Method for detecting insulation resistance of automobile battery, calculation module, device and automobile

Abstract

The application provides an insulation resistance detection method, a calculation module, a device and a car for a car battery. The detection method comprises: collecting a first voltage collected by a first sampling module and a second voltage collected by a second sampling module based on a preset sampling frequency; for any sampling time, determining a coefficient vector of an undetermined coefficient of an equivalent circuit model of an insulation resistance detection circuit based on the first voltage, the second voltage and a forgetting factor least square algorithm collected at the sampling time; and for any sampling time, determining the resistance value of a first equivalent insulation resistance and a second equivalent insulation resistance based on the coefficient vector of the undetermined coefficient at the sampling time and a target transfer function of the equivalent circuit model. In this way, the dynamic response of the car battery is simulated through the insulation resistance detection circuit, and the coefficient vector of the undetermined coefficient of the equivalent circuit model is updated in real time by using the forgetting factor least square algorithm to reduce the output error, thereby improving the accuracy of real-time detection of the insulation resistance of the car battery.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automotive electronics, and particularly relates to an insulation resistance detection method, a calculation module, a device and a vehicle for a vehicle battery. BACKGROUND

[0002] As a power source of an electric vehicle, the insulation performance between the vehicle battery and the vehicle is the basis for the operation of the vehicle electrical system and also guarantees the safety of passengers in the vehicle. The insulation performance between the vehicle battery and the vehicle is usually represented by insulation resistance. The insulation resistance is the direct current resistance of an insulator under specified conditions, which refers to the equivalent insulation resistance between the positive and negative electrodes of the battery and the vehicle body.

[0003] In the prior art, the insulation resistance of the vehicle battery is detected by an unbalanced bridge method. Specifically, the MOS tube switch is actively controlled to connect a bias resistor with a known resistance value to realize the shift change of the voltage, and then the changed voltage is detected to calculate the insulation resistance value.

[0004] Since the method connects the bias resistor, the detection circuit needs a long time to reach a new stable value. If the insulation resistance is calculated when the detection circuit is not stable, a large error will be generated, and there is a problem of low accuracy in real-time detection of the insulation resistance of the vehicle battery. SUMMARY

[0005] Therefore, the embodiments of the present application provide an insulation resistance detection method, a calculation module, a device and a vehicle for a vehicle battery. The dynamic response of the vehicle battery is simulated by an insulation resistance detection circuit, and the forgetting factor least square algorithm is used to update the undetermined coefficient vector of the equivalent circuit model in real time to reduce the output error, thereby improving the accuracy of real-time detection of the insulation resistance of the vehicle battery.

[0006] The present application mainly includes the following aspects:

[0007] In a first aspect, the embodiments of the present application provide a method for detecting an insulation resistance of a battery of a vehicle, which is applied to a calculation module of an insulation resistance detection device of the battery of the vehicle. The insulation resistance detection device further comprises an insulation resistance detection circuit. The insulation resistance detection circuit comprises a first resistor, a second resistor, a first capacitor, a second capacitor, a first sampling module and a second sampling module. A positive electrode of the battery of the vehicle is connected with a first end of the first resistor and an input end of the first sampling module respectively, and a negative electrode of the battery of the vehicle is connected with a first end of the second resistor. A second end of the first resistor is connected with a first end of the first capacitor. A second end of the second resistor is connected with an input end of the second sampling module and a first end of the second capacitor respectively. A second end of the first capacitor and a second end of the second capacitor are both grounded. An output end of the first sampling module and an output end of the second sampling module are both electrically connected with the calculation module. The method comprises the following steps:

[0008] collecting a first voltage collected by the first sampling module and a second voltage collected by the second sampling module based on a preset sampling frequency;

[0009] for any sampling moment, determining a coefficient vector of an equivalent circuit model of the insulation resistance detection circuit at the sampling moment based on the first voltage, the second voltage collected at the sampling moment and a forgetting factor least square algorithm. The equivalent circuit model comprises a first equivalent insulation resistance connected in parallel across the first capacitor and a second equivalent insulation resistance connected in parallel across the second capacitor;

[0010] for any sampling moment, determining resistances of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling moment based on the coefficient vector at the sampling moment and a target transfer function of the equivalent circuit model.

[0011] In a second aspect, the embodiments of the present application further provide a calculation module, which is applied to an insulation resistance detection device of a battery of a vehicle. The insulation resistance detection device further comprises an insulation resistance detection circuit. The insulation resistance detection circuit comprises a first resistor, a second resistor, a first capacitor, a second capacitor, a first sampling module and a second sampling module. A positive electrode of the battery of the vehicle is connected with a first end of the first resistor and an input end of the first sampling module respectively, and a negative electrode of the battery of the vehicle is connected with a first end of the second resistor. A second end of the first resistor is connected with a first end of the first capacitor. A second end of the first capacitor is grounded. A second end of the second resistor is connected with an input end of the second sampling module and a first end of the second capacitor respectively. A second end of the second capacitor is grounded. An output end of the first sampling module and an output end of the second sampling module are both electrically connected with the calculation module. The calculation module comprises the following steps:

[0012] a sampling unit, configured to collect the first voltage collected by the first sampling module and the second voltage collected by the second sampling module based on a preset sampling frequency;

[0013] a first determination unit, configured to determine, for any sampling moment, a coefficient vector of an equivalent circuit model of the insulation resistance detection circuit at the sampling moment based on the first voltage, the second voltage and a forgetting factor least square algorithm collected at the sampling moment, wherein the equivalent circuit model comprises a first equivalent insulation resistance connected in parallel to a first capacitor and a second equivalent insulation resistance connected in parallel to a second capacitor;

[0014] a second determination unit, configured to determine, for any sampling moment, resistances of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling moment based on the coefficient vector at the sampling moment and a target transfer function of the equivalent circuit model.

[0015] In a third aspect, an embodiment of the present application further provides an insulation resistance detection device for a battery of an automobile, and the insulation resistance detection device comprises:

[0016] an insulation resistance detection circuit and the calculation module in the second aspect.

[0017] In a fourth aspect, an embodiment of the present application further provides an automobile comprising the insulation resistance detection device for a battery of an automobile in the third aspect.

