Intelligent determination method and device for battery charging demand current

Abstract

The application discloses a kind of intelligent determination method and device of battery charging demand current, the method includes: based on the historical open-circuit voltage parameter of pre-set battery and historical ohmic resistance parameter, determine the current open-circuit voltage parameter of battery and current ohmic resistance parameter;Based on current open-circuit voltage parameter and current ohmic resistance parameter, calculate the current charging current limit of battery;Based on current charging current limit, determine the current charging demand current of battery. Visible, the charging current limit of battery can be calculated in real time by implementing the application, to evaluate the charging limit capacity of battery, and determine the charging demand current of battery, so that the reliability and accuracy of the charging demand current determined can be improved, and then the vehicle battery can be reliably and accurately charged, so that the charging safety and charging efficiency of vehicle battery can be improved, to realize the good charging effect of vehicle battery.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle battery charging, in particular to a method and device for intelligently determining battery charging demand current. BACKGROUND

[0002] With the rapid development of new energy vehicles, people's requirements for the charging effect of vehicle batteries are getting higher and higher. Only when the vehicle battery achieves good charging effect, the new energy vehicle can be normally started and smoothly run.

[0003] Currently, the charging method for vehicle batteries generally involves first importing experimental charging data to construct a Map table, and then determining the charging demand current by searching the Map table, and then sending the charging demand current to the charger to charge the vehicle battery through the charger. However, it is found through practice that in the process of charging the vehicle battery in this way, the charging limit capacity of the vehicle battery is easily ignored, and the charging limit capacity has a strong nonlinearity with temperature, working condition environment, and battery aging degree, which makes the determined charging demand current low in accuracy, and thus it is difficult to accurately charge the vehicle battery, thereby it is difficult to improve the charging safety and efficiency of the vehicle battery. Therefore, it is particularly important to provide a method for accurately determining the charging demand current of the vehicle battery. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a method and device for intelligently determining the charging demand current of a battery, which can improve the reliability and accuracy of the determined charging demand current, and thus can reliably and accurately charge the vehicle battery, thereby improving the charging safety and efficiency of the vehicle battery to achieve good charging effect of the vehicle battery.

[0005] To solve the above technical problem, the present application discloses a method for intelligently determining the charging demand current of a battery, which comprises:

[0006] Based on the preset historical open-circuit voltage parameter and historical ohmic resistance parameter of the battery at the last charging time, the current open-circuit voltage parameter and current ohmic resistance parameter of the battery at the current charging time are determined; the current charging time is the time adjacent to the last charging time;

[0007] According to the current open-circuit voltage parameter, the current ohmic resistance parameter, and the preset charging cutoff voltage of the battery, the current charging current limit value of the battery at the current charging time is calculated;

[0008] Based on the current charging current limit value, the current charging demand current of the battery at the current charging time is determined.

[0009] As an optional implementation, in the first aspect of the present application, the determination of the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time based on the preset historical open-circuit voltage parameter and the historical ohmic resistance parameter of the battery at the last charging time comprises:

[0010] determining a current information error parameter at the current charging time according to the preset historical open-circuit voltage parameter and the historical ohmic resistance parameter of the battery at the last charging time, the current battery port voltage parameter collected at the current charging time of the battery, the preset current observation matrix at the current charging time, and the preset state transition matrix;

[0011] determining a current gain parameter at the current charging time, and determining the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time according to the current information error parameter, the current gain parameter, and the state transition matrix;

[0012] wherein the current information error parameter is:

[0013] e k = U t,k - CA[U oc,k-1 ; R i,k-1 ];

[0014] U t,k is the current battery port voltage parameter, C is the current observation matrix, A is the state transition matrix, U oc,k-1 is the historical open-circuit voltage parameter, R i,k-1 is the historical ohmic resistance parameter, wherein C = [1I k ], I k is the current battery port current parameter collected at the current charging time of the battery;

[0015] and the current open-circuit voltage parameter and the current ohmic resistance parameter are calculated by the following formula:

[0016] [U oc,k ; R i,k ] = A(A[U oc,k-1 ; R i,k-1 ] + K k e k );

[0017] U oc,k is the current open-circuit voltage parameter, R i,k is the current ohmic resistance parameter, and K k is the current gain parameter.

[0018] As an optional implementation, in the first aspect of the present application, the determining of the current gain parameter at the current charging time comprises:

[0019] determining a current state error covariance parameter at the current charging time, and determining a current observation covariance parameter at the current charging time according to the current state error covariance parameter, the current information error parameter, a preset sliding window size parameter and the current observation matrix;

[0020] determining a current target state error covariance parameter at the current charging time, and determining the current gain parameter at the current charging time according to the current observation covariance parameter, the current target state error covariance parameter and the current observation matrix;

[0021] wherein the current observation covariance parameter is:

[0022]

[0023] M is the sliding window size parameter, P k is the current state error covariance parameter, wherein P k = AP k-1 A+Q k-1 , P k-1 is a preset historical state error covariance parameter at the last charging time, Q k-1 is a preset historical driving covariance parameter at the last charging time;

[0024] and the current gain parameter is:

[0025]

[0026] P +,k is the current target state error covariance parameter.

[0027] As an optional implementation, in the first aspect of the present application, the determining of the current target state error covariance parameter at the current charging time comprises:

[0028] determining the current target state error covariance parameter at the current charging time according to the current state error covariance parameter, a preset historical boundary value at the last charging time, the current observation covariance parameter, the current observation matrix and a preset current positive definite matrix at the current charging time;

[0029] wherein the current target state error covariance parameter is:

[0030] P +,k = P k(eye(n)-Thita k-1 S k +C T R k CP k ) -1 ;

[0031] Thita k-1 for the historical boundary value, S k is the preset n*n unit matrix.

[0032] As an optional implementation, in the first aspect of the present application, after the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery are determined based on the preset historical open circuit voltage parameter and historical ohmic resistance parameter of the last charging time of the battery, the method further comprises:

[0033] determining the current driving covariance parameter and the current boundary value of the current charging time for determining the target open circuit voltage parameter and the target ohmic resistance parameter of the next charging time, and triggering the operation of determining the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time based on the preset historical open circuit voltage parameter and historical ohmic resistance parameter of the last charging time of the battery based on the current driving covariance parameter and the current boundary value; the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time are the target open circuit voltage parameter and the target ohmic resistance parameter of the next charging time, respectively, and the historical open circuit voltage parameter and the historical ohmic resistance parameter of the last charging time are the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time, respectively;

[0034] wherein the current driving covariance parameter is:

[0035]

[0036] and the current boundary value is:

[0037] Thita k = λmax(eig(P +,k ))(CP k C T +R k ) -1 ;

[0038] λ is a preset adjustment proportion parameter.

