Battery control parameter estimation system and battery control parameter estimation method

Abstract

The invention provides a battery control parameter estimation system and a battery control parameter estimation method. The battery control parameter estimation system includes sensing, storage, and estimation circuits. The estimation circuit determines an operation model according to the to-be-estimated control parameter signal and the battery characteristic signal or the internal reference information. The operation model defines a control parameter, a state parameter and a relationship thereof, and performs an estimation operation to generate an estimation result. The estimation operation comprises the following steps: dividing the limited range into a plurality of sections, and generating a plurality of control parameter values; sequentially inputting the control parameter values into the operation model to obtain a plurality of state parameter values; checking whether the judgment object meets a judgment condition or not; if yes, determining an estimation result and ending; if not, the control parameter values corresponding to the two state parameter values crossing the target value for the first time are taken, the limit range of the next round is defined, and the next round of estimation operation is carried out.

Description

Technical Field

[0001] The present invention relates to a battery control parameter estimation system, and in particular to a battery control parameter estimation system that efficiently finds estimation results of control parameters in a nonlinear operation model, thereby saving system calculation time and energy consumption. The present invention also relates to a battery control parameter estimation method. Background Art

[0002] During the battery operation process, the battery electrical characteristics change due to changes in factors such as the battery's state of charge (SOC), material composition, battery aging, operation method, and battery temperature. Existing battery metering technology is mainly based on the sensing results of the battery's relevant characteristics, the battery electrical characteristics table, and the operation record to update the battery's current operation model or the calculation parameters therein, and estimate the subsequent battery state based on these operating conditions. However, when certain parameters change nonlinearly, or when different calculation parameters are combined for calculation, the relationship between these parameters may also cause the operation model to show nonlinear changes, and even lead to the generation of a nonlinear operation model (i.e., nonlinear corresponding control parameters and state parameters). In addition, because many battery characteristic parameters themselves have nonlinearity, and multiple characteristics affect each other, the battery characteristic operation model is complex, and it is difficult to use simple operations to calculate the solution of the control parameters. If the solution is solved by iterative calculation, it will result in a huge amount of calculation, resulting in lengthy calculation time and excessive power consumption.

[0003] In this case, using the bisection approximation method to solve and estimate the battery control parameters may lead to erroneous results (for example, when there is no single solution), while the exhaustive method consumes a lot of computing resources and power due to its large computational load.

[0004] In view of this, the present invention aims at the above-mentioned deficiencies of the prior art and proposes a battery control parameter estimation system and a battery control parameter estimation method, which can quickly find the solution of the control parameters in the nonlinear operation model, thereby saving the system's calculation time and energy consumption. Summary of the invention

[0005] The present invention provides a battery control parameter estimation system, comprising: a sensing circuit for sensing at least one battery characteristic and generating at least one corresponding battery characteristic signal; a storage circuit for storing at least one internal reference information; and an estimation circuit for: determining an operation model according to a control parameter signal to be estimated and the at least one battery characteristic signal or the at least one internal reference information, wherein the operation model defines a control parameter and a state parameter, and defines the relationship between the control parameter and the state parameter; and performing at least one round of estimation operation to generate an estimation result; wherein the estimation operation comprises: (a) dividing a limited range of the control parameter into a plurality of sections to generate a plurality of corresponding control parameter values; (b) inputting the plurality of control parameter values ​​into the operation model in sequence according to a sequence direction parameter to generate a plurality of corresponding state parameter values; (c) after each generation of the state parameter value, checking whether a corresponding judgment object satisfies a judgment condition; (d) when the judgment object satisfies the judgment condition, determining the estimation result and terminating the at least one round of estimation operation; and (e) When all the multiple judgment objects corresponding to the multiple state parameter values ​​do not satisfy the judgment condition, based on the multiple judgment objects, the two control parameter values ​​corresponding to the two state parameter values ​​that first cross a target value of the state parameter are used to define the limited range of the next round of estimation operation, and the next round of estimation operation is performed; wherein the multiple judgment objects are the multiple state parameter values ​​or the multiple segments; wherein the judgment condition is a node judgment condition or a segment judgment condition corresponding to the judgment object.

[0006] The present invention provides a battery control parameter estimation method, comprising: using a sensing circuit to sense at least one battery characteristic to generate at least one corresponding battery characteristic signal; storing at least one internal reference information in a storage circuit; using an estimation circuit to determine and select an operation model according to a control parameter signal to be estimated and the at least one battery characteristic signal or the at least one internal reference information, wherein the operation model defines a control parameter and a state parameter, and defines the relationship between the control parameter and the state parameter; and using the estimation circuit to perform at least one round of estimation operation to generate an estimation result; wherein the estimation operation includes: (a) dividing a limited range of the control parameter into a plurality of sections to generate a plurality of corresponding control parameter values; (b) inputting the plurality of control parameter values ​​into the operation model in sequence according to a sequence direction parameter to generate a plurality of corresponding state parameter values; (c) after each generation of the state parameter value, checking whether a corresponding judgment object satisfies a judgment condition; (d) when the judgment object satisfies the judgment condition, determining the estimation result and terminating the at least one round of estimation operation; and (e) When all the multiple judgment objects corresponding to the multiple state parameter values ​​do not satisfy the judgment condition, based on the multiple judgment objects, the two control parameter values ​​corresponding to the two state parameter values ​​that first cross a target value of the state parameter are used to define the limited range of the next round of estimation operation, and the next round of estimation operation is performed; wherein the multiple judgment objects are the multiple state parameter values ​​or the multiple segments; wherein the judgment condition is a node judgment condition or a segment judgment condition corresponding to the judgment object.

[0007] In one embodiment, the at least one internal reference information includes a battery electrical characteristic table, an operation record, a calculation parameter and / or a counting time.

[0008] In one embodiment, the at least one battery characteristic includes a battery voltage, a battery current and / or a battery temperature.

[0009] In one embodiment, the control parameter is defined according to one of the at least one battery characteristic signal or one of the at least one internal reference information.

[0010] In one embodiment, the state parameter is defined according to one of the at least one battery characteristic signal or one of the at least one internal reference information.

[0011] In one embodiment, the control parameter signal to be estimated includes an operation model selection parameter, the sequential direction parameter, a first round starting point and a first round end point; wherein the operation model selection parameter is used to determine the corresponding operation model; wherein the sequential direction parameter is used to indicate a sequential direction of the control parameter; wherein the first round starting point and the first round end point define the limited range of the first round of the estimation operation.

[0012] In one embodiment, in the same round of the estimation operation, the interval lengths of each of the plurality of segments are equal to each other.

[0013] In one embodiment, the step (d) of the estimation operation includes: when the difference between one of the state parameter values ​​of the multiple state parameter values ​​and the target value is lower than a first preset difference, it indicates that the node judgment condition is met, and the estimation circuit determines the estimation result according to a control parameter value corresponding to the state parameter value, and ends the at least one round of estimation operation.

[0014] In one embodiment, the step (d) of the estimation operation includes: when one of the multiple segments satisfies a piecewise linear condition, indicating that the segment judgment condition is satisfied, the estimation circuit performs linear interpolation on two control parameter values ​​corresponding to the segment and two state parameter values ​​corresponding to the segment, and determines the estimation result according to a control parameter value obtained by the linear interpolation, and ends the at least one round of estimation operation.

[0015] In one embodiment, the piecewise linear condition includes: the difference between two state parameter values ​​before and after the first crossing of the target value is lower than a second preset difference, or the difference between two control parameter values ​​corresponding to the two state parameter values ​​is lower than a third preset difference.

[0016] In one embodiment, the control parameter is a depth of discharge (DOD), and the state parameter is a battery voltage; wherein the operation model selection parameter indicates an estimation of the corresponding discharge depth when the battery voltage is equal to a discharge cut-off voltage threshold; wherein the sequence direction parameter indicates an increasing direction of the discharge depth; wherein the first round starting point is a current discharge depth; wherein the first round end point is an upper limit of the discharge depth; wherein the at least one battery characteristic signal corresponding to the operation model includes the battery voltage, a battery temperature and a battery current; wherein the at least one internal reference information corresponding to the operation model includes the discharge depth, an open circuit voltage (OCV) corresponding to the discharge depth characteristic table and a battery internal resistance corresponding to the discharge depth and battery temperature characteristic table.