[0018] The embodiment of the application provides a method for detecting the insulation resistance of an automobile battery, a calculation module, a device and an automobile, wherein the method for detecting the insulation resistance is applied to the calculation module of an insulation resistance detection device of the automobile battery, the insulation resistance detection device further comprises an insulation resistance detection circuit, the insulation resistance detection circuit comprises a first resistor, a second resistor, a first capacitor, a second capacitor, a first sampling module and a second sampling module; the positive electrode of the automobile battery is connected with the first end of the first resistor and the input end of the first sampling module respectively, and the negative electrode of the automobile battery is connected with the first end of the second resistor; the second end of the first resistor is connected with the first end of the first capacitor; the second end of the second resistor is connected with the input end of the second sampling module and the first end of the second capacitor respectively; the second end of the first capacitor and the second end of the second capacitor are grounded; the output end of the first sampling module and the output end of the second sampling module are electrically connected with the calculation module respectively; the detection method comprises the following steps: based on a preset sampling frequency, a first voltage collected by the first sampling module and a second voltage collected by the second sampling module are collected; for any sampling moment, based on the first voltage, the second voltage and a forgetting factor least square algorithm collected at the sampling moment, a to-be-determined coefficient vector of an equivalent circuit model of the insulation resistance detection circuit at the sampling moment is determined; wherein the equivalent circuit model comprises a first equivalent insulation resistance connected in parallel across the first capacitor and a second equivalent insulation resistance connected in parallel across the second capacitor; for any sampling moment, based on the to-be-determined coefficient vector at the sampling moment and a target transfer function of the equivalent circuit model, the resistance value of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling moment is determined. In this way, the dynamic response of the automobile battery is simulated through the insulation resistance detection circuit, and the to-be-determined coefficient vector of the equivalent circuit model is updated in real time by using the forgetting factor least square algorithm to reduce the output error, thereby improving the accuracy of real-time detection of the insulation resistance of the automobile battery.

[0019] In order to make the above objectives, characteristics and advantages of the application more apparent, clear and easy to understand, the following will specifically describe the preferred embodiments of the application with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some of the embodiments of the application, and therefore should not be regarded as a limitation to the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0021] Figure 1 Fig. 1 shows a structure schematic diagram of an insulation resistance detection device of an automobile battery according to an embodiment of the application;

[0022] Figure 2Fig. 2 shows a structural schematic diagram of an insulation resistance detection device for an automobile battery according to an embodiment of the present application;

[0023] Figure 3 Fig. 3 shows a flow chart of an insulation resistance detection method for an automobile battery according to an embodiment of the present application;

[0024] Figure 4 Fig. 4 shows a structural schematic diagram of an equivalent circuit model of an insulation resistance detection circuit according to an embodiment of the present application;

[0025] Figure 5 Fig. 5 shows a functional module diagram of a computing module according to an embodiment of the present application;

[0026] Figure 6 Fig. 6 shows a functional module diagram of a computing module according to an embodiment of the present application;

[0027] Figure 7 Fig. 7 shows a structural schematic diagram of an electronic device according to an embodiment of the present application.

[0028] Main element symbol explanation:

[0029] In the figure: 100-insulation resistance detection device; 101-first resistor; 102-second resistor; 103-first capacitor; 104-second capacitor; 105-first sampling module; 106-second sampling module; 107-computing module; 108-first switch; 109-second switch; 110-third switch; 111-fourth switch; 200-automobile battery; R x -first equivalent insulation resistance; R y -second equivalent insulation resistance; 1071-sampling unit; 1072-first determination unit; 1073-second determination unit; 1074-third determination unit; 1075-judgment unit; 1076-sending unit; 1077-first control unit; 1078-second control unit; 700-electronic device; 710-processor; 720-memory; 730-bus. DETAILED DESCRIPTION

[0030] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0031] The following will combine Figure 1 as well as Figure 2 The implementation methods of the embodiments of this application are described in detail; the embodiments of this application provide an insulation resistance detection method for automobile batteries, which is applied to the calculation module of an insulation resistance detection device for automobile batteries.

[0032] Please see Figure 1 , Figure 1 This is one of the structural schematic diagrams of an insulation resistance testing device for an automotive battery provided in an embodiment of this application. The insulation resistance testing method for an automotive battery provided in this application can be applied to... Figure 1 The insulation resistance detection device for the automobile battery shown includes a calculation module 107. The automobile battery insulation resistance detection device 100 may include: a first resistor 101, a second resistor 102, a first capacitor 103, a second capacitor 104, a first sampling module 105, a second sampling module 106, and a calculation module 107. The positive terminal of the automobile battery 200 is connected to the first end of the first resistor 101 and the input terminal of the first sampling module 105, respectively; the negative terminal of the automobile battery is connected to the first end of the second resistor 102; the second end of the first resistor 101 is connected to the first end of the first capacitor 103; the second end of the second resistor 102 is connected to the input terminal of the second sampling module 106 and the first end of the second capacitor 104, respectively; the second ends of the first capacitor 103 and the second ends of the second capacitor 104 are both grounded; the output terminals of the first sampling module 105 and the second sampling module 106 are electrically connected to the calculation module 107, respectively.

[0033] The first resistor 101 is used to protect the circuit and prevent the first capacitor 103 from being damaged by the large current at the moment of power-on, which would cause the first capacitor 103 to fail.

[0034] The second resistor, 102, is used for circuit protection, voltage sampling, and current calculation.

[0035] The first capacitor 103 and the second capacitor 104 are used to simulate the dynamic response process of the automotive battery system under transient operating conditions.

[0036] The first sampling module 105 is used to collect the total voltage of the battery pack of the car battery 200.

[0037] The second sampling module 106 is used to collect the voltage at the second terminal of the second resistor 102.

[0038] In the preferred embodiment of this application, please refer to Figure 2 , Figure 2 This is a second schematic diagram of the structure of an insulation resistance testing device for an automobile battery provided in an embodiment of this application, as shown below. Figure 2 As shown, the insulation resistance detection device 100 for the automotive battery may further include: a first switch 108, a second switch 109, a third switch 110, and a fourth switch 111; the first switch 108 is located between the first resistor 101 and the first capacitor 103; the second switch 109 is located between the second resistor 102 and the second capacitor 104; the third switch 110 is located between the first sampling module 105 and the positive terminal of the automotive battery 200; the fourth switch 111 is located between the second sampling module 106 and the second terminal of the second resistor 102; the first switch 108, the second switch 109, the third switch 110, and the fourth switch 111 are all electrically connected to the calculation module 107.

[0039] The following is a detailed description of an insulation resistance detection method for an automotive battery provided in the embodiments of this application. This insulation resistance detection method can be applied to the calculation module of the aforementioned automotive battery insulation resistance detection device.

[0040] Please see Figure 3 , Figure 3 This is a flowchart illustrating a method for detecting the insulation resistance of an automotive battery, as provided in an embodiment of this application. Figure 3 As shown in the embodiment of this application, the method for detecting the insulation resistance of an automotive battery includes the following steps:

[0041] S301, based on a preset sampling frequency, acquires the first voltage acquired by the first sampling module and the second voltage acquired by the second sampling module.

[0042] In this embodiment, the calculation module acquires a first voltage through a first sampling module and a second voltage through a second sampling module based on a preset sampling frequency. Here, the first voltage is the total voltage of the car battery pack, and the second voltage is the voltage at the second terminal of the second resistor. The preset sampling frequency is a sampling frequency set by the calculation module according to actual needs. For example, if 20 Hz is selected as the sampling frequency, then the calculation module acquires the first voltage once every 0.05 seconds through the first sampling module and the second voltage once every 0.05 seconds through the second sampling module.

[0043] In the embodiments of the present application, the first sampling module and the second sampling module are used to collect the voltage in the insulation resistance detection circuit, and various forms of analog to digital converters (ADC) can be selected as the voltage sampling circuit, which is not specifically limited here.