[0039] As an optional implementation form, in the first aspect of the present application, the determining of the current charging demand current of the battery at the current charging time based on the current charging current limit value comprises:

[0040] determining, based on a preset target relationship table and the current battery temperature parameter and the current battery remaining capacity parameter at the current charging time of the battery, a reference charging current limit value at the current charging time of the battery from the target relationship table, which matches the current battery temperature parameter and the current battery remaining capacity parameter; the target relationship table is a preset parameter relationship table among the battery temperature parameter, the battery remaining capacity parameter and the charging current limit value of the battery;

[0041] determining a charging current limit value comparison relationship of the battery according to the reference charging current limit value and the current charging current limit value;

[0042] determining a first reference remaining capacity parameter and a second reference remaining capacity parameter of the battery based on the type parameter and the health degree parameter of the battery, and determining a remaining capacity parameter comparison relationship of the battery according to the first reference remaining capacity parameter, the second reference remaining capacity parameter and the current battery remaining capacity parameter;

[0043] determining the current charging demand current of the battery at the current charging time based on the charging current limit value comparison relationship and the remaining capacity parameter comparison relationship;

[0044] wherein the current charging demand current is:

[0045]

[0046] I max the current charging current limit value is I M the reference charging current limit value is SOC, the current battery remaining capacity parameter is SOC lim1 the first reference remaining capacity parameter is SOC lim2 the second reference remaining capacity parameter is α, and α is a preset adjustment proportion parameter of the current charging current limit value.

[0047] As an optional implementation form, in the first aspect of the present application, the current charging current limit value is:

[0048]

[0049] U oc,k the current open-circuit voltage parameter is U i,k the current ohmic resistance parameter is U chrglim the charging cutoff voltage is U.

[0050] The second aspect of the present application discloses a device for intelligently determining the charging current demand of a battery, which comprises:

[0051] a first determining module, configured to determine the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time based on the preset historical open-circuit voltage parameter and the preset historical ohmic resistance parameter of the battery at the previous charging time; the current charging time is the time adjacent to the previous charging time;

[0052] a calculating module, configured to calculate the current charging current limit value of the battery at the current charging time according to the current open-circuit voltage parameter, the current ohmic resistance parameter and the preset charging cutoff voltage of the battery;

[0053] a second determining module, configured to determine the current charging current demand of the battery at the current charging time based on the current charging current limit value.

[0054] As an optional implementation, in the second aspect of the present application, the first determining module determines the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time based on the preset historical open-circuit voltage parameter and the preset historical ohmic resistance parameter of the battery at the previous charging time in the following manner:

[0055] determines the current information error parameter at the current charging time according to the preset historical open-circuit voltage parameter and the preset historical ohmic resistance parameter of the battery at the previous charging time, the current battery port voltage parameter of the battery at the current charging time collected, the preset current observation matrix at the current charging time and the preset state transition matrix;

[0056] determines the current gain parameter at the current charging time, and determines the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time according to the current information error parameter, the current gain parameter and the state transition matrix;

[0057] wherein, the current information error parameter is:

[0058] e k = U t,k - CA [U oc,k-1 ; R i,k-1 ];

[0059] U t,k is the current battery port voltage parameter, C is the current observation matrix, A is the state transition matrix, U oc,k-1 is the historical open-circuit voltage parameter, R i,k-1U k ; R k is a current battery port current parameter of the battery at the current charging moment collected;

[0060] The current open circuit voltage parameter and the current ohmic resistance parameter are calculated by the following formula:

[0061] U oc,k ; R i,k ] = A (A [U oc,k-1 ; R i,k-1 ] + K k e k ) ;

[0062] U oc,k is the current open circuit voltage parameter, R i,k is the current ohmic resistance parameter, and K k is the current gain parameter.

[0063] As an optional implementation, in the second aspect of the present application, the manner of determining the current gain parameter at the current charging moment by the first determining module is specifically:

[0064] determining a current state error covariance parameter at the current charging moment, and determining a current observation covariance parameter at the current charging moment according to the current state error covariance parameter, the current information error parameter, a preset sliding window size parameter and the current observation matrix;

[0065] determining a current target state error covariance parameter at the current charging moment, and determining the current gain parameter at the current charging moment according to the current observation covariance parameter, the current target state error covariance parameter and the current observation matrix;

[0066] wherein the current observation covariance parameter is:

[0067]

[0068] M is the sliding window size parameter, P k is the current state error covariance parameter, wherein P k = AP k-1 A + Q k-1 , P k-1 is a preset historical state error covariance parameter at the last charging moment, and Q k-1 is a preset historical driving covariance parameter at the last charging moment;

[0069] and the current gain parameter is:

[0070]

[0071] P +,k is the current target state error covariance parameter of the current charging time.

[0072] As an optional implementation, in the second aspect, the first determining module determines the current target state error covariance parameter of the current charging time in the following manner:

[0073] determining the current target state error covariance parameter of the current charging time according to the current state error covariance parameter, a preset historical boundary value of the last charging time, the current observation covariance parameter, the current observation matrix and a preset current positive definite matrix of the current charging time;

[0074] wherein, the current target state error covariance parameter is:

[0075] P +,k = P k (eye(n)-Thita k-1 S k +C T R k CP k ) -1 ;

[0076] Thita k-1 is the historical boundary value, S k is the current positive definite matrix, and eye(n) is a preset n*n unit matrix.

[0077] As an optional implementation, in the second aspect, the second determining module is further used for:

[0078] after the first determining module determines the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the preset historical open-circuit voltage parameter and the historical ohmic resistance parameter of the last charging time of the battery, the current driving covariance parameter and the current boundary value of the current charging time for determining the target open-circuit voltage parameter and the target ohmic resistance parameter of the next charging time are determined, and the first determining module is triggered to perform the operation of determining the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the preset historical open-circuit voltage parameter and the historical ohmic resistance parameter of the last charging time of the battery based on the current driving covariance parameter and the current boundary value; the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time are the target open-circuit voltage parameter and the target ohmic resistance parameter of the next charging time respectively, and the historical open-circuit voltage parameter and the historical ohmic resistance parameter of the last charging time are the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time respectively;

[0079] wherein the current driving covariance parameter is:

[0080]

[0081] and the current boundary value is:

[0082] Thita k = λmax(eig(P +,k ))(CP k C T + R k ) -1 ;

[0083] λ is a preset adjustment proportion parameter.

