a preset current, and the gain control engine adjusts and maintains the gain to be a fixed light load gain.

20. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The gain control engine compares a charge change amount (ΔSOC_T-1) at a previous moment with a change amount target value (ΔSOCI) to adaptively adjust the gain, wherein the change amount target value is related to the battery current and the full charge capacity (FCC).

21. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The full charge capacity (FCC) is related to a load condition, a battery temperature (TBAT) and / or a battery aging level (AGS).

22. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The battery fuel gauge includes: a weighted fuzzifier for estimating a weight according to the battery voltage using a voltage weight model, wherein the voltage weight model is a first predetermined relationship between the battery voltage and the weight in battery information collected during charging, discharging, and relaxation of the battery; a pressure difference fuzzifier, used for estimating a fuzzy pressure difference according to the voltage difference by using a pressure difference model, wherein the pressure difference model is a second preset relationship between the voltage difference and the fuzzy pressure difference; a multiplier for performing a multiplication operation on the weight and the fuzzy pressure difference to obtain a product of the weight and the fuzzy pressure difference; and A compensator is used to compensate or calibrate the product of the weight and the fuzzy pressure difference according to the gain to generate the charge variation.

23. The system for estimating the state of charge of a battery as claimed in claim 22, wherein: The weighted fuzzy model and the voltage difference fuzzy model are established under different charging / discharging currents according to the corresponding different states of charge and different battery voltages to form the voltage weight model and the voltage difference model.

24. The system for estimating the state of charge of a battery as claimed in claim 23, wherein: The weighted fuzzy device calculates the weight according to the difference between the battery voltages at different charging / discharging currents to establish the voltage weight model.

25. The system for estimating the state of charge of a battery as claimed in claim 23, wherein: The voltage difference fuzzifier calculates the fuzzy voltage difference according to the difference between the voltage differences at different charge / discharge currents to establish the voltage difference model.

26. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The battery fuel gauge also includes a table lookup device for looking up a preset state of charge and open circuit voltage relationship table according to the state of charge to generate the open circuit voltage.

27. The system for estimating the state of charge of a battery as claimed in claim 15, wherein: The accumulator accumulates at least one previous charge change amount by using the inverse Z-transformation method of the charge state to generate the current charge state.

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