[0044] S302, for any sampling time, based on the first voltage, the second voltage collected at the sampling time and the forgetting factor least square algorithm, the undetermined coefficient vector of the equivalent circuit model of the insulation resistance detection circuit at the sampling time is determined; wherein the equivalent circuit model includes a first equivalent insulation resistance connected in parallel across the first capacitor and a second equivalent insulation resistance connected in parallel across the second capacitor.

[0045] Specifically, please refer to Figure 4 , Figure 4 The structure diagram of the equivalent circuit model of the insulation resistance detection circuit provided by the embodiments of the present application is shown in Figure 4 As shown, the embodiments of the present application equivalently connect the first equivalent insulation resistance R x in parallel across the first capacitor 103 to equivalently the positive-to-ground equivalent insulation resistance of the automobile battery, and equivalently connect the second equivalent insulation resistance R y in parallel across the second capacitor 104 to equivalently the negative-to-ground equivalent insulation resistance of the automobile battery. The equivalent circuit model takes into account both the accuracy of the model and the battery reaction mechanism, and is composed of electrical elements such as resistors and capacitors in a specific connection mode as shown in Figure 4 , wherein the first capacitor 103 and the second capacitor 104 are used to simulate the dynamic response of the entire battery system, so that the equivalent circuit model can accurately simulate the dynamic response and static process of the automobile battery under the same external excitation as the real vehicle, thereby realizing real-time detection of the insulation resistance of the automobile battery.

[0046] In this step, for any sampling time, the embodiments of the present application obtain the input and output of the equivalent circuit model of the insulation resistance detection circuit at the time based on the first voltage collected by the first sampling module at the time and the second voltage collected by the second sampling module at the time, and calculate the undetermined coefficient vector of the equivalent circuit model at the sampling time through the forgetting factor least square algorithm. Here, the undetermined coefficient vector is used to represent the coefficients of the transfer function of the first transfer function of the equivalent circuit model after bilinear transformation and discretization. Specifically, after bilinear transformation and discretization of the first transfer function of the equivalent circuit model , the discretized first transfer function expression is as follows:

[0047]

[0048] Here, each coefficient of the first transfer function after discretization is represented by a1-a5, and the undetermined coefficient vector is represented by The expression of the undetermined coefficient vector is shown as follows:

[0049]

[0050] where T represents a sampling period, which can be obtained according to a preset sampling frequency, and the transfer function is converted from the complex frequency domain to the time domain through bilinear transformation, which can eliminate part of the frequency aliasing of the equivalent circuit model and improve the calculation accuracy.

[0051] In S303, for any sampling time, the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling time are determined based on the undetermined coefficient vector at the sampling time and the target transfer function of the equivalent circuit model.

[0052] In the embodiments of the present application, the target transfer function of the equivalent circuit model is the ratio of the Laplace transform of the output voltage to the input current of the equivalent circuit model. The target transfer function can be expressed in two different ways, including a first transfer function represented by an undetermined coefficient vector , and a second transfer function represented by the parameters of each element in the equivalent circuit model and the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance.

[0053] Here, the undetermined coefficient vector at the sampling time is obtained through the forgetting factor least square algorithm. After that, the expression G(z -1 ) of the first transfer function after discretization is subjected to inverse bilinear transformation from the time domain to the complex frequency domain, to obtain the expression of the first transfer function of the equivalent circuit model represented by the undetermined coefficient vector .

[0054] Specifically, the expression of the first transfer function is shown as follows:

[0055]

[0056] Since the values of each undetermined coefficient in the undetermined coefficient vector are known, each coefficient in the first transfer function can be obtained. Moreover, since each coefficient in the transfer function of the equivalent circuit model can also be represented by each coefficient in the second transfer function represented by the parameters of each element in the equivalent circuit model and the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance, the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance can be calculated according to the values of each undetermined coefficient in the undetermined coefficient vector.

[0057] In a possible implementation, for any sampling moment, the undetermined coefficient vector of the equivalent circuit model of the insulation resistance detection circuit at the sampling moment is determined by the following steps:

[0058] Step a1, the difference between the first voltage and the second voltage is determined as the output voltage of the equivalent circuit model at the sampling moment.

[0059] In the embodiments of the present application, the first voltage is the total voltage of the battery pack at the sampling moment, and the second voltage is the voltage at the second end of the second resistor at the sampling moment. According to Kirchhoff's voltage law, the difference between the two is determined as the output voltage of the equivalent circuit model at the sampling moment.

[0060] Step a2, the ratio between the second voltage and the resistance value of the second resistor is determined as the input current of the equivalent circuit model at the sampling moment.

[0061] In the embodiments of the present application, the ratio between the second voltage and the resistance value of the second resistor is also the current value flowing through the second resistor at the sampling moment. According to Kirchhoff's current law, the current value flowing through the second resistor is determined as the input current of the equivalent circuit model at the sampling moment.

[0062] Step a3, the undetermined coefficient vector of the equivalent circuit model at the sampling moment is determined according to the output voltage, the input current at the sampling moment and at multiple sampling moments before the sampling moment, and a forgetting factor least square algorithm.

[0063] In the embodiments of the present application, the undetermined coefficient vector of the equivalent circuit model at any sampling moment is determined by a forgetting factor least square algorithm (Forgetting Factor Recursive Least Square, FFRLS). That is, during the operation of the automobile battery system, the calculation module collects a new set of output voltage and input current data of the equivalent circuit model every time, and then obtains the value of the undetermined coefficient in the undetermined coefficient vector at the current moment by correcting the value of the undetermined coefficient in the undetermined coefficient vector determined at the previous moment according to the output voltage and the input current at the sampling moment and at multiple sampling moments before the sampling moment, while introducing a forgetting factor to weaken the effect of old data and enhance the effect of new data, prevent the phenomenon of "filter saturation", and improve the accuracy of the determination of the undetermined coefficient vector to minimize the sum of errors.

[0064] Further, step a3 specifically includes:

[0065] Step b1, for any sampling time, determining the observation vector of the sampling time according to the difference equation of the first transfer function of the discretized equivalent circuit model of the sampling time; wherein the observation vector includes the output voltage and the input current at the sampling time and at a plurality of sampling times before the sampling time.

[0066] Specifically, for any sampling time k, the difference equation of the first transfer function of the discretized equivalent circuit model of the sampling time can be expressed by the following formula:

[0067] Y k = α1Y k-1 + α2Y k-2 + α3I k + α4I k-1 + α5I k-2 ;

[0068] In the formula, Y k is the output voltage of the current sampling time k, Y k-1 is the output voltage of the previous sampling time k-1 before the current sampling time, I k is the input current of the current sampling time k, I k-1 is the input current of the previous sampling time k-1 before the current sampling time, and I k-2 is the input current of the previous sampling time k-2 before the previous sampling time k-1.

[0069] And the observation vector of the sampling time is represented by Y k-1 , Y k-2 , I k , I k-1 , and I k-2 . As shown in the following formula:

[0070]

[0071] In the formula, T represents the transpose of the matrix.