[0084] As an optional implementation, in the second aspect of the present application, the manner in which the second determining module determines the current charging demand current of the current charging time of the battery based on the current charging current limit value is specifically:

[0085] determining a reference charging current limit value of the current charging time from a target relationship table based on the target relationship table and the current battery temperature parameter and the current battery remaining capacity parameter of the current charging time of the battery; the target relationship table is a preset parameter relationship table among the battery temperature parameter, the battery remaining capacity parameter and the charging current limit value of the battery;

[0086] determining a charging current limit value comparison relationship of the battery according to the reference charging current limit value and the current charging current limit value;

[0087] determining a first reference remaining capacity parameter and a second reference remaining capacity parameter of the battery based on the type parameter of the battery and the health parameter of the battery, and determining a remaining capacity parameter comparison relationship of the battery according to the first reference remaining capacity parameter, the second reference remaining capacity parameter and the current battery remaining capacity parameter;

[0088] determining a current charging demand current of the battery at a current charging time based on the charging current limit value comparison relationship and the remaining capacity parameter comparison relationship;

[0089] wherein the current charging demand current is:

[0090]

[0091] I max the current charging current limit value, I M the reference charging current limit value, SOC is the current battery remaining capacity parameter, SOC lim1 the first reference remaining capacity parameter, SOC lim2 the second reference remaining capacity parameter, and a is a preset adjustment proportion parameter of the current charging current limit value.

[0092] As an optional implementation, in the second aspect of the present application, the current charging current limit value is:

[0093]

[0094] U oc,k the current open circuit voltage parameter, R i,k the current ohmic resistance parameter, U chrglim the charging cutoff voltage.

[0095] The third aspect of the present application discloses another intelligent determination device of battery charging demand current, which comprises:

[0096] a memory storing executable program codes;

[0097] a processor coupled with the memory;

[0098] the processor invokes the executable program codes stored in the memory to execute the intelligent determination method of battery charging demand current disclosed in the first aspect of the present application.

[0099] The fourth aspect of the present application discloses a computer storage medium, the computer storage medium stores computer instructions, when the computer instructions are invoked, the computer instructions are used to execute the intelligent determination method of the battery charging demand current disclosed by the first aspect of the present application.

[0100] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0101] In the embodiments of the present application, based on the preset historical open-circuit voltage parameter and historical ohmic resistance parameter of the last charging time of the battery, the current open-circuit voltage parameter and current ohmic resistance parameter of the current charging time of the battery are determined; according to the current open-circuit voltage parameter, current ohmic resistance parameter and preset charging cutoff voltage of the battery, the current charging current limit value of the current charging time of the battery is calculated; based on the current charging current limit value, the current charging demand current of the current charging time of the battery is determined. It can be seen that by implementing the present application, the charging current limit value of the battery can be calculated in real time to evaluate the charging limit capability of the battery and determine the charging demand current of the battery, so that the reliability and accuracy of the determined charging demand current can be improved, and the vehicle battery can be reliably and accurately charged, thereby the charging safety and charging efficiency of the vehicle battery can be improved to achieve good charging effect of the vehicle battery. BRIEF DESCRIPTION OF DRAWINGS

[0102] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0103] Figure 1 is a flow diagram of the intelligent determination method of the battery charging demand current disclosed by the embodiments of the present application;

[0104] Figure 2 is a flow diagram of another intelligent determination method of the battery charging demand current disclosed by the embodiments of the present application;

[0105] Figure 3 is a structural diagram of an intelligent determination device of the battery charging demand current disclosed by the embodiments of the present application;

[0106] Figure 4 is a structural diagram of another intelligent determination device of the battery charging demand current disclosed by the embodiments of the present application. DETAILED DESCRIPTION

[0107] ​In the following, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0108] The terms "first", "second", and the like in the description and claims of the present application and the above drawings are used to distinguish different objects, rather than to describe a particular order. In addition, the terms "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or end including a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product, or end.

[0109] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearance of the phrase in various places in the specification does not necessarily all refer to the same embodiment, nor does it necessarily refer to a separate or alternative embodiment. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with each other.

[0110] The application discloses an intelligent determination method and device for battery charging demand current, which can improve the reliability and accuracy of the determined charging demand current, and then reliably and accurately charge the vehicle battery, thereby improving the charging safety and efficiency of the vehicle battery to achieve good charging effect of the vehicle battery. The following are described in detail.

[0111] Embodiment one

[0112] Please refer to Figure 1 , Figure 1 is a flowchart of an intelligent determination method for battery charging demand current disclosed by the embodiments of the present application. Wherein, Figure 1The described intelligent determination method of battery charging demand current can be applied to determine the charging demand current of vehicle batteries of various vehicle types. Optionally, the vehicle types can be pure electric vehicles, extended-range electric vehicles, hybrid vehicles, fuel cell electric vehicles, hydrogen engine vehicles, and other new energy vehicles, etc., and the embodiments of the present application are not limited. Further optionally, the method can be implemented by a demand current determination system, which can be integrated in a charging device for charging the vehicle battery, can exist independently of the charging device, and can also be a local server or a cloud server for processing the determination process of the charging demand current of the vehicle battery, and the embodiments of the present application are not limited. As shown in Figure 1 The intelligent determination method of battery charging demand current can include the following operations:

[0113] 101. Determine the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the preset historical open-circuit voltage parameter and the historical ohmic resistance parameter of the last charging time of the battery.

[0114] In the embodiments of the present application, the current charging time is the time adjacent to the last charging time, and when the last charging time is the initial charging time, the historical open-circuit voltage parameter is the initial open-circuit voltage parameter U oc,0 , and the historical ohmic resistance parameter is the initial ohmic resistance parameter R i,0 . It should be noted that the determination process of the open-circuit voltage parameter and the ohmic resistance parameter of the battery is an iterative calculation process, that is, after the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery are determined, the target open-circuit voltage parameter and the target ohmic resistance parameter of the next charging time of the battery can be determined based on the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery. Further, the determination method of the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery can be realized by using adaptive H filter method (AHIF), and compared with the traditional Kalman filter, the adaptive H filter method has less dependence on model accuracy and better robustness.