[0017] In one embodiment, the control parameter is a charging time, and the state parameter is a battery temperature; wherein the operation model selection parameter indicates an estimate of the charging time corresponding to the battery temperature being equal to a charging cut-off temperature threshold; wherein the sequence direction parameter indicates a decreasing direction of the charging time; wherein the starting point of the first round is an upper limit charging time point; wherein the end point of the first round is a current charging time point; wherein the at least one battery characteristic signal corresponding to the operation model includes the battery temperature; wherein the at least one internal reference information corresponding to the operation model includes a battery temperature corresponding charging time characteristic table and a counting time.

[0018] Compared with the prior art, the present invention has at least the following advantages:

[0019] First, it avoids the problem that the bisection approximation method cannot find the correct solution when there are multiple possible solutions.

[0020] Second, the problem of excessive computational load and poor accuracy of the exhaustive method is solved.

[0021] Third, a multi-stage approach is adopted to narrow the computational scope and increase computational density, thereby reducing the computational load while ensuring computational accuracy.

[0022] Fourth, clearly specify the scope of analysis and focus only on the calculation of key data to avoid additional data interfering with the calculation results.

[0023] The following will be described in detail 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

[0024] Figure 1 FIG. 4 is a block diagram of a battery control parameter estimation system in one embodiment of the present invention.

[0025] Figure 2 FIG. 4 is a block diagram showing a battery control parameter estimation system in another embodiment of the present invention.

[0026] Figure 3 The present invention is an embodiment of the present invention, showing the operation steps of the battery control parameter estimation method.

[0027] Figure 4 FIG. 4 is an operational flow chart of an estimation operation in one embodiment of the present invention.

[0028] FIG. 5A to FIG. 5D A more specific embodiment of a method for estimating battery control parameters is shown according to the present invention.

[0029] Fig. 6A and Figure 6B Another more specific embodiment of the method for estimating battery control parameters is shown according to the present invention.

[0030] Explanation of symbols in the figure

[0031] 1: Battery control parameter estimation system

[0032] 2: Battery Pack

[0033] 11: Sensing circuit

[0034] 111: Voltage sensing circuit

[0035] 112: Current sensing circuit

[0036] 113: Temperature Sensing Circuit

[0037] 12: Storage circuit

[0038] 121: Volatile Memory Circuit

[0039] 122: Non-volatile memory circuit

[0040] 13: Control circuit

[0041] 14: Estimation Circuit

[0042] 15: Charge / discharge drive circuit

[0043] 20: Estimation Circuit

[0044] Bat1, Bat2, Bat3: Batteries

[0045] DOD, DOD1, DOD2, DOD3: Depth of Discharge

[0046] DODpr: Current discharge depth

[0047] DODup: upper limit of discharge depth

[0048] End1, End2, End3, End4: End point

[0049] EST: Control parameter signal to be estimated

[0050] Ibat: battery current

[0051] OCV: Open Circuit Voltage

[0052] Prd1, Prd2, Prd3, Prd4: Preset segment intervals

[0053] R: Battery internal resistance

[0054] Str1, Str2, Str3, Str4: Starting point

[0055] R: Battery internal resistance

[0056] Rstd: Battery reference internal resistance

[0057] S01, S02, S03, S04, S11, S12, S13, S131, S132: Steps

[0058] Sbat: Battery characteristic signal

[0059] STS: Estimated results

[0060] SWC, SWD: Power Switch

[0061] Tbat: battery temperature

[0062] Tc: Temperature sensitive element

[0063] Time_chg: Charging time

[0064] Ttrg: Charging cut-off temperature threshold

[0065] Vbat, Vb1, Vb2, Vb3, Vpr: battery voltage

[0066] Vb1', Vb2', Vb3': battery voltage sensing signals

[0067] Vs: Battery current sensing signal

[0068] Vt: Battery temperature sensing signal

[0069] Vtrg: discharge cut-off voltage threshold

[0070] Xm1~Xm6, Xn1~Xn7, Xp1~Xp6, Xq1~Xq6: control parameter values

[0071] Ym1~Ym6, Yn1~Yn7, Yp1~Yp6, Yq1~Yq6: Status parameter values DETAILED DESCRIPTION

[0072] 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.

[0073] Please refer to Figure 1 , Figure 1 FIG. 1 is a block diagram of a battery control parameter estimation system in one embodiment of the present invention. Figure 1As shown, the battery control parameter estimation system 1 includes a sensing circuit 11, a storage circuit 12 and an estimation circuit 20. The sensing circuit 11 is used to sense at least one battery characteristic of the battery to generate at least one corresponding battery characteristic signal Sbat. The battery characteristics include, for example but not limited to, battery voltage Vbat, battery current Ibat and / or battery temperature Tbat. The storage circuit 12 is used to store at least one internal reference information. In one embodiment, the internal reference information includes a battery electrical characteristic table, an operation record, a calculation parameter and / or a counting time. The estimation circuit 20 is used to determine an operation model based on the control parameter signal to be estimated EST and at least one battery characteristic signal Sbat or at least one internal reference information, wherein the operation model defines control parameters and state parameters, and defines the relationship between the control parameters and the state parameters. The estimation circuit 20 performs an estimation operation to generate an estimation result STS.

[0074] It should be noted that the battery electrical characteristic table includes, for example but not limited to, a comparison table between different battery electrical characteristics or between battery electrical characteristics and battery characteristics, such as a comparison table between open circuit voltage and discharge depth at different battery temperatures, a comparison table between state of charge and open circuit voltage, and the like, and other comparison tables related to battery electrical characteristics.

[0075] It should be noted that the operation record includes, for example but not limited to, the historical record data of the battery, which can display various battery parameters of the battery over a period of time, such as the battery voltage, battery current, battery temperature, etc. corresponding to different time points, and other comparison tables related to the battery parameter history records. These historical record data can be used to calculate the required data such as the battery current or the amount of electricity charged at a certain time point; in addition, the operation record provides the data required by the operation model to determine the parameters and determine specific conditions.

[0076] It should be noted that the calculation parameters include, but are not limited to, various battery parameters used in battery characteristic signals, battery electrical characteristic tables or operation records, such as battery voltage, battery current, battery temperature, open circuit voltage, discharge depth, state of charge, etc., and other parameters related to battery parameters.

[0077] It should be noted that the counting time includes, for example but not limited to, the charging counting time, the discharging counting time, the estimation operation counting time for counting each round of estimation operations, the state parameter value generation counting time for counting each state parameter value generation, and so on, and other counting times related to battery operation.

[0078] It should be noted that the estimation circuit 20 determines the control parameters and state parameters of the operating model based on the estimated control parameter signal EST, and obtains, calculates or derives the functional relationship between the control parameters and the state parameters based on at least one battery characteristic signal Sbat or at least one internal reference information to determine the operating model, wherein the functional relationship between the control parameters and the state parameters is, for example, a nonlinear functional relationship.

[0079] The estimation operation includes:

[0080] (a) the estimation circuit 20 divides the limited range of the control parameter of the operation model into a plurality of sections to generate a plurality of corresponding control parameter values;

[0081] (b) the estimation circuit 20 sequentially inputs a plurality of control parameter values ​​into the operation model according to the sequence direction indicated by the sequence direction parameter, and correspondingly generates a plurality of state parameter values ​​of the state parameter;

[0082] (c) after each state parameter value is generated, the estimation circuit 20 checks whether the corresponding judgment object satisfies the judgment condition;

[0083] (d) when the judgment object satisfies the judgment condition, the estimation circuit 20 determines the estimation result and ends the estimation operation; and

[0084] (e) when all the multiple judgment objects corresponding to all the multiple state parameter values ​​in the current estimation operation do not satisfy the judgment condition, the estimation circuit 20 defines the limited range of the next round of estimation operation by using the two control parameter values ​​corresponding to the two state parameter values ​​that first cross the target value of the state parameter according to the multiple judgment objects, and performs the next round of estimation operation;

[0085] The multiple judgment objects are multiple state parameter values ​​or multiple segments;

[0086] The judgment condition is a node judgment condition or a segment judgment condition corresponding to the judgment object.