[0072] Wherein, before starting to collect the first voltage and the second voltage based on the preset sampling frequency, the observation vector needs to be initialized, so that the calculation is performed by initializing the observation vector at the beginning of sampling, to solve the problem that there is no output voltage and input current at a plurality of times before the sampling time at the beginning of sampling.

[0073] Step b2, for any sampling time, the gain factor of the sampling time is determined according to the observation vector of the sampling time, the covariance matrix of the last sampling time and the preset forgetting factor; wherein the covariance matrix of the last sampling time is determined according to the observation vector of the last sampling time, the gain factor of the last sampling time, the covariance matrix of the last sampling time before the last sampling time and the preset forgetting factor.

[0074] Specifically, for any sampling time k, the gain factor K k which can be expressed by the following formula:

[0075]

[0076] In the formula, Y represents the observation vector of the sampling time K, P k-1 represents the covariance matrix of the last sampling time k-1, H k represents the transpose of the observation vector of the sampling time k, and λ represents the forgetting factor, and in the embodiment of the application, the preset forgetting factor λ=0.99.

[0077] Here, the covariance matrix P is updated during the operation of the system to make the obtained parameters converge. Specifically, the covariance matrix P k-1 which can be expressed by the following formula:

[0078]

[0079] In the formula, E represents the unit matrix, P k-2 represents the covariance matrix of the last sampling time k-2 before the last sampling time k-1.

[0080] Wherein, based on the same reason as above, before starting to collect the first voltage and the second voltage based on the preset sampling frequency, the covariance matrix P needs to be initialized to make the calculation through the initialized covariance matrix when the sampling starts.

[0081] Step b3, the undetermined coefficient vector of the sampling time is determined according to the observation vector of the sampling time, the gain factor of the sampling time, the output voltage of the sampling time and the undetermined coefficient vector of the last sampling time.

[0082] Specifically, for any sampling time k, the undetermined coefficient vector of the sampling time is which can be expressed by the following formula:

[0083]

[0084] In the formula, Y represents the undetermined coefficient vector of the last sampling time K-1;

[0085] As shown in the above formula, the actual observation value Y k at the current sampling time K is subtracted from the prediction value at the current sampling time K as the prediction error at the current sampling time K, and the prediction error at the current sampling time K is multiplied by the gain factor K k at the current sampling time K to obtain the correction value of the undetermined coefficient vector at the current sampling time K, and is added to the value of the undetermined coefficient vector determined at the previous sampling time K-1 before the current sampling time K, so as to obtain the undetermined coefficient vector

[0086] At the same time, based on the same reason, before starting to collect the first voltage and the second voltage based on the preset sampling frequency, the undetermined coefficient vector needs to be initialized so that the calculation through the undetermined coefficient vector can be performed at the beginning of sampling.

[0087] Moreover, in the process of recursive estimation of the least square algorithm, the more the sampling times, the smaller the mean square error caused by estimation. The insulation resistance value related information, i.e., the undetermined coefficient vector, extracted from the voltage collected at the current sampling time is used to correct the estimated value at the previous sampling time, and a forgetting factor is added to reduce the weight of historical data. With the progress of the estimation process, the estimation accuracy will be higher and higher, and thus the detection accuracy of the insulation resistance will be improved.

[0088] Therefore, further, in the embodiment of the application, the voltage sampling for a preset time can be performed first and the recursive estimation of the forgetting factor least square algorithm is performed. After the estimation accuracy of the undetermined coefficient vector is improved to a certain extent, the insulation resistance value is solved based on the undetermined coefficient vector, so as to further improve the detection accuracy of the insulation resistance. For example, only sampling and recursive estimation of the forgetting factor least square algorithm can be performed in the first 40 seconds after the start of sampling based on the preset frequency, and after 40 seconds of sampling, the insulation resistance value is solved based on the undetermined coefficient vector obtained by the forgetting factor least square algorithm at any sampling time after 40 seconds, so as to ensure the detection accuracy of the insulation resistance.

[0089] Further, S303 specifically includes:

[0090] c1, determining a second transfer function of an equivalent circuit model represented based on the first equivalent insulation resistance and the second equivalent insulation resistance according to the Kirchhoff's law and the Laplace transform; wherein the Kirchhoff's law is used to represent the relationship between the circuit parameters in the equivalent circuit model.

[0091] In this step, the first equivalent insulation resistance and the second equivalent insulation resistance are solved by the undetermined coefficient vector, and the coefficients of the second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance are obtained, and the coefficients of the same position in the first transfer function represented by the undetermined coefficient vector are established as equations to obtain the conversion relationship between the undetermined coefficient vector and the first equivalent insulation resistance and the second equivalent insulation resistance. The second transfer function of the equivalent circuit model can be constructed by the relationship between the circuit parameters in the equivalent circuit model characterized by Kirchhoff's law.

[0092] In step c2, the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling time are determined based on the first transfer function of the equivalent circuit model represented by the undetermined coefficient vector, the second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance, and the undetermined coefficient vector at the sampling time.

[0093] In this step, the coefficients of the first transfer function of the equivalent circuit model are represented by the undetermined coefficient vector, the coefficients of the second transfer function of the equivalent circuit model are represented by the first equivalent insulation resistance and the second equivalent insulation resistance, the coefficients of the same position of the first transfer function and the second transfer function are established as equations, the conversion relationship between the undetermined coefficient vector and the first equivalent insulation resistance and the second equivalent insulation resistance is solved, and the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling time are obtained by bringing the undetermined coefficient vector at the sampling time into the above conversion relationship.

[0094] Further, step c1 specifically includes:

[0095] In step d1, according to the relationship between the circuit parameters in the equivalent circuit model, the mathematical model of the sampling point voltage of the second sampling module represented by the first equivalent insulation resistance and the second equivalent insulation resistance is determined.

[0096] In this step, according to Kirchhoff's voltage law and Kirchhoff's current law, the relationship between the circuit parameters in the equivalent circuit model can be obtained as follows:

[0097] U 参考 = U BAT -IR 101 -U x -U y ;

[0098]

[0099]

[0100]

[0101]

[0102]

[0103] In the formula, U BAT U represents the sampling point voltage of the first sampling module, Ureference represents the sampling point voltage of the second sampling module, I represents the current value flowing through the equivalent circuit model, and R… 101 U represents the resistance value of the first resistor. x U represents the voltage across the first equivalent insulation resistance. y I represents the voltage across the second equivalent insulation resistance. x I represents the current flowing through the first equivalent insulation resistance. y R represents the current flowing through the second equivalent insulation resistance. x R represents the resistance value of the first equivalent insulation resistance. y I represents the resistance value of the second equivalent insulation resistance. 103 I represents the current flowing through the first capacitor. 104 R represents the current flowing through the second capacitor. 102 C represents the resistance value of the second resistor. 103 C represents the capacitance value of the first capacitor. 104 This indicates the capacitance value of the second capacitor.