[0115] 102. Calculate the current charging current limit value of the current charging time of the battery according to the current open-circuit voltage parameter, the current ohmic resistance parameter, and the preset charging cutoff voltage of the battery.

[0116] In the embodiments of the present application, specifically, the current charging current limit value is:

[0117]

[0118] wherein U oc,k is the current open-circuit voltage parameter, R i,k is the current ohmic resistance parameter, and Uchrglim is a charging cut-off voltage. Further specifically, the charging maximum current limit value I max of the battery is estimated in real time based on the estimated current open-circuit voltage parameter, the current ohmic resistance parameter and the charging cut-off voltage parameter of the battery, so as to evaluate the charging limit capability of the battery.

[0119] 103. Determine the current charging demand current of the battery at the current charging time based on the current charging current limit value.

[0120] In the embodiment of the present application, further, the current charging demand current of the battery at the current charging time can be determined based on the current charging current limit value and the reference charging current limit value determined from the preset target relationship table, wherein the target relationship table is a preset parameter relationship table among the battery temperature parameter, the battery remaining capacity parameter and the charging current limit value of the battery.

[0121] It can be seen that the embodiment of the present application can calculate the charging current limit value of the battery in real time, evaluate the charging limit capability of the battery and determine the charging demand current of the battery, so as to not only reduce the nonlinear error caused by the changes of temperature, working condition environment, battery aging degree and the like on the charging limit capability of the battery, but also improve the reliability and accuracy of the determined charging demand current, and then reliably and accurately charge the vehicle battery, so as to improve the charging safety and charging efficiency of the vehicle battery and achieve good charging effect of the vehicle battery.

[0122] In an optional embodiment, the determination of the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time based on the preset historical open-circuit voltage parameter and the historical ohmic resistance parameter of the battery at the previous charging time in the step 101 comprises:

[0123] determining the current information error parameter at the current charging time according to the preset historical open-circuit voltage parameter and the historical ohmic resistance parameter of the battery at the previous charging time, the collected current battery port voltage parameter of the battery at the current charging time, the preset current observation matrix at the current charging time and the preset state transition matrix;

[0124] determining the current gain parameter at the current charging time, and determining the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time according to the current information error parameter, the current gain parameter and the state transition matrix.

[0125] In the optional embodiment, specifically, the current information error parameter is:

[0126] e k = U t,k - CA [Uoc,k-1 ;R i,k-1 ];

[0127] wherein, U t,k is a current battery port voltage parameter, C is a current observation matrix, A is a state transition matrix, U oc,k-1 is a historical open circuit voltage parameter, R i,k-1 is a historical ohmic resistance parameter, wherein, C = [1I k ], I k is a current battery port current parameter collected at a current charging time of the battery, and A[U oc,k-1 ;R i,k-1 ] can be understood as a current parameter state vector at the current charging time of the battery. Optionally, A can be [1 0; 01].

[0128] Further specifically, the current open circuit voltage parameter and the current ohmic resistance parameter are calculated by the following formula:

[0129] [U oc,k ;R i,k ] = A(A[U oc,k-1 ;R i,k-1 ] + K k e k );

[0130] wherein, U oc,k is a current open circuit voltage parameter, R i,k is a current ohmic resistance parameter, K k is a current gain parameter. Further, the calculated U oc,k and R i,k may be respectively understood as an optimal estimation value of the current open circuit voltage of the battery and an optimal estimation value of the current ohmic resistance.

[0131] It can be seen that the optional embodiment can reasonably and pertinently determine the current open circuit voltage parameter and the current ohmic resistance parameter of the battery, which is beneficial to reliably and accurately determine the current open circuit voltage parameter and the current ohmic resistance parameter of the battery, and further beneficial to improve the reliability and accuracy of the current charging current limit value of the battery calculated based on the current open circuit voltage parameter and the current ohmic resistance parameter, so as to improve the reliability and accuracy of the current charging demand current of the battery determined subsequently, so as to accurately charge the battery.

[0132] In another optional embodiment, the determination of the current gain parameter at the current charging time in the above step comprises:

[0133] determining a current state error covariance parameter of the current charging time, and determining a current observation covariance parameter of the current charging time according to the current state error covariance parameter, a current information error parameter, a preset sliding window size parameter and a current observation matrix;

[0134] determining a current target state error covariance parameter of the current charging time, and determining a current gain parameter of the current charging time according to the current observation covariance parameter, the current target state error covariance parameter and the current observation matrix.

[0135] In this optional embodiment, specifically, the current observation covariance parameter is:

[0136]

[0137] wherein, M is the sliding window size parameter, P k is the current state error covariance parameter. Further, P k = AP k-1 A+Q k-1 , P k-1 is a preset historical state error covariance parameter of the previous charging time, Q k-1 is a preset historical driving covariance parameter of the previous charging time. Still further, when the previous charging time is an initial charging time, the P k-1 is an initial state error covariance parameter P0, and Q k-1 is an initial driving covariance parameter Q0.

[0138] Further specifically, the current gain parameter is:

[0139]

[0140] wherein, P +,k is the current target state error covariance parameter.

[0141] It can be seen that this optional embodiment can determine the current gain parameter of the battery based on the current observation covariance parameter and the current target state error covariance parameter of the battery, so that the reliability and accuracy of the determined current gain parameter can be improved, and the calculation reliability and accuracy of the current open circuit voltage parameter and the current ohm parameter of the battery can be improved, thereby the determination reliability and accuracy of the current charging demand current of the battery can be improved to achieve safe charging of the battery and improve the charging efficiency based on the current charging demand current.

[0142] In yet another optional embodiment, the step of determining the current target state error covariance parameter of the current charging time comprises:

[0143] The current target state error covariance parameter is determined according to the current state error covariance parameter, the preset historical boundary value of the last charging time, the current observation covariance parameter, the current observation matrix and the preset current positive definite matrix of the current charging time.