[0087] In one embodiment, the control parameter is defined according to one of at least one battery characteristic signal or one of at least one internal reference information. For example, the control parameter may be a discharge depth, a counting time, a battery voltage, a battery current, a battery temperature, a parameter recorded in an operation record, a calculated parameter, etc. The estimation circuit 20 may select or define the control parameter from the battery characteristic signal or the internal reference information according to the control parameter signal to be estimated EST.

[0088] In one embodiment, the state parameter includes at least one of the battery characteristic signals or at least one of the internal reference information. For example, the state parameter may be discharge depth, counting time, battery voltage, battery current, battery temperature, parameters recorded in the operation record, calculated parameters, etc. The estimation circuit 20 may select or define the state parameter from the battery characteristic signal or the internal reference information according to the control parameter signal to be estimated EST.

[0089] In one embodiment, the control parameter signal to be estimated includes an operation model selection parameter, a sequential direction parameter, a first round start point and a first round end point; wherein the operation model selection parameter is used to indicate the corresponding operation model; wherein the sequential direction parameter is used to indicate the sequential direction of multiple control parameter values ​​of the control parameter input into the operation model; wherein the first round start point and the first round end point define the limited range of the first round of the estimated operation.

[0090] The operation model selection parameter includes relevant data required for selecting or deriving the operation model, so that the estimation circuit 20 can obtain or derive the operation model used for the estimation operation, which will be described in detail below with examples.

[0091] In one embodiment, in the same round of the estimation operation, the interval length of each of the multiple segments is equal to each other. The preset segment interval is, for example, fixed, and in different rounds of the estimation operation, the interval lengths of the preset segments in different steps (a) are different from each other. In one embodiment, the interval length of the current preset segment interval is greater than the interval length of the preset segment interval in the next round.

[0092] In one embodiment, the step (d) of the estimation operation includes: when the difference between one of the state parameter values ​​and the target value is lower than a first preset difference, the node judgment condition is satisfied, and the estimation circuit determines the estimation result according to the control parameter value of the corresponding state parameter value, and ends at least one round of estimation operation. For example, in the process of sequentially comparing the state parameter value and the target value to generate the comparison result, once the difference between the state parameter value and the target value is lower than the first preset difference, the corresponding control parameter value can be determined as the estimation result, and at least one round of estimation operation is ended. In the same round of estimation operation, the subsequent unfinished step of comparing the state parameter value and the target value to obtain the difference can be performed without continuing, and there is no need to perform the next round of estimation operation.

[0093] In one embodiment, the step (d) of the estimation operation includes: when one of the multiple segments meets the piecewise linear condition, it indicates that the segment judgment condition is met, the estimation circuit performs linear interpolation with two control parameter values ​​corresponding to the segment and two state parameter values ​​corresponding to the segment, and determines the estimation result according to the control parameter value obtained by the linear interpolation, and ends at least one round of estimation operation. In one embodiment, once a segment that meets the piecewise linear condition appears, linear interpolation can be performed on the corresponding state parameter value and control parameter value of the segment, and the obtained control parameter value is judged as the estimation result, and at least one round of estimation operation is ended, and the subsequent unexecuted checks on whether other segments meet the piecewise linear condition do not need to be continued, and there is no need to perform the next round of estimation operation.

[0094] In one embodiment, the piecewise linear condition includes: the difference between the two state parameter values ​​before and after the first crossing of the target value is lower than a second preset difference, or the difference between the two control parameter values ​​corresponding to the two state parameter values ​​is lower than a third preset difference.

[0095] It should be noted that the first preset difference, the second preset difference and the third preset difference are determined according to actual needs, as long as they can meet the requirements for determining the estimation result.

[0096] Please refer to Figure 2 , Figure 2 FIG. 1 is a block diagram of a battery control parameter estimation system in another embodiment of the present invention. Figure 2 As shown, the battery control parameter estimation system 1 includes a sensing circuit 11, a memory circuit 12, a charge / discharge driving circuit 15 and an estimation circuit 20. In this embodiment, the sensing circuit 11 includes a voltage sensing circuit 111, a current sensing circuit 112 and a temperature sensing circuit 113, for example.

[0097] In this embodiment, the voltage sensing circuit 111 is coupled to a battery pack 2 and is used to sense the battery voltage Vb1, Vb2, Vb3 of each battery of a plurality of batteries Bat1, Bat2, Bat3 connected in series in the battery pack 2, and generate battery voltage sensing signals Vb1', Vb2', Vb3' accordingly. The battery voltage sensing signals Vb1', Vb2', Vb3' can be stored in the volatile memory circuit 121 for calculation or transmission, and the battery current sensing signal Vs and the battery temperature sensing signal Vt described later can also be stored in the volatile memory circuit 121, which will not be described in detail. In one embodiment, the voltage sensing circuit 111 includes, for example but not limited to, an analog-to-digital converter (ADC) and a multiplexer (MUX) to realize the function of sensing voltage, wherein the structure and function of the analog-to-digital converter and the multiplexer are known to those skilled in the art, and thus will not be described in detail.

[0098] The current sensing circuit 112 is coupled to the sensing resistor Rs to sense the battery current Ibat flowing through the batteries Bat1, Bat2, Bat3, and generate a battery current sensing signal Vs, wherein the sensing resistor Rs is connected in series with the battery pack 2. The temperature sensing circuit 113 is coupled to the temperature sensitive element Tc to sense the battery temperature Tbat and generate a battery temperature sensing signal Vt. The battery voltage sensing signals Vb1', Vb2', Vb3', the battery current sensing signal Vs and the battery temperature sensing signal Vt mentioned above all belong to the battery characteristic signal Sbat.

[0099] It should be noted that, in the present embodiment, each battery characteristic signal Sbat corresponds only to a single battery Bat1, Bat2 or Bat3, and the internal reference information, the control parameter signal to be estimated EST, the sequential direction parameter, the estimation result STS, the control parameter, the control parameter value, the battery characteristic signal, the operation model, the state parameter, the state parameter value and other battery-related parameters or values ​​also correspond to a single battery Bat1, Bat2 or Bat3; that is to say, each battery Bat1, Bat2 or Bat3 has its own corresponding battery characteristic signal, internal reference information, the control parameter signal to be estimated EST, the estimation result STS, the control parameter, the control parameter value, the operation model, the state parameter, the state parameter value and other battery-related parameters or values, and each has corresponding battery characteristics.

[0100] In this embodiment, the storage circuit 12 includes a volatile memory circuit 121 and a non-volatile memory circuit 122. In one embodiment, the non-volatile memory circuit 122 can be used to store at least one internal reference information. The non-volatile memory circuit 122 can store, for example, an operation model, a battery electrical characteristic table, an operation record, a calculation parameter, a target value, a judgment condition, a first round start point, a first round end point, a preset segment interval, a first preset difference, a second preset difference, a third preset difference, or a piecewise linear condition. In one embodiment, the volatile memory circuit 121 can be used to temporarily store a battery characteristic signal, an estimation result, a control parameter value, a state parameter value, a comparison result, a counting time such as a charging time and a discharging time or a difference, etc.

[0101] The charge / discharge driving circuit 15 is coupled between the estimation circuit 20 and the power switches SWC and SWD, and is used to drive and operate the power switches SWC and SWD according to the operation signal of the estimation circuit 20 to charge / discharge the battery pack 2. This is well known to those skilled in the art and will not be described in detail here.

[0102] In one embodiment, the estimation circuit 20 determines the operation model according to the control parameter signal to be estimated EST and at least one battery characteristic signal or at least one internal reference information. The operation model defines the control parameter and the state parameter, and defines the relationship between the control parameter and the state parameter. The relationship between the control parameter and the state parameter is, for example, a nonlinear function relationship. This nonlinear function relationship, for example, already exists in the storage circuit 12 and can be directly selected and obtained. If this nonlinear function relationship needs to be obtained after calculation and conversion, the estimation circuit 20 obtains the information required for calculation and conversion from the battery characteristic signal or the internal reference information according to the control parameter signal to be estimated EST and actual application needs to determine the operation model. After determining the operation model, the estimation circuit 20 performs an estimation operation, for example, according to the sequential direction parameter in the control parameter signal to be estimated EST and the first round starting point and the first round end point, to generate an estimation result STS.