[0104] Based on the relationship between the circuit parameters mentioned above, the first equivalent insulation resistance R can be determined. x Second equivalent insulation resistance R y The mathematical model for the sampling point voltage U reference of the second sampling module is shown in the following equation:

[0105]

[0106] In the formula, τ1 is the first time constant, τ1=R x C 103 τ2 is the second time constant, τ2=R y C 104 .

[0107] Step d2: Based on the relationship between the circuit parameters in the equivalent circuit model, the mathematical model of the input current of the equivalent circuit model is determined by the mathematical model of the sampling point voltage of the second sampling module and the resistance value of the second resistor.

[0108] In this step, based on the relationship between the circuit parameters in the equivalent circuit model described above, the mathematical model Ureference of the sampling point voltage Ureference of the second sampling module is obtained. ,t Second resistor R 102 The ratio of the resistance values ​​is used to determine the mathematical model of the input current I(t) in the equivalent circuit model, specifically as shown in the following equation:

[0109]

[0110] Step d3, according to the mathematical model of the sampling point voltage of the first sampling module and the mathematical model of the sampling point voltage of the second sampling module, determine the mathematical model of the output voltage of the equivalent circuit model.

[0111] In this step, according to the relationship between the circuit parameters in the above-mentioned equivalent circuit model, the difference between the mathematical model of the sampling point voltage U BAT,t of the first sampling module and the mathematical model of the sampling point voltage of the second sampling module U ,t is determined as the mathematical model Y(t) of the output voltage of the equivalent circuit model, specifically as shown in the following formula:

[0112]

[0113] Step d4, based on the mathematical model of the output voltage of the equivalent circuit model, the mathematical model of the input current and the Laplace transform formula, obtain the second transfer function of the equivalent circuit model.

[0114] In this step, the mathematical model Y(t) of the output voltage represented by the first equivalent insulation resistance R x and the second equivalent insulation resistance R y and the mathematical model I(t) of the input current represented by the first equivalent insulation resistance R x and the second equivalent insulation resistance R y are obtained by Laplace transform to obtain the expression of the second transfer function G(s) of the equivalent circuit model, as shown in the following formula:

[0115]

[0116] Specifically, according to the first transfer function of the equivalent circuit model represented by the undetermined coefficient vector, the second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance, the conversion relationship between the value of each undetermined coefficient in the undetermined coefficient vector and the resistance value of the first equivalent insulation resistance and the resistance value of the second equivalent insulation resistance can be obtained, as shown in the following formula:

[0117]

[0118]

[0119] In the formula, T is the sampling period, which can be obtained according to the preset sampling frequency. Since the first capacitance C 103 and the second capacitance C 104 are known quantities, the first equivalent insulation resistance R can be solved according to the undetermined coefficient vector calculated at any sampling time.x and the second equivalent insulation resistance R y The resistance value of the first equivalent insulation resistance and the second equivalent insulation resistance.

[0120] In a possible implementation, for any sampling time, after determining the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling time, the insulation resistance detection method further includes:

[0121] Step e1, determining the smaller resistance value between the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance as the resistance value of the insulation resistance of the automotive battery.

[0122] In the embodiments of the present application, since an excessively small insulation resistance can cause safety risks such as leakage of the automotive battery, the present application determines the smaller resistance value between the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance as the resistance value of the insulation resistance of the automotive battery, for judging the insulation performance of the automotive battery.

[0123] Step e2, determining that the automotive battery has a safety risk if the resistance value of the insulation resistance of the automotive battery is less than a preset safety insulation resistance threshold value.

[0124] In this step, when the resistance value of the insulation resistance of the automotive battery, that is, the smaller resistance value between the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance, is less than the preset safety insulation resistance threshold value, it is determined that the insulation performance of the automotive battery cannot meet the standard of being usable, and there is a safety risk.

[0125] Step e3, generating safety risk prompt information and sending the safety risk prompt information to a battery management system of the automotive battery.

[0126] In this step, the calculation module generates safety risk prompt information and sends the safety risk prompt information to a battery management system (BMS, Battery Management System) of the automotive battery, so that the BMS controls the battery to be powered off and performs maintenance inspection according to the safety risk prompt information.

[0127] In the embodiments of the present application, the processor of the battery management system BMS can also be directly used as the calculation module, and after it is determined that the automotive battery has a safety risk, the automotive battery is directly controlled to be powered off and maintenance inspection is performed.

[0128] In a preferred scheme of the embodiments of the present application, the detection method further includes:

[0129] Step f1, before collecting the first voltage collected by the first sampling module and the second voltage collected by the second sampling module based on the preset sampling frequency, the second switch is controlled to be closed at a first time, the first switch is controlled to be closed at a second time, and the third switch and the fourth switch are controlled to be closed at a third time; wherein the second time is after the first time, and the third time is after the second time.

[0130] In this step, in order to protect the safety of the insulation resistance detection circuit, prevent the first switch from being closed first to make the first capacitor accumulate positive potential, which will cause irreversible damage to the entire insulation circuit at the moment of closing the second switch, the computing module of the embodiment of the application first controls the second switch to be closed at the first time, so that the negative electrode of the automobile battery is grounded through the second resistor and the second capacitor, controls the first switch to be closed at the second time, so that the positive electrode of the automobile battery is grounded through the first resistor and the first capacitor, and finally controls the third switch and the fourth switch to be closed at the third time, so as to connect the first sampling module and the second sampling module into the insulation resistance detection circuit for sampling. Wherein the second time is after the first time, the third time is after the second time, and the time interval between the first time, the second time and the third time can be set according to actual conditions, which is not limited here.

[0131] Step f2, after completing the insulation resistance detection, the third switch and the fourth switch are controlled to be opened at a fourth time, the first switch is controlled to be opened at a fifth time, and the second switch is controlled to be opened at a sixth time; wherein the fifth time is after the fourth time, and the sixth time is after the fifth time.

[0132] In this step, in order to protect the safety of the insulation resistance detection circuit, the computing module of the embodiment of the application first controls the third switch and the fourth switch to be opened at the fourth time to protect the first sampling module and the second sampling module; controls the first switch to be opened at the fifth time to disconnect the positive electrode of the automobile battery from the first capacitor, so that the equivalent insulation resistance consumes the charge accumulated by the first capacitor, reducing the impact of the capacitor on the battery pack; finally, the second switch is controlled to be opened at the sixth time to disconnect the negative electrode of the automobile battery from the second capacitor. Wherein the fifth time is after the fourth time, the sixth time is after the fifth time, and the time interval between the fourth time, the fifth time and the sixth time can be set according to actual conditions, which is not limited here.

[0133] The following is a specific description of the method for detecting the insulation resistance of the automobile battery provided by the embodiment of the application:

[0134] The embodiment of the application mainly realizes real-time detection of the insulation resistance of the automobile battery through the following steps:

[0135] Step 1, an equivalent circuit model of the insulation resistance detection circuit is established, and the relationship between the circuit parameters of the equivalent circuit model is determined; specifically, according to the Kirchhoff's law and based on the equivalent circuit model of the insulation resistance detection circuit, the relationship between the circuit parameters of the equivalent circuit model is solved, and the input parameters and the output parameters of the equivalent circuit model system are determined according to the relationship between the parameters.