[0144] In this optional embodiment, specifically, the current target state error covariance parameter is:

[0145] P +,k = P k (eye(n)-Thita k-1 S k +C T R k CP k ) -1 ;

[0146] Wherein, Thita k-1 is the historical boundary value, S k is the current positive definite matrix, and eye(n) is a preset n*n unit matrix. Further, when the last charging time is the initial charging time, Thita k-1 is the initial boundary value Thita0. Still further, the specific matrix parameter of S k may be determined based on the parameter weight ratio between U oc,k and R i,k , such as when the parameter weight ratio between U oc,k and R i,k is 1:1, S k may be [1 0; 0 1], and when the parameter weight ratio between U oc,k and R i,k is 2:1, S k may be [2 0; 0 1].

[0147] It can be seen that this optional embodiment can flexibly determine the current target state error covariance parameter of the battery based on the current positive definite matrix and other parameters, so as to meet various calculation requirements of the user for the current target state error covariance parameter, thereby facilitating to improve the reliability and accuracy of the determined current target state error covariance parameter, and thus facilitating to improve the reliability and accuracy of the subsequently determined current gain parameter of the battery, so as to improve the calculation accuracy of the overall battery current demand parameter.

[0148] In still another optional embodiment, after determining the current open circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging time based on the preset historical open circuit voltage parameter and the historical ohmic resistance parameter of the battery at the last charging time in the above step 101, the method further comprises:

[0149] determining the current driving covariance parameter and the current boundary value of the current charging time for determining the target open-circuit voltage parameter and the target ohmic resistance parameter of the next charging time, and triggering the operation of determining the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the current driving covariance parameter and the current boundary value.

[0150] In the optional embodiment, the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time are respectively the target open-circuit voltage parameter and the target ohmic resistance parameter of the next charging time, and the historical open-circuit voltage parameter and the historical ohmic resistance parameter of the previous charging time are respectively the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time, that is, the iteration calculation process of the open-circuit voltage parameter and the ohmic resistance parameter of the battery is started based on the current driving covariance parameter and the current boundary value. Further, after the target open-circuit voltage parameter and the target ohmic resistance parameter of the next charging time are determined, the calculation operation of the current charging current limit value of the battery based on the target open-circuit voltage parameter and the target ohmic resistance parameter can be continued, and the operation of determining the current charging demand current of the battery based on the current charging current limit value of the battery, wherein the current charging current limit value is a new current charging current limit value and the current charging demand current is a new current charging demand current.

[0151] Specifically, the current driving covariance parameter is:

[0152]

[0153] Further specifically, the current boundary value is:

[0154] Thita k = λmax(eig(P +,k ))(CP k C T + R k ) -1 ,

[0155] Wherein, λ is a preset adjustment proportion parameter, and 0<λ<1.

[0156] It can be seen that the optional embodiment can automatically start the iteration calculation of the target open-circuit voltage parameter and the target ohmic resistance parameter of the next charging time based on the current driving covariance parameter and the current boundary value of the battery, which is beneficial to realize the real-time calculation of the open-circuit voltage parameter and the ohmic resistance parameter of the battery, and further beneficial to realize the real-time calculation of the charging demand current of the battery, thereby being beneficial to better realize the precise charging of the vehicle battery.

[0157] Embodiment Two

[0158] Referring to Figure 2 , Figure 2 is a flowchart of a method for intelligently determining a battery charging demand current according to an embodiment of the present application. In the method, the following operations are performed. Figure 2 The method for intelligently determining a battery charging demand current can be applied to determining a charging demand current of a vehicle battery of various types of vehicles. Optionally, the vehicle type can be a pure electric vehicle, a range-extended electric vehicle, a hybrid vehicle, a fuel cell electric vehicle, a hydrogen engine vehicle, and other new energy vehicles, etc., and the present application is not limited thereto. Further optionally, the method can be implemented by a demand current determination system, which can be integrated in a charging device for charging the vehicle battery, can exist independently of the charging device, can be a local server or a cloud server for processing the determination process of the charging demand current of the vehicle battery, etc., and the present application is not limited thereto. As shown in Figure 2 The method for intelligently determining a battery charging demand current can include the following operations.

[0159] 201. Determine a current open-circuit voltage parameter and a current ohmic resistance parameter of a current charging time of a battery based on a preset historical open-circuit voltage parameter and a preset historical ohmic resistance parameter of a previous charging time of the battery.

[0160] 202. Calculate a current charging current limit value of the current charging time of the battery according to the current open-circuit voltage parameter, the current ohmic resistance parameter, and a preset charging cutoff voltage of the battery.

[0161] 203. Determine a reference charging current limit value of the current charging time from a target relationship table based on the target relationship table and a current battery temperature parameter and a current battery remaining capacity parameter of the current charging time of the battery.

[0162] In the present embodiment, specifically, the target relationship table is a parameter relationship table among a battery temperature parameter, a battery remaining capacity parameter, and a charging current limit value of the preset battery.

[0163] 204. Determine a charging current limit value comparison relationship of the battery according to the reference charging current limit value and the current charging current limit value.

[0164] In the present embodiment, the charging current limit value comparison relationship can reflect a charging capability degradation condition of the vehicle battery.

[0165] 205、based on the battery type parameter and the health degree parameter of the battery, determine a first reference remaining capacity parameter and a second reference remaining capacity parameter of the battery, and determine a comparison relationship of the remaining capacity parameter of the battery according to the first reference remaining capacity parameter, the second reference remaining capacity parameter and the current remaining capacity parameter of the battery.

[0166] 206、based on the comparison relationship of the charging current limit value and the comparison relationship of the remaining capacity parameter, determine the current charging demand current of the battery at the current charging time.

[0167] In the embodiment of the application, specifically, the current charging demand current is:

[0168]

[0169] wherein, I max is the current charging current limit value, I M is the reference charging current limit value, SOC is the current remaining capacity parameter of the battery, SOC lim1 is the first reference remaining capacity parameter, SOC lim2 is the second reference remaining capacity parameter, and a is a preset adjustment proportion parameter of the current charging current limit value. Further, a satisfies the following relationship: 0 < a < 1. Optionally, the adjustment proportion parameter can be determined based on at least one of the battery type parameter, the charging machine output power parameter and the health degree parameter of the battery.

[0170] In the embodiment of the application, for other descriptions of steps 201 and 202, please refer to the detailed description of steps 101 and 102 in Embodiment One, and the embodiment of the application will not be repeated here.

[0171] It can be seen that by implementing the embodiment of the application, the charging limit capability of the battery can be evaluated based on the comparison relationship between the reference charging current limit value and the current charging current limit value, which is beneficial to improve the reliability and accuracy of the determined current charging demand current of the battery, and further beneficial to improve the reliability and accuracy of the charging operation of the battery, thereby beneficial to improve the charging safety and charging efficiency of the battery, so that the vehicle can operate normally.