[0103] In this embodiment, if Figure 2 As shown, after the estimation circuit 20 obtains the current battery characteristic signal, it can update the internal reference information, such as updating the parameters in the comparison table of the battery reference internal resistance and the depth of discharge. The estimation circuit 20 can set the operation model and the sequence direction parameter according to the control parameter signal to be estimated EST to perform the estimation operation to generate the estimation result. The estimation result can be further used to predict when the battery power will be exhausted, or when it is necessary to limit the load in advance (such as stopping charging) to suppress the increase of the battery temperature Tbat.

[0104] The present invention can find the corresponding control parameter value in a more efficient and energy-saving manner according to one or more specific conditions of the state parameter as an estimation result, and the estimation result can be further used to predict the battery state in actual needs. In actual applications, there are many applications for converting the estimation result into the predicted battery state, which is not the focus of the present invention. Therefore, the subsequent description only describes the examples without elaborating on the various applications for predicting the battery state.

[0105] This embodiment is intended to illustrate the implementation of the present invention in a rechargeable battery system. Figure 1 The embodiments shown are the same, please also refer to Figure 1 Description.

[0106] Figure 3 FIG. 1 is a flowchart showing the operation steps of a method for estimating battery control parameters in one embodiment of the present invention. Figure 3 As shown, the battery control parameter estimation method includes:

[0107] Step S01: using a sensing circuit to sense at least one battery characteristic to generate at least one corresponding battery characteristic signal;

[0108] Step S02: storing at least one internal reference information in a storage circuit;

[0109] Step S03: using an estimation circuit to determine and select an operation model according to the control parameter signal to be estimated and at least one battery characteristic signal or at least one internal reference information, wherein the operation model defines the control parameter and the state parameter, and defines the relationship between the control parameter and the state parameter; and

[0110] Step S04: using the estimation circuit to perform at least one round of estimation operation to generate an estimation result.

[0111] Figure 4 FIG. 1 is an operation flow chart showing an estimation operation in one embodiment of the present invention. Figure 4 As shown, the estimation operation includes:

[0112] Step S11: dividing the limited range of the control parameter into a plurality of sections to generate a plurality of corresponding control parameter values;

[0113] Step S12: inputting a plurality of control parameter values ​​into the operation model in sequence according to the sequence direction parameter to generate a plurality of corresponding state parameter values;

[0114] Step S13: after each state parameter value is generated, check whether the corresponding judgment object meets the judgment condition;

[0115] Step S131: when the judgment object satisfies the judgment condition, determining the estimation result and ending at least one round of estimation operation;

[0116] Step S132: When all the multiple judgment objects corresponding to the multiple state parameter values ​​do not meet the judgment conditions, the two control parameter values ​​corresponding to the two state parameter values ​​that first cross the target value of the state parameter are used to define the limited range of the next round of estimation operation according to the multiple judgment objects, and the next round of estimation operation is performed.

[0117] In a more specific embodiment, according to the control parameter signal to be estimated EST, the control parameter may be the depth of discharge (DOD), and the state parameter may be the battery voltage Vbat. The operation model selection parameter of the control parameter signal to be estimated EST, for example, indicates the estimation of the corresponding discharge depth when the battery voltage Vbat is equal to the discharge cut-off voltage threshold. The first round starting point of the control parameter signal to be estimated EST, for example, is the current discharge depth. The first round end point of the control parameter signal to be estimated EST, for example, is the upper limit of the discharge depth. The battery characteristic signal corresponding to the operation model includes, for example, the battery voltage Vbat, the battery temperature Tbat and the discharge current Ibat; the internal reference information corresponding to the operation model includes the discharge depth, the open circuit voltage (OCV) corresponding to the discharge depth characteristic table and the battery internal resistance corresponding to the open circuit voltage and the battery temperature characteristic table; the sequential direction parameter indicates the direction in which the current discharge depth increases toward the upper limit of the discharge depth, that is, the sequential direction indicates the direction in which the discharge depth increases. The estimation circuit 20 determines the operation model according to the control parameter signal to be estimated EST, the corresponding battery characteristic signal and the internal reference information. The relevant description will be described in detail later.

[0118] In one embodiment, the control parameter may be the charging time, the state parameter may be the battery temperature Tbat, the estimated control parameter signal EST indicates the estimated charging time corresponding to the battery temperature Tbat being equal to the charging cut-off temperature threshold; wherein at least one of the battery characteristics corresponding to the operation model includes the battery temperature Tbat; wherein at least one of the internal reference information corresponding to the operation model includes a battery temperature corresponding to the charging time characteristic table; wherein the first round starting point includes the upper limit charging time point, the first round end point includes the current charging time point, and wherein the sequence direction includes the charging time decreasing direction. wherein the estimation circuit 20 determines the operation model according to the estimated control parameter signal EST, the corresponding battery characteristic signal and the internal reference information. the relevant description will be described in detail later. the relevant description will be described in detail later.

[0119] FIG. 5A to FIG. 5D This is a more specific embodiment of a battery control parameter estimation method according to the present invention. This embodiment shows a battery control parameter estimation method for estimating the discharge depth corresponding to when the battery voltage is equal to the discharge cut-off voltage threshold Vtrg. Figure 5A Schematic diagram showing the characteristics of the battery reference internal resistance Rstd at different discharge depths DOD. Figure 5A The change of the characteristic curve shows that the functional relationship between the reference internal resistance Rstd and the discharge depth DOD is not only nonlinear but also non-monotonic, indicating that there may be several discharge depth DOD solutions that all meet the condition of being equal to the discharge cut-off voltage threshold Vtrg. Among them, the battery reference internal resistance Rstd refers to the battery internal resistance without load (when the battery is open circuit) at 25 degrees Celsius. Figure 5B As shown, when the battery voltage is equal to the discharge cut-off voltage threshold Vtrg, this operation model contains three sets of discharge depth DOD solutions, namely, discharge depth DOD1, DOD2, and DOD3. Because the function corresponding to this operation model is not a 1-to-1 monotonic function, it must be solved in the form of scanning. In this embodiment, the minimum value of the discharge depth DOD is set as the solution target, the purpose is to find the discharge depth DOD that reaches the discharge cut-off voltage threshold Vtrg the earliest, that is, the discharge depth DOD1 closest to the discharge depth DODpr is the target solution.

[0120] Figure 5B Displays the relationship between the battery's discharge depth DOD, battery voltage Vbat, and open circuit voltage OCV. Figure 5B As shown, in this embodiment, when the discharge depth DOD is higher, the open circuit voltage OCV is lower. However, between the battery voltage Vbat and the open circuit voltage OCV, the influence of the battery current Ibat and the battery internal resistance R must also be considered.

[0121] In this embodiment, the control parameter is the discharge depth DOD, the state parameter is the battery voltage Vbat, and the control parameter signal to be estimated EST indicates the estimated discharge depth DOD when the battery voltage Vbat is equal to the discharge cut-off voltage threshold Vtrg; wherein at least one of the battery characteristics corresponding to the operation model includes the battery voltage Vbat, the battery temperature Tbat and the discharge current Ibat; wherein at least one of the internal reference information corresponding to the operation model includes the open circuit voltage corresponding to the discharge depth characteristic table and the battery internal resistance corresponding to the open circuit voltage and the battery temperature characteristic table; wherein the sequence direction includes the discharge depth increasing direction. In this embodiment, the starting point of the first round is the current discharge depth DODpr; the end point of the first round is the upper limit of the discharge depth DODup. Generally speaking, the upper limit of the discharge depth DODup is 100%. That is to say, in this embodiment, the operation model is the functional relationship between the discharge depth DOD and the battery voltage Vbat under specific conditions. wherein, in this embodiment, the specific conditions are, for example, a specific battery temperature Tbat, a specific battery current Ibat and a specific battery internal resistance.