[0136] Step 2, a mathematical model of the sampling point voltage is determined.

[0137] Specifically, since the sampling point voltage can be directly obtained through the sampling circuit and is a directly measurable value, the accuracy can be guaranteed, so the sampling point voltage is a direct intuitive performance of the dynamic process of the equivalent circuit model, and the equivalent insulation resistance can be directly linked to the sampling point voltage by establishing a mathematical model.

[0138] Step 3, the transfer function relationship between the input and the output of the equivalent circuit model is obtained.

[0139] Specifically, if the mathematical model is to be applied to the least square algorithm, the mathematical model expression in the time domain needs to be converted into the mathematical model expression in the frequency domain. The transfer function relationship between the input and the output of the equivalent circuit model can be expressed in two ways, including a first transfer function represented by an undetermined coefficient vector, and a second transfer function represented by the parameters of each element in the equivalent circuit model and the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance.

[0140] Step 4, discretization of the transfer function.

[0141] Specifically, since continuous sampling cannot be performed in real processes, the transfer function needs to be discretized to meet the sampling side requirements, and since the bilinear transformation can not only maintain the original stability of the system, but also eliminate part of the frequency spectrum aliasing, the bilinear transformation is selected to discretize the transfer function.

[0142] Step 5, inverse transformation to solve the undetermined coefficient vector.

[0143] Specifically, after obtaining the undetermined coefficient vector with high accuracy through the least square recursive operation, the inverse transformation of the bilinear transformation is used to analyze the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance according to the corresponding relationship between the coefficient expression of the first transfer function and the coefficient expression of the second transfer function, thereby improving the accuracy of real-time detection of the insulation resistance detection.

[0144] The embodiment of the application provides a kind of automobile battery insulation resistance detection method, applied to the computing module of the insulation resistance detection device of automobile battery, insulation resistance detection device also includes insulation resistance detection circuit, insulation resistance detection circuit includes first resistance, second resistance, first capacitor, second capacitor, first sampling module and second sampling module;The positive pole of automobile battery is connected with the first end of first resistance and the input terminal of first sampling module respectively, the negative pole of automobile battery is connected with the first end of second resistance;The second end of first resistance is connected with the first end of first capacitor;The second end of second resistance is connected with the input terminal of second sampling module and the first end of second capacitor respectively;The second end of first capacitor and the second end of second capacitor are all grounded;The output terminal of first sampling module and the output terminal of second sampling module are electrically connected with computing module respectively;Detection method includes: based on preset sampling frequency, the first voltage collected by first sampling module and the second voltage collected by second sampling module;For any sampling time, based on the first voltage, the second voltage and the forgetting factor least square algorithm collected at the sampling time, determine the undetermined coefficient vector of the equivalent circuit model of insulation resistance detection circuit at the sampling time;Wherein, equivalent circuit model includes the first equivalent insulation resistance in parallel connected at the two ends of first capacitor and the second equivalent insulation resistance in parallel connected at the two ends of second capacitor;For any sampling time, based on the undetermined coefficient vector at the sampling time and the transfer function of equivalent circuit model, determine the resistance value of first equivalent insulation resistance and second equivalent insulation resistance at the sampling time.Such, through insulation resistance detection circuit simulates the dynamic response of automobile battery, and the undetermined coefficient vector of equivalent circuit model is updated in real time using forgetting factor least square algorithm to reduce output error, improve the accuracy of real-time detection of insulation resistance of automobile battery.

[0145] Based on the same application concept, the embodiment of the application also provides a computing module corresponding to the insulation resistance detection method of the automobile battery provided by the above-mentioned embodiment. Since the principle of solving problems in the computing module of the embodiment of the application is similar to the insulation resistance detection method of the above-mentioned embodiment of the application, the implementation of the computing module can be referred to the implementation of the method, and the repeated parts will not be described.

[0146] Please refer to Figure 5 , Figure 5 As shown in Figure 1, the computing module 107 includes: Figure 5

[0147] The sampling unit 1071 is configured to collect the first voltage collected by the first sampling module and the second voltage collected by the second sampling module based on the preset sampling frequency.

[0148] ​The first determination unit 1072 is configured to determine, for any sampling time, a to-be-determined coefficient vector of an equivalent circuit model of the insulation resistance detection circuit based on the first voltage, the second voltage and the forgetting factor least square algorithm collected at the sampling time, wherein the equivalent circuit model comprises a first equivalent insulation resistance connected in parallel to the first capacitor and a second equivalent insulation resistance connected in parallel to the second capacitor.

[0149] The second determination unit 1073 is configured to determine, for any sampling time, the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance based on the to-be-determined coefficient vector at the sampling time and a target transfer function of the equivalent circuit model.

[0150] In a possible implementation, the first determination unit 1072 is configured to determine, for any sampling time, the to-be-determined coefficient vector of the equivalent circuit model of the insulation resistance detection circuit by the following steps:

[0151] determining the difference between the first voltage and the second voltage as the output voltage of the equivalent circuit model at the sampling time, determining the ratio between the second voltage and the resistance value of the second resistor as the input current of the equivalent circuit model at the sampling time, and determining the to-be-determined coefficient vector of the equivalent circuit model at the sampling time according to the output voltage, the input current at the sampling time and at a plurality of sampling times before the sampling time, and the forgetting factor least square algorithm.

[0152] Further, when the first determination unit 1072 is configured to determine, for any sampling time, the to-be-determined coefficient vector of the equivalent circuit model at the sampling time according to the output voltage, the input current at the sampling time and at a plurality of sampling times before the sampling time, and the forgetting factor least square algorithm, the first determination unit 1072 is specifically configured to:

[0153] determine, for any sampling time, an observation vector at the sampling time according to a difference equation of the first transfer function of the discretized equivalent circuit model at the sampling time, wherein the observation vector comprises the output voltage and the input current at the sampling time and at a plurality of sampling times before the sampling time, determine, for any sampling time, a gain factor at the sampling time according to the observation vector at the sampling time, a covariance matrix at a previous sampling time and a preset forgetting factor, wherein the covariance matrix at the previous sampling time is determined according to the observation vector at the previous sampling time, the gain factor at the previous sampling time, a covariance matrix at a previous previous sampling time before the previous sampling time and the preset forgetting factor, and determine the to-be-determined coefficient vector at the sampling time according to the observation vector at the sampling time, the gain factor at the sampling time, the output voltage at the sampling time and the to-be-determined coefficient vector at the previous sampling time.

[0154] Further, the second determining unit 1073 is specifically configured to:

[0155] determine the second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance according to the Kirchhoff's law and the Laplace transform; wherein the Kirchhoff's law is used to represent the relationship between the circuit parameters in the equivalent circuit model; and determine the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling moment based on the first transfer function of the equivalent circuit model represented by the undetermined coefficient vector, the second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance, and the undetermined coefficient vector at the sampling moment.