[0172] Embodiment Three

[0173] Please refer to Figure 3 , Figure 3 is a structural schematic diagram of an intelligent determination device for battery charging demand current disclosed by the embodiment of the application. As Figure 3 shown, the intelligent determination device for battery charging demand current can include:

[0174] The first determination module 301 is configured to determine a current open-circuit voltage parameter and a current ohmic resistance parameter of a current charging time of the battery based on a preset historical open-circuit voltage parameter and a preset historical ohmic resistance parameter of a previous charging time of the battery.

[0175] The calculation module 302 is configured to calculate a current charging current limit value of the current charging time of the battery according to the current open-circuit voltage parameter, the current ohmic resistance parameter and a preset charging cutoff voltage of the battery.

[0176] The second determination module 303 is configured to determine a current charging demand current of the current charging time of the battery based on the current charging current limit value.

[0177] In the embodiment of the present application, the current charging time is a time point adjacent to the previous charging time.

[0178] The current charging current limit value is:

[0179]

[0180] U oc,k The current open-circuit voltage parameter is U i,k The current ohmic resistance parameter is R chrglim The charging cutoff voltage is U

[0181] It can be seen that the implementation Figure 3 The described intelligent determination device of the battery charging demand current can calculate the charging current limit value of the battery in real time, evaluate the charging limit capability of the battery and determine the charging demand current of the battery. In this way, the nonlinear error caused by the changes of temperature, working conditions, aging degree of the battery and the like on the charging limit capability of the battery can be reduced, the reliability and accuracy of the determined charging demand current can be improved, and the vehicle battery can be reliably and accurately charged, so that the charging safety and charging efficiency of the vehicle battery can be improved, and good charging effect of the vehicle battery can be achieved.

[0182] In an optional embodiment, the first determination module 301 determines the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the preset historical open-circuit voltage parameter and the preset historical ohmic resistance parameter of the previous charging time of the battery in the following manner:

[0183] The current information error parameter of the current charging time is determined according to the preset historical open-circuit voltage parameter and the preset historical ohmic resistance parameter of the previous charging time of the battery, the collected current battery port voltage parameter of the current charging time of the battery, the preset current observation matrix of the current charging time and the preset state transition matrix.

[0184] Determine the current gain parameter at the current charging moment, and based on the current information error parameter, the current gain parameter, and the state transition matrix, determine the current open-circuit voltage parameter and the current ohmic resistance parameter of the battery at the current charging moment.

[0185] In this optional embodiment, the current information error parameter is:

[0186] e k =U t,k -CA[U oc,k-1 ;R i,k-1 ];

[0187] U t,k Here, C represents the current battery port voltage parameters, A represents the current observation matrix, and U represents the state transition matrix. oc,k-1 For historical open-circuit voltage parameters, R i,k-1 Here are the historical ohmic resistance parameters, where C = [1I k ], I k The current battery port current parameters at the current charging moment of the battery are collected;

[0188] Furthermore, the current open-circuit voltage parameters and the current ohmic resistance parameters are calculated using the following formulas:

[0189] [U oc,k ;R i,k ] = A(A[U oc,k-1 ;R i,k-1 ]+K k e k );

[0190] U oc,k R represents the current open-circuit voltage parameter. i,k K represents the current ohmic resistance parameter. k This is the current gain parameter.

[0191] It is evident that implementation Figure 3 The intelligent device for determining the battery charging current demand described herein can reasonably and specifically determine the current open-circuit voltage parameters and current ohmic resistance parameters of the battery. This facilitates the reliable and accurate determination of the current open-circuit voltage parameters and current ohmic resistance parameters, thereby improving the reliability and accuracy of the current charging current limit value of the battery calculated based on the current open-circuit voltage parameters and current ohmic resistance parameters. This, in turn, improves the reliability and accuracy of the subsequently determined current charging current demand of the battery, enabling precise charging of the battery.

[0192] In another optional embodiment, the first determining module 301 determines the current gain parameter at the current charging moment in the following specific manner:

[0193] Determine the current state error covariance parameter at the current charging moment, and based on the current state error covariance parameter, the current information error parameter, the preset sliding window size parameter, and the current observation matrix, determine the current observation covariance parameter at the current charging moment.

[0194] Determine the current target state error covariance parameter at the current charging moment, and based on the current observation covariance parameter, the current target state error covariance parameter, and the current observation matrix, determine the current gain parameter at the current charging moment.

[0195] In this optional embodiment, the current observation covariance parameter is:

[0196]

[0197] M is the sliding window size parameter, P k Let P be the current state error covariance parameter, where P is the current state error covariance parameter. k =AP k-1 A+Q k-1 P k-1 Q is the preset historical state error covariance parameter from the previous charging time. k-1 The preset historical driving covariance parameter for the previous charging time;

[0198] And, the current gain parameter is:

[0199]

[0200] P +,k This is the current target state error covariance parameter.

[0201] It is evident that implementation Figure 3 The intelligent device for determining the battery charging current demand described herein can determine the battery's current gain parameter based on the battery's current observation covariance parameter and the current target state error covariance parameter. This improves the reliability and accuracy of the determined current gain parameter, and consequently improves the reliability and accuracy of the calculation of the battery's current open-circuit voltage parameter and current ohmic parameter. This, in turn, improves the reliability and accuracy of determining the battery's current charging current demand, enabling safe charging and improved charging efficiency based on the current charging current demand.

[0202] In yet another optional embodiment, the first determining module 301 determines the current target state error covariance parameter at the current charging moment in the following specific manner:

[0203] Based on the current state error covariance parameter, the preset historical boundary value of the previous charging time, the current observation covariance parameter, the current observation matrix, and the preset current positive definite matrix of the current charging time, determine the current target state error covariance parameter at the current charging time.

[0204] In this optional embodiment, the current target state error covariance parameter is:

[0205] P +,k =P k (eye(n)-Thita k-1 S k +C T R k CP k ) -1 ;

[0206] Thita k-1 S represents the historical boundary value. k Let eye(n) be the current positive definite matrix, and eye(n) be the preset n*n identity matrix.