[0122] Figure 5C The depth of discharge DOD of the battery is replaced by the control parameter x, and the battery voltage Vbat is replaced by the state parameter y. The sequential direction parameter indicates that the sequential direction is the increasing direction of the control parameter x, which represents the increasing direction of the control parameter x. The first time the judgment condition is met is the solution. The starting point of the first round is the starting point Str1, and the end point of the first round is the end point End1. The range between the starting point Str1 and the end point End1 is a limited range. The limited range is further divided into multiple sections, and each section has a fixed preset section interval Prd1. For example but not limited to Figure 5CAs shown, the area between the starting point Str1 and the end point End1 is divided into 5 sections, and corresponding 6 control parameter values ​​Xm1, Xm2, Xm3, Xm4, Xm5, and Xm6 are generated in a sequential direction. The estimation operation inputs the control parameter values ​​Xm1, Xm2, Xm3, Xm4, Xm5, and Xm6 into the corresponding operation model in a sequential direction, and correspondingly generates 6 state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6 of the state parameter y of the operation model; after each generation of one of the state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6, one of the multiple state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6 is also compared with the target value, which is the discharge cut-off voltage threshold Vtrg, and multiple comparison results are generated in sequence, and the estimation circuit sequentially determines whether the multiple comparison results meet the judgment conditions.

[0123] In one embodiment, the multiple judgment objects are, for example, multiple state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6, and the judgment conditions include, for example, but not limited to, node judgment conditions. The node judgment condition is, for example, that the difference between one of the state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6 and the discharge cut-off voltage threshold value Vtrg is lower than the first preset difference. If the judgment object (one of the state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6) satisfies the node judgment condition (the difference between the state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6 and the discharge cut-off voltage threshold value Vtrg is lower than the first preset difference), it indicates that the node judgment condition is satisfied, and the estimation circuit 20 uses the control parameter value (one of Xm1, Xm2, Xm3, Xm4, Xm5, and Xm6) corresponding to the state parameter value that satisfies the node judgment condition as the estimation result, and ends the estimation operation. That is to say, the control parameter values ​​Xm1, Xm2, Xm3, Xm4, Xm5, and Xm6 are sequentially input into the operation model, and the six state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6 of the state parameter y of the operation model are generated correspondingly, and the state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6 are sequentially compared with the discharge cut-off voltage threshold Vtrg in real time, and corresponding differences are sequentially generated. Once the difference is lower than the first preset difference, an estimation result is generated, and the subsequent control parameter values ​​are stopped from being input into the operation model.

[0124] In another embodiment, the multiple judgment objects are, for example, multiple state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6, and multiple sections defined by them, for example, the state parameter values ​​Ym1 and Ym2 define the first section, the state parameter values ​​Ym2 and Ym3 define the second section, and so on. The judgment condition is, for example, a section judgment condition. The section judgment condition includes, for example but not limited to: the difference between the two state parameter values ​​before and after the first crossing of the target value is lower than the second preset difference, or the difference between the two control parameter values ​​corresponding to the two state parameter values ​​is lower than the third preset difference. When one of the multiple segments satisfies the piecewise linear condition, two control parameter values ​​corresponding to the segment judgment condition, i.e., two continuous control parameter values ​​among the control parameter values ​​Xm1, Xm2, Xm3, Xm4, Xm5, and Xm6, and two continuous state parameter values ​​among the corresponding two state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6, are linearly interpolated, and the control parameter values ​​obtained by the linear interpolation are obtained as the estimation result. Once the estimation result is generated, the subsequent control parameter values ​​are stopped from being continuously input into the operation model.

[0125] In this embodiment, for example, Figure 5C In the first round of estimation operation shown, multiple state parameter values ​​do not meet the node judgment condition. The estimation circuit will define the next limited range by the two control parameter values ​​corresponding to the two consecutive state parameter values ​​before and after the target value (i.e., the discharge cut-off voltage threshold Vtrg), i.e., the state parameter values ​​Ym2 and Ym3, i.e., the control parameter values ​​Xm2 and Xm3, and then perform the next round of estimation operation, including dividing the new limited range defined by the control parameter values ​​Xm2 and Xm3 into multiple sections and then inputting the operation model, checking whether the corresponding judgment objects meet the judgment conditions one by one, until the judgment conditions are met and the estimation result is generated, as shown in FIG. Figure 5D shown.

[0126] Figure 5D show Figure 5C In the first round of estimation operation shown, multiple state parameter values ​​Ym1, Ym2, Ym3, Ym4, Ym5, and Ym6 do not meet the node judgment condition. Therefore, the two control parameter values ​​Xm2 and Xm3 corresponding to the two consecutive state parameter values ​​Ym2 and Ym3 before and after the discharge cut-off voltage threshold Vtrg are used to define the limited range of the next round of estimation operation, that is, the new limited range. The new starting point is the starting point Str2, and the new end point is the end point End2. The range between the starting point Str2 and the end point End2 is the new limited range. The new limited range is further divided into multiple sections, and each section has a new fixed preset section interval Prd2. For example, but not limited to, Figure 5DAs shown, the area between the starting point Str2 and the end point End2 is divided into 6 sections, and corresponding 7 control parameter values ​​Xn1, Xn2, Xn3, Xn4, Xn5, Xn6, and Xn7 are generated in a sequential direction. The estimation operation inputs the control parameter values ​​Xn1, Xn2, Xn3, Xn4, Xn5, Xn6, and Xn7 into the operation model in a sequential direction, and the 7 state parameter values ​​Yn1, Yn2, Yn3, Yn4, Yn5, Yn6, and Yn7 corresponding to the state parameter y of the operation model are used as new judgment objects; and the multiple state parameter values ​​Yn1, Yn2, Yn3, Yn4, Yn5, Yn6, and Yn7 are compared one by one with the target value, that is, the discharge cut-off voltage threshold Vtrg, to generate multiple new comparison results, and sequentially judge whether the multiple comparison results meet the node judgment conditions.

[0127] The node judgment condition includes, for example but not limited to, the difference between one of the state parameter values ​​Yn1, Yn2, Yn3, Yn4, Yn5, Yn6, and Yn7 and the discharge cut-off voltage threshold value Vtrg being lower than the first preset difference. If the judgment object (one of the state parameter values ​​Yn1, Yn2, Yn3, Yn4, Yn5, and Yn6) satisfies the node judgment condition (the difference between the state parameter values ​​Yn1, Yn2, Yn3, Yn4, Yn5, and Yn6 and the discharge cut-off voltage threshold value Vtrg is lower than the first preset difference), it indicates that the node judgment condition is satisfied, and the estimation circuit 20 uses the control parameter value (one of Xn1, Xn2, Xn3, Xn4, Xn5, and Xn6) corresponding to the state parameter value that satisfies the node judgment condition as the estimation result, and ends the estimation operation. That is to say, the control parameter values ​​Xn1, Xn2, Xn3, Xn4, Xn5, Xn6, and Xn7 are sequentially input into the operation model, and the seven state parameter values ​​Yn1, Yn2, Yn3, Yn4, Yn5, Yn6, and Yn7 of the state parameter y of the operation model are generated accordingly, and the state parameter values ​​Yn1, Yn2, Yn3, Yn4, Yn5, Yn6, and Yn7 are sequentially compared with the discharge cut-off voltage threshold Vtrg in real time, and corresponding differences are sequentially generated. Once the difference is lower than the first preset difference, an estimation result is generated, and the control parameter values ​​Xn1, Xn2, Xn3, Xn4, Xn5, Xn6, and Xn7 are stopped from being input into the operation model.

[0128] For example, in this embodiment, the difference between the state parameter value Yn6 and the discharge cut-off voltage threshold value Vtrg is lower than the first preset difference, which satisfies the node judgment condition, that is, generates an estimation result, determines that the discharge depth corresponding to the battery voltage Vbat equals the discharge cut-off voltage threshold value Vtrg is the control parameter value Xn6, and stops inputting the control parameter value Xn7, and continues to input the operation model, without generating the state parameter value Yn7. In addition, in this embodiment, if Figure 5DAs shown, since the state parameter value Yn1 is equal to the state parameter value Ym2, the state parameter value Yn7 is equal to the state parameter value Ym3, the control parameter value Xn1 is equal to the control parameter value Xm2, and the control parameter value Xn7 is equal to the control parameter value Xm3; in the second round of estimation operation, the control parameter values ​​and state parameter values ​​of the first round mentioned above are directly used as the control parameter values ​​and state parameter values ​​corresponding to the second round, which can also save the time required to calculate the difference between the state parameter values ​​Yn1 and Yn7.