[0156] Further, the second determining unit 1073 is specifically configured to:

[0157] determine the mathematical model of the sampling point voltage of the second sampling module represented by the first equivalent insulation resistance and the second equivalent insulation resistance according to the relationship between the circuit parameters in the equivalent circuit model; determine the mathematical model of the input current of the equivalent circuit model according to the mathematical model of the sampling point voltage of the second sampling module and the resistance value of the second resistance; determine the mathematical model of the output voltage of the equivalent circuit model according to the mathematical model of the sampling point voltage of the first sampling module and the mathematical model of the sampling point voltage of the second sampling module; and obtain the second transfer function of the equivalent circuit model based on the mathematical model of the output voltage of the equivalent circuit model, the mathematical model of the input current, and the Laplace transform formula.

[0158] In a possible implementation, referring to Figure 6 , Figure 6 Figure 2 is a functional module diagram of a calculation module provided by an embodiment of the present application, as Figure 6 shown, the calculation module 107 further includes:

[0159] The third determining unit 1074 is configured to determine the smaller resistance value between the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance as the resistance value of the insulation resistance of the automobile battery.

[0160] The judging unit 1075 is configured to determine that the automobile battery has a safety risk if the resistance value of the insulation resistance of the automobile battery is less than the preset safety insulation resistance threshold value.

[0161] The sending unit 1076 is configured to generate the security risk prompt information and send the security risk prompt information to the battery management system of the automobile battery.

[0162] In the preferred embodiment of the present application, as shown in Figure 6 The computing module 107 further includes:

[0163] The first control unit 1077 is configured to control the second switch to be closed at a first time, control the first switch to be closed at a second time, and control the third switch and the fourth switch to be closed at a third time before collecting the first voltage collected by the first sampling module and the second voltage collected by the second sampling module based on a preset sampling frequency, wherein the second time is after the first time, and the third time is after the second time.

[0164] The second control unit 1078 is configured to control the third switch and the fourth switch to be opened at a fourth time, control the first switch to be opened at a fifth time, and control the second switch to be opened at a sixth time after completing the insulation resistance detection, wherein the fifth time is after the fourth time, and the sixth time is after the fifth time.

[0165] The computing module provided by the embodiment of the application is applied to the insulation resistance detection device of the automobile battery. The insulation resistance detection device further comprises an insulation resistance detection circuit. The insulation resistance detection circuit comprises a first resistor, a second resistor, a first capacitor, a second capacitor, a first sampling module and a second sampling module. The positive electrode of the automobile battery is connected with the first end of the first resistor and the input end of the first sampling module respectively. The negative electrode of the automobile battery is connected with the first end of the second resistor. The second end of the first resistor is connected with the first end of the first capacitor. The second end of the second resistor is connected with the input end of the second sampling module and the first end of the second capacitor respectively. The second end of the first capacitor and the second end of the second capacitor are both grounded. The output end of the first sampling module and the output end of the second sampling module are electrically connected with the computing module respectively. The computing module comprises: a sampling unit, configured to collect the first voltage collected by the first sampling module and the second voltage collected by the second sampling module based on a preset sampling frequency; a first determination unit, configured to determine, for any sampling moment, the undetermined coefficient vector of the equivalent circuit model of the insulation resistance detection circuit based on the first voltage, the second voltage collected at the sampling moment and the forgetting factor least square algorithm. The equivalent circuit model comprises a first equivalent insulation resistance connected in parallel across the first capacitor and a second equivalent insulation resistance connected in parallel across the second capacitor. A second determination unit, configured to determine, for any sampling moment, the resistance value of the first equivalent insulation resistance and the second equivalent insulation resistance based on the undetermined coefficient vector at the sampling moment and the target transfer function of the equivalent circuit model. In this way, the dynamic response of the automobile battery is simulated by the insulation resistance detection circuit, and the undetermined coefficient vector of the equivalent circuit model is updated in real time by using the forgetting factor least square algorithm to reduce the output error, thereby improving the accuracy of real-time detection of the insulation resistance of the automobile battery.

[0166] Based on the same application concept, the embodiment of the application further provides an automobile comprising the insulation resistance detection device of the automobile battery as described above and adopting the insulation resistance detection method of the automobile battery as described above to detect the insulation resistance of the automobile battery. Details are not repeated.

[0167] Please refer to Figure 7 , Figure 7 The structure schematic diagram of an electronic device 700 provided by the embodiment of the application comprises a processor 710, a memory 720 and a bus 730.

[0168] The memory 720 stores machine readable instructions executable by the processor 710. When the electronic device 700 is running, the processor 710 and the memory 720 communicate through the bus 730. The machine readable instructions are executed by the processor 710 to perform the steps of the insulation resistance detection method of the automobile battery provided by the above embodiment. The specific implementation mode can be referred to the method embodiment, and details are not repeated here.

[0169] The application further provides a computer readable storage medium, which stores a computer program. When the computer program is run by a processor, the steps of the automobile battery insulation resistance detection method provided by the above-mentioned embodiments are executed. For details, refer to the method embodiments, which will not be described here.

[0170] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned device and unit can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0171] In the embodiments provided in the present application, it should be understood that the disclosed method, module and device can be implemented in other ways. The above-described device embodiments are only schematic, for example, the division of the units is only a logical function division, and there can be another division manner in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection can be indirect coupling or communication connection through some communication interfaces, devices or units, and can be electrical, mechanical or other forms.

[0172] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the present embodiment scheme.

[0173] In addition, each functional unit in the embodiments provided in the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0174] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0175] It should be noted that similar reference numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", "third" and the like are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0176] Finally, it should be noted that the above-described embodiments are only specific implementations of the present application, which are used to illustrate the technical solutions of the present application, but not to limit them. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily think of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed by the present application, or make equivalent replacements to some of the technical features. These modifications, changes or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application. They should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method of detecting an insulation resistance of an automobile battery, characterized by, The application relates to a computing module of an insulation resistance detection device applied to an automobile battery, wherein the insulation resistance detection device further comprises an insulation resistance detection circuit, the insulation resistance detection circuit comprises a first resistor, a second resistor, a first capacitor, a second capacitor, a first sampling module and a second sampling module; a positive electrode of the automobile battery is connected with a first end of the first resistor and an input end of the first sampling module; a negative electrode of the automobile battery is connected with a first end of the second resistor; a second end of the first resistor is connected with a first end of the first capacitor; a second end of the second resistor is connected with an input end of the second sampling module and a first end of the second capacitor; a second end of the first capacitor and a second end of the second capacitor are grounded; an output end of the first sampling module and an output end of the second sampling module are electrically connected with the computing module; the detection method comprises the following steps: Based on a preset sampling frequency, a first voltage collected by the first sampling module and a second voltage collected by the second sampling module are collected; For any sampling moment, based on the first voltage, the second voltage and a forgetting factor least square algorithm collected at the sampling moment, a to-be-determined coefficient vector of an equivalent circuit model of the insulation resistance detection circuit at the sampling moment is determined; wherein the equivalent circuit model comprises a first equivalent insulation resistance connected in parallel between the first capacitor and a second equivalent insulation resistance connected in parallel between the second capacitor; For any sampling moment, based on the to-be-determined coefficient vector at the sampling moment and a target transfer function of the equivalent circuit model, the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling moment are determined.