[0207] It is evident that implementation Figure 3 The intelligent device for determining the battery charging current demand described herein can flexibly determine the current target state error covariance parameter of the battery based on parameters such as the current positive definite matrix. This can meet the user's various calculation needs for the current target state error covariance parameter, thereby improving the reliability and accuracy of the determined current target state error covariance parameter. This, in turn, improves the reliability and accuracy of the subsequently determined current gain parameter of the battery, thus enhancing the overall accuracy of the battery current demand parameter calculation.

[0208] In yet another optional embodiment, the second determining module 303 is further configured to:

[0209] After the first determining module 301 determines the current open-circuit voltage parameters and current ohmic resistance parameters of the battery at the current charging time based on the preset historical open-circuit voltage parameters and historical ohmic resistance parameters of the battery at the previous charging time, it determines the current driving covariance parameters and current boundary values ​​of the current charging time for determining the target open-circuit voltage parameters and target ohmic resistance parameters of the next charging time. Based on the current driving covariance parameters and current boundary values, the first determining module 301 is triggered to perform the operation of determining the current open-circuit voltage parameters and current ohmic resistance parameters of the battery at the current charging time based on the preset historical open-circuit voltage parameters and historical ohmic resistance parameters of the battery at the previous charging time.

[0210] In this optional embodiment, the current open-circuit voltage parameter and the current ohmic resistance parameter at the current charging moment are respectively the target open-circuit voltage parameter and the target ohmic resistance parameter at the next charging moment, and the historical open-circuit voltage parameter and the historical ohmic resistance parameter at the previous charging moment are respectively the current open-circuit voltage parameter and the current ohmic resistance parameter at the current charging moment.

[0211] The current driving covariance parameter is:

[0212]

[0213] And, the current boundary value is:

[0214] Thita k =λmax(eig(P) +,k ))(CP k C T +R k ) -1 ;

[0215] λ is a preset adjustment ratio parameter.

[0216] It is evident that implementation Figure 3 The intelligent device for determining the battery charging current described herein can automatically initiate iterative calculations of the target open-circuit voltage parameters and target ohmic resistance parameters for the next charging moment based on the battery's current driving covariance parameters and current boundary values. This facilitates real-time calculation of the battery's open-circuit voltage parameters and ohmic resistance parameters, which in turn facilitates real-time calculation of the battery's charging current demand, thereby enabling more precise charging of the vehicle battery.

[0217] In another optional embodiment, the second determining module 303 determines the current charging current requirement of the battery at the current charging moment based on the current charging current limit value in the following specific manner:

[0218] Based on the preset target relationship table and the current battery temperature parameters and current battery remaining capacity parameters at the current charging time, the reference charging current limit value at the current charging time that matches the current battery temperature parameters and current battery remaining capacity parameters is determined from the target relationship table.

[0219] The comparison relationship between the battery's charging current limits is determined based on the reference charging current limit and the current charging current limit.

[0220] Based on the battery type parameters and battery health parameters, a first reference remaining capacity parameter and a second reference remaining capacity parameter are determined, and the comparison relationship of the remaining capacity parameters of the battery is determined according to the first reference remaining capacity parameter, the second reference remaining capacity parameter and the current remaining capacity parameter of the battery.

[0221] determining the current charging demand current of the battery at the current charging moment based on the comparison relationship between the charging current limit value and the comparison relationship between the remaining power parameters.

[0222] In this optional embodiment, the target relationship table is a parameter relationship table between the battery temperature parameters, the battery remaining power parameters and the charging current limit value of the preset battery.

[0223] The current charging demand current is:

[0224]

[0225] I max is the current charging current limit value, I M is the reference charging current limit value, SOC is the current battery remaining power parameter, SOC lim1 is the first reference remaining power parameter, SOC lim2 is the second reference remaining power parameter, and α is a preset adjustment proportion parameter of the current charging current limit value.

[0226] It can be seen that the implementation Figure 3 The intelligent battery charging demand current determination device described can evaluate the charging limit capability of the battery based on the comparison relationship between the reference charging current limit value and the current charging current limit value, which is beneficial to improve the reliability and accuracy of the determined current charging demand current of the battery, and further beneficial to improve the reliability and accuracy of the charging operation of the battery, thereby beneficial to improve the charging safety and charging efficiency of the battery, so that the vehicle can operate normally.

[0227] Embodiment Four

[0228] Please refer to Figure 4 , Figure 4 is another structure diagram of the intelligent battery charging demand current determination device according to the embodiment of the present application. As Figure 4 shown, the intelligent battery charging demand current determination device can include:

[0229] a memory 401 storing executable program codes;

[0230] a processor 402 coupled with the memory 401;

[0231] The processor 402 calls the executable program codes stored in the memory 401 to execute the steps in the intelligent battery charging demand current determination method described in the embodiment one or the embodiment two of the present application.

[0232] Embodiment Five

[0233] The embodiment of the present application discloses a computer storage medium, which stores computer instructions, and the computer instructions are used to execute the steps in the intelligent determination method of battery charging demand current described in the embodiment one or the embodiment two of the present application.

[0234] Embodiment six

[0235] The embodiment of the present application discloses a computer program product, which comprises a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to make a computer execute the steps in the intelligent determination method of battery charging demand current described in the embodiment one or the embodiment two.

[0236] The above described device embodiments are only schematic, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed on multiple network modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0237] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software and necessary general hardware platform, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of software product, and the computer software product can be stored in a computer readable storage medium, and the storage medium includes read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other computer readable medium capable of carrying or storing data.

[0238] Finally, it should be noted that the battery charging demand current intelligent determination method and device disclosed in the embodiments of the present application are only the preferred embodiments of the present application, and are used to illustrate the technical solutions of the present application, but not to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents. The modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for intelligent determination of battery charging demand current, characterized in that, The method comprises: determining a current open-circuit voltage parameter and a current ohmic resistance parameter of a current charging time of the battery based on a historical open-circuit voltage parameter and a historical ohmic resistance parameter of a previous charging time of the battery; the current charging time is a time adjacent to the previous charging time; calculating a current charging current limit value of the current charging time of the battery according to the current open-circuit voltage parameter, the current ohmic resistance parameter, and a preset charging cut-off voltage of the battery; determining a current charging demand current of the current charging time of the battery based on the current charging current limit value; wherein the determination of the current charging demand current of the current charging time of the battery based on the current charging current limit value comprises: determining a reference charging current limit value of the current charging time that matches the current battery temperature parameter and the current battery remaining capacity parameter from a target relationship table based on the target relationship table and the current battery temperature parameter and the current battery remaining capacity parameter of the current charging time of the battery; the target relationship table is a preset parameter relationship table among the battery temperature parameter, the battery remaining capacity parameter, and the charging current limit value of the battery; determining a charging current limit value comparison relationship of the battery according to the reference charging current limit value and the current charging current limit value; determining a first reference remaining capacity parameter and a second reference remaining capacity parameter of the battery based on the type parameter and the health degree parameter of the battery, and determining a remaining capacity parameter comparison relationship of the battery according to the first reference remaining capacity parameter, the second reference remaining capacity parameter, and the current battery remaining capacity parameter; determining a current charging demand current of the current charging time of the battery based on the charging current limit value comparison relationship and the remaining capacity parameter comparison relationship.