[0129] For ease of understanding, in this embodiment, although the control parameter is a single variable, namely the depth of discharge DOD, other parameters, such as the discharge current Ibat, the battery internal resistance R and the battery temperature Tbat, are all specific conditions. However, the present invention is not limited to this. According to the present invention, the control parameter may also include multiple parameters, for example, the control parameter includes the discharge current Ibat, the battery internal resistance R and the battery temperature Tbat in addition to the depth of discharge DOD. It is only necessary to change the current battery state, that is, the starting point of the first round of the estimation operation, to the control parameters corresponding to the current depth of discharge DODpr, the current discharge current, the current battery internal resistance and the current battery temperature, and the state parameter is still the battery voltage Vpr. The target value is still set to the discharge cut-off voltage threshold Vtrg. In other words, the present invention can be extended to applications where multiple control parameters are solved. In addition, the functional relationship between the battery voltage Vbat and the depth of discharge DOD, the discharge current Ibat, the battery internal resistance R and the battery temperature Tbat, that is, the operation model, is: battery voltage Vbat = function f (DOD, Ibat, R, Tbat). Therefore, after adding the relationship between the open circuit voltage OCV, the battery current Ibat and the battery internal resistance R, for example, the relationship can be obtained: Vbat = OCV (DOD) + Ibat R(DOD, Tbat).

[0130] To further illustrate, estimating the battery state where the battery voltage Vbat is equal to the discharge depth DOD corresponding to the discharge cut-off voltage threshold Vtrg can be regarded as solving the function f(DOD, Ibat, R, Tbat) = Vtrg. The subsequent steps include checking whether the corresponding judgment object meets the judgment condition, determining the estimation result when the judgment object meets the judgment condition, and ending at least one round of estimation operation, and when all multiple judgment objects corresponding to multiple state parameter values ​​do not meet the judgment condition, based on multiple judgment objects, the two control parameter values ​​corresponding to the two state parameter values ​​that first cross the target value of the state parameter are used to define the limited range of the next round of estimation operation, and perform the next round of estimation operation; all of which are the same as the aforementioned FIG. 5A to FIG. 5D The embodiment shown is similar except that more control variables are added for calculation, which will not be described in detail here.

[0131] Fig. 6A and Figure 6B This is another more specific embodiment of the method for estimating battery control parameters according to the present invention. This embodiment is a method for estimating battery control parameters when charging starts at room temperature of 25 degrees and displays the charging time Time_chg corresponding to the estimated battery temperature Tbat being equal to the charging cut-off temperature threshold Ttrg.

[0132] Fig. 6A and Figure 6B Displays the relationship between the battery charging time Time_chg and the battery temperature Tbat. Fig. 6A and Figure 6B As shown, the battery state corresponds to the control parameter (x-axis) as the charging time Time_chg, and the state parameter (y-axis) as the battery temperature Tbat. The target value is set as the charging cut-off temperature threshold Ttrg. In this embodiment, the functional relationship between the battery temperature Tbat and the charging time Time_chg, that is, the operation model, is: battery voltage battery temperature Tbat = function f (Time_chg).

[0133] The battery temperature Tbat = function f (Time_chg), where the relationship between some parameters and the internal parameter table can be roughly expressed as: Ichg1 = Ichg_cc, Ichg2 = (Vchg-OCV (SOC)) / Res (Tbat, SOC), SOC = (SOC Cap+ Ichg Time_chg) / Cap,Tbat_delta= (Ichg^2 Res (Tbat, SOC) Qres. Among them, Ichg_cc is the current value of constant current charging mode, Ichg2 is the current value of constant voltage charging, Ichg is the actual charging current, which is the smaller of Ichg1 and Ichg2, Cap is the battery capacity, Res is the battery internal resistance, Qres is the thermal resistance of the battery to dissipate heat, Tbat_delta is the battery temperature change, and the battery temperature Tbat will be superimposed on the ambient temperature. Combining the above parameters, iterative calculation can establish a parameter table of battery charging time and battery temperature change.

[0134] In this embodiment, the estimated battery temperature Tbat is equal to the charging time Time_chg corresponding to the charging cut-off temperature threshold Ttrg, that is, solving the function f(Time_chg) = Trg. Fig. 6AAs shown, this function contains two sets of solutions. Because this function is not a 1-to-1 monotonic function, it must be solved in a scanning form. In this embodiment, the maximum value of the charging time Time_chg is set as the solution target, and the purpose is to find the charging time Time_chg that reaches the charging cut-off temperature threshold Ttrg at the latest.

[0135] In this embodiment, the control parameter is the charging time Time_chg, the state parameter is the battery temperature Tbat, and the control parameter signal to be estimated indicates that the battery temperature Tbat is equal to the charging time Time_chg corresponding to the charging cut-off temperature threshold Ttrg; wherein at least one of the battery characteristics corresponding to the operation model includes the battery temperature Tbat; wherein at least one of the internal reference information corresponding to the operation model includes a battery temperature corresponding to the charging time characteristic table; wherein the sequence direction includes the decreasing direction of the charging time Time_chg. wherein the multiple judgment objects are multiple state parameter values. wherein the judgment condition is the node judgment condition corresponding to the judgment object.

[0136] The present invention can be used in various practical applications according to the needs of users. For example, in this embodiment, a parameter table of battery charging time and battery temperature change can be established by calculation, which becomes a corresponding table of charging time and battery temperature change in the complete charging process. For example, in a practical application of the present embodiment, the starting point of the first round of estimation is the longest charging time in the corresponding table (until the battery is fully charged or even overcharged), and the battery state of charge and battery OCV comparison table can be combined to calculate the charging time corresponding to the current battery power (state of charge) as the first round of estimation end point. After the charging time at which the temperature reaches the charging cut-off temperature threshold Ttrg is obtained from the estimation result, the charging time corresponding to the current battery power can be subtracted from the estimation result, and the calculated result is the remaining time required to properly charge the battery. This practical application also illustrates a practical application method of how to select the first round of estimation starting point and the first round of estimation end point in this embodiment.

[0137] Fig. 6A The battery charging time Time_chg is replaced by the control parameter x, and the battery temperature Tbat is replaced by the state parameter y. The sequential direction parameter indicates that the sequential direction is the decreasing control parameter, which means that the control parameter x decreases and the first time the judgment condition is met is the solution. The starting point of the first round is the starting point Str3, and the end point of the first round is the end point End3. The range between the starting point Str3 and the end point End3 is a limited range. The limited range is further divided into multiple sections, and each section has a fixed preset section interval Prd3. For example, but not limited to Fig. 6AAs shown, the area between the starting point Str3 and the end point End3 is divided into 5 sections, generating 6 corresponding control parameter values ​​Xp1, Xp2, Xp3, Xp4, Xp5, and Xp6 marked in the order direction. The estimation operation inputs the control parameter values ​​Xp1, Xp2, Xp3, Xp4, Xp5, and Xp6 into the corresponding operation model, i.e., the function f (Time_chg), and the 6 state parameter values ​​Yp1, Yp2, Yp3, Yp4, Yp5, and Yp6 corresponding to the state parameter y of the operation model are the judgment objects; at the same time, multiple state parameter values ​​Yp1, Yp2, Yp3, Yp4, Yp5, and Yp6 are compared with the target value, i.e., the charging cut-off temperature threshold Ttrg, to generate multiple comparison results, and determine whether the multiple comparison results meet the node judgment conditions.