2. The insulation resistance detection method according to claim 1, characterized by, For any sampling moment, the to-be-determined coefficient vector of the equivalent circuit model of the insulation resistance detection circuit at the sampling moment is determined through the following steps: The difference between the first voltage and the second voltage is determined as the output voltage of the equivalent circuit model at the sampling moment; The ratio between the second voltage and the resistance value of the second resistor is determined as the input current of the equivalent circuit model at the sampling moment; The to-be-determined coefficient vector of the equivalent circuit model at the sampling moment is determined according to the output voltage, the input current at the sampling moment and at multiple sampling moments before the sampling moment and the forgetting factor least square algorithm.

3. The insulation resistance detection method according to claim 2, characterized by, The to-be-determined coefficient vector of the equivalent circuit model at the sampling moment is determined according to the output voltage, the input current at the sampling moment and at multiple sampling moments before the sampling moment and the forgetting factor least square algorithm, and comprises the following steps: For any sampling moment, the observation vector at the sampling moment is determined according to the difference equation of the first transfer function of the equivalent circuit model after discretization at the sampling moment; wherein the observation vector comprises the output voltage and the input current at the sampling moment and at multiple sampling moments before the sampling moment. For any sampling time, a gain factor of the sampling time is determined according to an observation vector of the sampling time, a covariance matrix of a previous sampling time, and a preset forgetting factor; wherein the covariance matrix of the previous sampling time is determined according to an observation vector of the previous sampling time, a gain factor of the previous sampling time, a covariance matrix of the previous sampling time before the previous sampling time, and the preset forgetting factor; A to-be-determined coefficient vector of the sampling time is determined according to the observation vector of the sampling time, the gain factor of the sampling time, an output voltage of the sampling time, and a to-be-determined coefficient vector of a previous sampling time.

4. The insulation resistance detection method according to claim 1, characterized by, For any sampling time, the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance of the sampling time are determined based on the to-be-determined coefficient vector of the sampling time and a target transfer function of the equivalent circuit model, and the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance of the sampling time are determined based on the to-be-determined coefficient vector of the sampling time and the target transfer function of the equivalent circuit model, comprising: A second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance is determined according to Kirchhoff's law and Laplace transform; wherein Kirchhoff's law is used to represent the relationship between the circuit parameters in the equivalent circuit model; The resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance of the sampling time are determined based on the first transfer function of the equivalent circuit model represented by the to-be-determined coefficient vector, the second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance, and the to-be-determined coefficient vector of the sampling time.

5. The insulation resistance detection method according to claim 4, characterized by, The second transfer function of the equivalent circuit model represented by the first equivalent insulation resistance and the second equivalent insulation resistance is determined according to Kirchhoff's law and Laplace transform, comprising: A mathematical model of the sampling point voltage of the second sampling module represented by the first equivalent insulation resistance and the second equivalent insulation resistance is determined according to the relationship between the circuit parameters in the equivalent circuit model; A mathematical model of the input current of the equivalent circuit model is determined according to the mathematical model of the sampling point voltage of the second sampling module and the resistance value of the second resistance according to the relationship between the circuit parameters in the equivalent circuit model; A mathematical model of the output voltage of the equivalent circuit model is determined according to the mathematical models of the sampling point voltage of the first sampling module and the sampling point voltage of the second sampling module; The second transfer function of the equivalent circuit model is obtained based on the mathematical model of the output voltage of the equivalent circuit model, the mathematical model of the input current, and the Laplace transform formula.

6. The insulation resistance detection method according to claim 1, characterized by, For any sampling time, after the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance of the sampling time are determined, the insulation resistance detection method further comprises: The smaller resistance value of the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance is determined as the resistance value of the insulation resistance of the automobile battery; If the resistance value of the insulation resistance of the automobile battery is less than a preset safe insulation resistance threshold value, it is determined that the automobile battery has a safety risk. Generate a security risk prompt information, send to the battery management system of the automobile battery.

7. The method of claim 1, wherein The insulation resistance detection circuit further comprises a first switch, a second switch, a third switch and a fourth switch; the first switch is located between the first resistor and the first capacitor; the second switch is located between the second resistor and the second capacitor; the third switch is located between the first sampling module and the positive electrode of the automobile battery; the fourth switch is located between the second sampling module and the second end of the second resistor; The first switch, the second switch, the third switch and the fourth switch are electrically connected with the calculation module; the detection method further comprises: Before collecting the first voltage collected by the first sampling module and the second voltage collected by the second sampling module based on the preset sampling frequency, the second switch is controlled to be closed at the first time, the first switch is controlled to be closed at the second time, and the third switch and the fourth switch are controlled to be closed at the third time; wherein the second time is after the first time, and the third time is after the second time; After completing the insulation resistance detection, the third switch and the fourth switch are controlled to be opened at the fourth time, the first switch is controlled to be opened at the fifth time, and the second switch is controlled to be opened at the sixth time; wherein the fifth time is after the fourth time, and the sixth time is after the fifth time.

8. A computing module, characterized by The insulation resistance detection device applied to the automobile battery further comprises an insulation resistance detection circuit, the insulation resistance detection circuit comprises a first resistor, a second resistor, a first capacitor, a second capacitor, a first sampling module and a second sampling module; the positive electrode of the automobile battery is connected with the first end of the first resistor and the input end of the first sampling module respectively, and the negative electrode of the automobile battery is connected with the first end of the second resistor; the second end of the first resistor is connected with the first end of the first capacitor; the second end of the first capacitor is grounded; the second end of the second resistor is connected with the input end of the second sampling module and the first end of the second capacitor respectively; the second end of the second capacitor is grounded; The output end of the first sampling module and the output end of the second sampling module are electrically connected with the calculation module respectively; The calculation module comprises: A sampling unit is configured to collect the first voltage collected by the first sampling module and the second voltage collected by the second sampling module based on a preset sampling frequency; A first determination unit is configured to determine, for any sampling time, an undetermined coefficient vector of an equivalent circuit model of the insulation resistance detection circuit at the sampling time based on the first voltage, the second voltage collected at the sampling time and a forgetting factor least square algorithm; wherein the equivalent circuit model comprises a first equivalent insulation resistance connected in parallel across the first capacitor and a second equivalent insulation resistance connected in parallel across the second capacitor; A second determination unit is configured to determine, for any sampling time, the resistance values of the first equivalent insulation resistance and the second equivalent insulation resistance at the sampling time based on the undetermined coefficient vector at the sampling time and a target transfer function of the equivalent circuit model.

9. An insulation resistance detecting device for an automobile battery, characterized by comprising: The insulation resistance detection device comprises: The insulation resistance detection device comprises:

10. An automobile characterized by comprising: The insulation resistance detection device comprises:

Images