2. The method for intelligent determination of battery charging demand current according to claim 1, characterized in that, The determination of the current open-circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the historical open-circuit voltage parameter and the historical ohmic resistance parameter of the previous charging time of the battery comprises: determining a current information error parameter of the current charging time according to a preset historical open-circuit voltage parameter and a preset historical ohmic resistance parameter of a previous charging time of the battery, a current battery port voltage parameter of the current charging time of the battery collected, a preset current observation matrix of the current charging time, and a preset state transition matrix; determining a current gain parameter of the current charging time, and determining a current open-circuit voltage parameter and a current ohmic resistance parameter of the current charging time of the battery according to the current information error parameter, the current gain parameter, and the state transition matrix; wherein the current information error parameter is: e k = U t,k - CA[U oc,k-1 ; R i,k-1 ]; U t,k is the current battery port voltage parameter, C is the current observation matrix, A is the state transition matrix, U oc,k-1 is the historical open circuit voltage parameter, R i,k-1 is the historical ohmic resistance parameter, wherein C = [1I k ], I k is a current battery port current parameter of the battery at the current charging time point. and the current open-circuit voltage parameter and the current ohmic resistance parameter are calculated by the following formula: [U oc,k ; R i,k ] = A(A[U oc,k-1 ; R i,k-1 ] + K k e k ); U oc,k R is the current open circuit voltage parameter, i,k K is the current ohmic resistance parameter, k G is the current gain parameter.

3. The method of intelligent determination of battery charging demand current as claimed in claim 2, wherein, The determination of the current gain parameter of the current charging time comprises: determining a current state error covariance parameter of the current charging time according to the current state error covariance parameter, the current information error parameter, a preset sliding window size parameter and the current observation matrix; determining a current target state error covariance parameter of the current charging time according to the current observation covariance parameter, the current target state error covariance parameter and the current observation matrix; wherein the current observation covariance parameter is: M is the sliding window size parameter, P k is the current state error covariance parameter, wherein P k = AP k-1 A + Q k-1 , P k-1 is a preset historical state error covariance parameter at the last charging time, Q k-1 is a preset historical driving covariance parameter at the last charging time; and the current gain parameter is: P +,k is the current target state error covariance parameter.

4. The method of intelligent determination of battery charging demand current as claimed in claim 3, wherein, the determining of the current target state error covariance parameter of the current charging time comprises: determining the current target state error covariance parameter of the current charging time according to the current state error covariance parameter, a preset historical boundary value of the previous charging time, the current observation covariance parameter, the current observation matrix and a preset current positive definite matrix of the current charging time; wherein the current target state error covariance parameter is: P +,k = P k (eye(n) - Thita k-1 S k + C T R k CP k ) -1 ; Thita k-1 S is the history boundary value k S is the current positive definite matrix, and eye(n) is a preset n*n unit matrix.

5. The method of intelligent determination of battery charging demand current as claimed in claim 4, wherein, after the determining of the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the preset historical open circuit voltage parameter and the historical ohmic resistance parameter of the previous charging time of the battery, the method further comprises: determining a current driving covariance parameter and a current boundary value of the current charging time for determining a target open circuit voltage parameter and a target ohmic resistance parameter of a next charging time, and triggering the operation of determining the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time of the battery based on the preset historical open circuit voltage parameter and the historical ohmic resistance parameter of the previous charging time of the battery according to the current driving covariance parameter and the current boundary value; the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time are respectively the target open circuit voltage parameter and the target ohmic resistance parameter of the next charging time, and the historical open circuit voltage parameter and the historical ohmic resistance parameter of the previous charging time are respectively the current open circuit voltage parameter and the current ohmic resistance parameter of the current charging time; wherein the current driving covariance parameter is: and the current boundary value is: Thita k = λmax(eig(P +,k ))(CP k C T + R k ) -1 ; λ is a preset adjustment proportion parameter.

6. The method of intelligent determination of battery charging demand current according to any one of claims 1-5, characterized in that, the current charging demand current is: I max is the current charging current limit value, I M is the reference charging current limit value, SOC is the current battery remaining capacity parameter, SOC lim1 is the first reference remaining capacity parameter, SOC lim2 is the second reference remaining capacity parameter, and a is a preset adjustment proportion parameter of the current charging current limit value.

7. The method of intelligent determination of battery charging demand current according to any one of claims 1-5, characterized in that, the current charging current limit value is: U oc,k is the current open circuit voltage parameter, R i,k is the current ohmic resistance parameter, U chrglim is the charge cut-off voltage.

8. An intelligent determination of battery charge demand current apparatus, characterized by, the device is used for executing the intelligent determination method of the battery charging demand current according to any one of claims 1-7, and the device comprises: a first determining module, configured to determine a current open circuit voltage parameter and a current ohmic resistance parameter of a current charging time of a battery based on a preset historical open circuit voltage parameter and a preset historical ohmic resistance parameter of a previous charging time of the battery; the current charging time is a time adjacent to the previous charging time; The computing module is configured to calculate a current charging current limit value of the battery at a current charging time according to the current open circuit voltage parameter, the current ohmic resistance parameter, and a preset charging cutoff voltage of the battery. The second determining module is configured to determine a current charging demand current of the battery at the current charging time based on the current charging current limit value.

9. An intelligent determination of battery charge demand current apparatus, characterized by, The device comprises: a memory storing executable program codes; a processor coupled with the memory; the processor invokes the executable program codes stored in the memory to execute the intelligent determination method of the battery charging demand current according to any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which are invoked to execute the intelligent determination method of the battery charging demand current according to any one of claims 1-7.

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