[0138] The node judgment condition includes, for example but not limited to, the difference between one of the state parameter values ​​Yp1, Yp2, Yp3, Yp4, Yp5, Yp6 and the charging cut-off temperature threshold Ttrg being lower than a first preset difference. When the judgment object satisfies the node judgment condition, it is decided to use one of the corresponding control parameter values ​​Xp1, Xp2, Xp3, Xp4, Xp5, Xp6 as the estimation result. That is to say, the control parameter values ​​Xp1, Xp2, Xp3, Xp4, Xp5, and Xp6 are sequentially input into the function f (Time_chg), and the corresponding 6 state parameter values ​​Yp1, Yp2, Yp3, Yp4, Yp5, and Yp6 of the state parameter y of the operation model are generated, and the state parameter values ​​Yp1, Yp2, Yp3, Yp4, Yp5, and Yp6 are sequentially compared with the charging cut-off temperature threshold Ttrg in real time, and the corresponding differences are sequentially generated. Once the difference is lower than the first preset difference, it means that the judgment object meets the node judgment condition, the estimation result is determined, and at least one round of estimation operation is terminated, and the subsequent control parameter values ​​are stopped from continuing to be input into the operation model, including the calculation of the function f (Time_chg).

[0139] Another judgment condition includes, for example but not limited to: multiple judgment objects are multiple segments; the judgment condition is a segment judgment condition corresponding to the judgment object. When one of the segments satisfies the segment judgment condition, such as a piecewise linear condition, the two control parameter values ​​corresponding to the segment, that is, two continuous control parameter values ​​among the control parameter values ​​Xp1, Xp2, Xp3, Xp4, Xp5, and Xp6, and the two continuous state parameter values ​​among the corresponding two state parameter values ​​Yp1, Yp2, Yp3, Yp4, Yp5, and Yp6 are linearly interpolated to obtain a linear interpolation node as an estimation result. In other words, the estimation circuit 20 performs linear interpolation on the two control parameter values ​​corresponding to the segment and the two state parameter values ​​corresponding to the segment, and determines the estimation result according to the control parameter values ​​obtained by the linear interpolation, and ends the at least one round of estimation operation. The piecewise linear condition includes that the difference between the two continuous control parameter values ​​is lower than the second preset difference, or the difference between the two control parameter values ​​corresponding to the two state parameter values ​​is lower than the third preset difference. Once the difference is lower than the second preset difference or the third preset difference, the estimation result is determined, and the subsequent control parameter values ​​are stopped from being input into the operation model, including the calculation of the function f(Time_chg).

[0140] In this embodiment, for example, Fig. 6A In the first round of estimation operation shown, multiple state parameter values ​​do not meet the judgment condition. The estimation circuit defines the next limited range by the two control parameter values ​​corresponding to the two consecutive state parameter values ​​before and after the target value (i.e., the charging cut-off temperature threshold Ttrg), i.e., the state parameter values ​​Yp1, Yp2, i.e., the control parameter values ​​Xp1, Xp2, and repeats the above steps, including dividing the limited range into multiple segments and the subsequent input functions, comparison and judgment steps, until the judgment condition is met and the estimation result is generated, as shown in FIG. Figure 6B shown.

[0141] Figure 6B show Fig. 6A In the first round of estimation operation shown, multiple state parameter values ​​Yp1, Yp2, Yp3, Yp4, Yp5, and Yp6 do not meet the judgment conditions. Therefore, the two control parameter values ​​Xp1 and Xp2 corresponding to the two consecutive state parameter values ​​Yp1 and Yp2 before and after the first crossing of the charging cut-off temperature threshold Ttrg are used to define the next limited range, that is, the new limited range. The new starting point is the starting point Str4, and the new end point is the end point End4. The range between the starting point Str4 and the end point End4 is the new limited range. The new limited range is further divided into multiple sections, and each section has a new fixed preset section interval Prd4. For example but not limited to Figure 6BAs shown, the area between the starting point Str4 and the end point End4 is divided into 5 sections, generating 6 corresponding control parameter values ​​Xq1, Xq2, Xq3, Xq4, Xq5, and Xq6 marked in the order direction. The estimation operation inputs the control parameter values ​​Xq1, Xq2, Xq3, Xq4, Xq5, and Xq6 into the operation model, i.e., the function f (Time_chg), and generates 6 state parameter values ​​Yq1, Yq2, Yq3, Yq4, Yq5, and Yq6 of the state parameter y of the operation model in the order direction; at the same time, multiple state parameter values ​​Yq1, Yq2, Yq3, Yq4, Yq5, and Yq6 are compared with the target value, i.e., the charging cut-off temperature threshold Ttrg, to generate multiple comparison results, and determine whether the multiple comparison results meet the judgment conditions.

[0142] The judgment conditions include, for example but not limited to, the difference between one of the state parameter values ​​Yq1, Yq2, Yq3, Yq4, Yq5, Yq6 and the charging cut-off temperature threshold Ttrg being lower than a first preset difference, i.e., taking one of the corresponding control parameter values ​​Xq1, Xq2, Xq3, Xq4, Xq5, Xq6 as the estimation result. That is to say, the control parameter values ​​Xq1, Xq2, Xq3, Xq4, Xq5, and Xq6 are sequentially input into the function f (Time_chg), and the six state parameter values ​​Yq1, Yq2, Yq3, Yq4, Yq5, and Yq6 of the state parameter y of the operation model are generated accordingly, and the state parameter values ​​Yq1, Yq2, Yq3, Yq4, Yq5, and Yq6 are sequentially compared with the charging cut-off temperature threshold Ttrg in real time, and corresponding differences are sequentially generated. Once the difference is lower than the first preset difference, an estimation result is generated, and the control parameter values ​​Xq1, Xq2, Xq3, Xq4, Xq5, and Xq6 are stopped from being input into the function f (Time_chg).

[0143] For example, in this embodiment, the difference between the state parameter value Yq3 and the charging cut-off temperature threshold value Ttrg is lower than the first preset difference, that is, an estimation result is generated, and the charging time Time_chg is determined to be equal to the charging time corresponding to the charging cut-off temperature threshold value Ttrg as the control parameter value Xq3, and the control parameter values ​​Xq4, Xq5, and Xq6 are stopped from being input into the function f (Time_chg), and the state parameter values ​​Yq4, Yq5, and Yq6 do not need to be generated.

[0144] It should be noted that Figure 5A-5D and Figure 6A-6B These are two implementations according to the present invention, but the present invention is not limited thereto. Other battery control parameter estimation methods can also be implemented according to the present invention.

[0145] 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 battery control parameter estimation system, comprising: a sensing circuit for sensing at least one battery characteristic and generating at least one corresponding battery characteristic signal; a storage circuit for storing at least one internal reference information; as well as An estimation circuit is provided for: Determine an operation model according to a control parameter signal to be estimated and the at least one battery characteristic signal or the at least one internal reference information, wherein the operation model defines a control parameter and a state parameter, and defines a relationship between the control parameter and the state parameter; as well as Perform at least one round of estimation operation to generate an estimation result; The estimation operation includes: (a) dividing a limited range of the control parameter into a plurality of segments to generate a corresponding plurality of control parameter values; (b) inputting the plurality of control parameter values ​​into the operation model in sequence according to a sequence direction parameter to generate a plurality of corresponding state parameter values; (c) after each time the state parameter value is generated, checking whether a corresponding judgment object satisfies a judgment condition; (d) when the judgment object satisfies the judgment condition, determining the estimation result and ending the at least one round of estimation operation; and (e) when all the judgment objects corresponding to the plurality of state parameter values ​​do not satisfy the judgment condition, defining, according to the plurality of judgment objects, two control parameter values ​​corresponding to two state parameter values ​​that first cross a target value of the state parameter as a limited range for a next round of estimation operation, and performing the next round of estimation operation; The multiple judgment objects are the multiple state parameter values ​​or the multiple segments; The judgment condition is a node judgment condition or a segment judgment condition corresponding to the judgment object.

2. The battery control parameter estimation system according to claim 1, wherein: The at least one internal reference information includes a battery electrical characteristic table, an operation record, a calculation parameter and / or a counting time.

3. The battery control parameter estimation system according to claim 1, wherein: The at least one battery characteristic includes a battery voltage, a battery current and / or a battery temperature.

4. The battery control parameter estimation system according to claim 1, wherein: The control parameter is defined according to one of the at least one battery characteristic signal or one of the at least one internal reference information.

5. The battery control parameter estimation system according to claim 1, wherein: The state parameter is defined according to one of the at least one battery characteristic signal or one of the at least one internal reference information.

6. The battery control parameter estimation system according to claim 1, wherein: The control parameter signal to be estimated includes an operation model selection parameter, the sequence direction parameter, a first round starting point and a first round end point; The operation model selection parameter is used to determine the corresponding operation model; The sequence direction parameter is used to indicate a sequence direction of the control parameter; The first round starting point and the first round end point define the limited range of the first round of the estimation operation.

7. The battery control parameter estimation system according to claim 1, wherein: In the same round of the estimation operation, the interval lengths of each of the plurality of segments are equal to each other.

8. The battery control parameter estimation system according to claim 1, wherein: The step (d) of the estimation operation includes: when the difference between one of the state parameter values ​​of the multiple state parameter values ​​and the target value is lower than a first preset difference, it indicates that the node judgment condition is satisfied, the estimation circuit determines the estimation result according to a control parameter value corresponding to the state parameter value, and ends the at least one round of estimation operation.

9. The battery control parameter estimation system according to claim 1, wherein: The step (d) of the estimation operation includes: when one of the multiple segments satisfies a piecewise linear condition, indicating that the segment judgment condition is satisfied, the estimation circuit performs linear interpolation with two control parameter values ​​corresponding to the segment and two state parameter values ​​corresponding to the segment, and determines the estimation result according to a control parameter value obtained by the linear interpolation, and ends the at least one round of estimation operation.

10. The battery control parameter estimation system according to claim 9, wherein: The piecewise linear condition includes: the difference between two state parameter values ​​before and after the first crossing of the target value is lower than a second preset difference, or the difference between two control parameter values ​​corresponding to the two state parameter values ​​is lower than a third preset difference.

11. The battery control parameter estimation system according to claim 6, wherein: The control parameter is a discharge depth, and the state parameter is a battery voltage; The operation model selection parameter indicates estimating the discharge depth corresponding to when the battery voltage is equal to a discharge cut-off voltage threshold; The sequential direction parameter indicates an increasing direction of the discharge depth; The first round starting point is a current discharge depth; The first round endpoint is an upper limit of the discharge depth; The at least one battery characteristic signal corresponding to the operation model includes the battery voltage, a battery temperature and a battery current; The at least one internal reference information corresponding to the operation model includes the discharge depth, a characteristic table of open circuit voltage corresponding to discharge depth, and a characteristic table of battery internal resistance corresponding to discharge depth and battery temperature.

12. The battery control parameter estimation system according to claim 6, wherein: The control parameter is a charging time, and the state parameter is a battery temperature; The operation model selection parameter indicates estimating the charging time corresponding to the battery temperature being equal to a charging cut-off temperature threshold; The sequential direction parameter indicates a decreasing direction of charging time; The starting point of the first round is an upper limit charging time point; The first round endpoint is a current charging time point; The at least one battery characteristic signal corresponding to the operation model includes the battery temperature; The at least one internal reference information corresponding to the operation model includes a battery temperature corresponding to charging time characteristic table and a counting time.

13. A battery control parameter estimation method, comprising: Using a sensing circuit to sense at least one battery characteristic to generate at least one corresponding battery characteristic signal; Storing at least one internal reference information in a storage circuit; Using an estimation circuit, according to a control parameter signal to be estimated and the at least one battery characteristic signal or the at least one internal reference information, an operation model is determined, wherein the operation model defines a control parameter and a state parameter, and defines a relationship between the control parameter and the state parameter; as well as Using the estimation circuit, performing at least one round of estimation operation to generate an estimation result; The estimation operation includes: (a) dividing a limited range of the control parameter into a plurality of segments to generate a corresponding plurality of control parameter values; (b) inputting the plurality of control parameter values ​​into the operation model in sequence according to a sequence direction parameter to generate a plurality of corresponding state parameter values; (c) after each time the state parameter value is generated, checking whether a corresponding judgment object satisfies a judgment condition; (d) when the judgment object satisfies the judgment condition, determining the estimation result and ending the at least one round of estimation operation; and (e) when all the judgment objects corresponding to the plurality of state parameter values ​​do not satisfy the judgment condition, defining, according to the plurality of judgment objects, two control parameter values ​​corresponding to two state parameter values ​​that first cross a target value of the state parameter as a limited range for a next round of estimation operation, and performing the next round of estimation operation; The multiple judgment objects are the multiple state parameter values ​​or the multiple segments; The judgment condition is a node judgment condition or a segment judgment condition corresponding to the judgment object.

14. The battery control parameter estimation method according to claim 13, wherein: The at least one internal reference information includes a battery electrical characteristic table, an operation record, a calculation parameter and / or a counting time.

15. The battery control parameter estimation method according to claim 13, wherein: The at least one battery characteristic includes a battery voltage, a battery current and / or a battery temperature.

16. The battery control parameter estimation method according to claim 13, wherein: The control parameter includes one of the at least one battery characteristic signal or one of the at least one internal reference information.

17. The battery control parameter estimation method according to claim 13, wherein: The state parameter includes one of the at least one battery characteristic signal or one of the at least one internal reference information.

18. The battery control parameter estimation method according to claim 13, wherein: The control parameter signal to be estimated includes an operation model selection parameter, the sequence direction parameter, a first round starting point and a first round end point; The operation model selection parameter is used to determine the corresponding operation model; The sequence direction parameter is used to indicate a sequence direction of the control parameter; The first round starting point and the first round end point define the limited range of the first round of the estimation operation.

19. The battery control parameter estimation method according to claim 13, wherein: In the same round of the estimation operation, the interval lengths of each of the plurality of segments are equal to each other.

20. The battery control parameter estimation method according to claim 13, wherein: The step (d) of the estimation operation includes: when the difference between one of the state parameter values ​​of the multiple state parameter values ​​and the target value is lower than a first preset difference, it indicates that the node judgment condition is satisfied, the estimation circuit determines the estimation result according to a control parameter value corresponding to the state parameter value, and ends the at least one round of estimation operation.

21. The battery control parameter estimation method according to claim 13, wherein: The step (d) of the estimation operation includes: when one of the multiple segments satisfies a piecewise linear condition, indicating that the segment judgment condition is satisfied, the estimation circuit performs linear interpolation with two control parameter values ​​corresponding to the segment and two state parameter values ​​corresponding to the segment, and determines the estimation result according to a control parameter value obtained by the linear interpolation, and ends the at least one round of estimation operation.

22. The battery control parameter estimation method according to claim 21, wherein: The piecewise linear condition includes: the difference between two state parameter values ​​before and after the first crossing of the target value is lower than a second preset difference, or the difference between two control parameter values ​​corresponding to the two state parameter values ​​is lower than a third preset difference.

23. The battery control parameter estimation method according to claim 18, wherein: The control parameter is a discharge depth, and the state parameter is a battery voltage; The operation model selection parameter indicates estimating the discharge depth corresponding to when the battery voltage is equal to a discharge cut-off voltage threshold; The sequential direction parameter indicates an increasing direction of the discharge depth; The first round starting point includes a current discharge depth; The first round endpoint is related to an upper limit of the discharge depth; The at least one battery characteristic signal corresponding to the operation model includes the battery voltage, a battery temperature and a battery current; The at least one internal reference information corresponding to the operation model includes the discharge depth, a characteristic table of open circuit voltage corresponding to discharge depth, and a characteristic table of battery internal resistance corresponding to discharge depth and battery temperature.

24. The battery control parameter estimation method according to claim 18, wherein: The control parameter is a charging time, and the state parameter is a battery temperature; The operation model selection parameter indicates estimating the charging time corresponding to the battery temperature being equal to a charging cut-off temperature threshold; The sequential direction parameter includes a charging time decreasing direction; The first round starting point includes an upper limit charging time point; The first round endpoint includes a current charging time point; The at least one battery characteristic signal corresponding to the operation model includes the battery temperature; The at least one internal reference information corresponding to the operation model includes a battery temperature corresponding to charging time characteristic table and a counting time.

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