Insulation testing method and system for electric vehicle, and electric vehicle

Abstract

An insulation testing method for an electric vehicle, comprising: defining system parameters of an insulation monitoring module of a battery management system (BMS) (S110); starting an insulation test task of a powertrain domain control system (PDCS) on the BMS on the basis of the system parameters (S120); collecting the system parameters on the basis of a hardware part of the BMS (S130); determining calculation logic for an original insulation resistance value on the basis of a software part of the BMS, and calculating the original insulation resistance value on the basis of the calculation logic (S140); performing data processing on the original insulation resistance value (S150); and determining an insulation test result of the electric vehicle on the basis of the original insulation resistance value subjected to the data processing (S160). Data detection of the insulation resistance of the electric vehicle is realized by means of the domination of the BMS and the assistance of the PDCS. Also provided are an insulation testing system for an electric vehicle, and an electric vehicle.

Description

Electric vehicle insulation detection method, system and electric vehicle Technical Field

[0001] The present invention relates to the technical field of insulation resistance detection of electric vehicles, and in particular to an insulation detection method and system for electric vehicles and the electric vehicle. Background Art

[0002] With the increasing popularity of electric vehicles, their safety is receiving increasing attention, particularly regarding the insulation safety of power batteries. Due to the high voltage levels of power batteries, a high-voltage leak can be dangerous. Therefore, insulation testing of electric vehicles is a measure to ensure both human safety and equipment protection. Effectively testing the insulation resistance of electric vehicles, whether riding in or driving an electric vehicle, or performing vehicle maintenance, remains a significant design challenge and a significant pain point in the industry.

[0003] In the industry, insulation resistance testing solutions are typically based on the balanced bridge method. While the balanced bridge method uses two bridge arms, the unbalanced bridge method uses a single bridge arm. Furthermore, the software algorithms often lack reliable data processing mechanisms and hardware fault definitions. This results in wasted hardware components, increased design costs, and reduced insulation resistance test reliability.

[0004] Summary of the Invention

[0005] The object of the present invention is to solve one of the above-mentioned technical problems at least to a certain extent.

[0006] To this end, the first object of the present invention is to propose an insulation detection method for an electric vehicle, which realizes data detection of the insulation resistance of the electric vehicle through the leadership of the battery management system BMS and the assistance of the power domain controller PDCS.

[0007] A second object of the present invention is to provide an insulation detection system for an electric vehicle.

[0008] The third object of the present invention is to provide an electric vehicle.

[0009] A fourth object of the present invention is to provide an electronic device.

[0010] A fifth object of the present invention is to provide a non-transitory computer-readable storage medium.

[0011] To achieve the above-mentioned object, a first embodiment of the present invention provides an insulation detection method for an electric vehicle, comprising:

[0012] Define the system parameters of the insulation monitoring module of the battery management system BMS;

[0013] Initiate, based on the system parameters, an insulation detection task of the power domain controller PDCS on the battery management system BMS;

[0014] Collecting the system parameters based on the hardware part of the battery management system BMS;

[0015] determining a calculation logic for an original insulation resistance value based on a software portion of the battery management system (BMS) and calculating the original insulation resistance value based on the calculation logic;

[0016] performing data processing on the original value of the insulation resistance;

[0017] An insulation test result of the electric vehicle is determined based on the original insulation resistance value after data processing.

[0018] According to one embodiment of the present invention, the system parameters of the insulation monitoring module of the battery management system BMS are defined as follows:

[0019] The battery management system BMS collects and calculates the voltage of the battery pack Pack+_GND as Up;

[0020] The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack+_GND as Rp;

[0021] The battery management system BMS collects and calculates the voltage of the battery pack Pack-_GND as Un;

[0022] The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack-_GND as Rn;

[0023] The battery management system BMS collects and calculates the voltage of the battery pack Pack+_Pack- as Ubattery;

[0024] A=R1+R2, B=R3+R4, C=(R3+R4) / / R2;

[0025] Among them, A is called by the software formula and is defined as the simplified calculation coefficient of resistance; B is called by the software formula and is defined as the simplified calculation coefficient of resistance; C is called by the software formula and is defined as the simplified calculation coefficient of resistance;

[0026] R1 is the voltage divider resistor 1 of the positive arm of the unbalanced bridge method; R2 is the voltage divider resistor 2 of the positive arm of the unbalanced bridge method; R3 is the voltage divider resistor 1 of the negative arm of the unbalanced bridge method; R4 is the voltage divider resistor 2 of the negative arm of the unbalanced bridge method;

[0027] Un1(a) shows the first time the software delays 10ms to collect data after Q2 is closed. The data is filtered and output to the battery management system (BMS) for calculation of the battery pack-GND voltage. Un1(b) shows the second time the software delays 10ms to collect data after Q2 is closed. The data is filtered and output to the battery management system (BMS) for calculation of the battery pack-GND voltage.

[0028] Un2(a) is the first time the software delays 10ms to collect data after Q1 is closed. After filtering and processing the data, the battery management system BMS collects and calculates the voltage between the battery pack Pack and GND. Un2(b) is the second time the software delays 10ms to collect data after Q1 is closed. After filtering and processing the data, the battery management system BMS collects and calculates the voltage between the battery pack Pack and GND.

[0029] Determine the filter sensitivity coefficients KRiso1=|Un1(a) / Un1(b)| and KRiso2=|Un2(a) / Un2(b)| of the insulation resistance value of the battery management system BMS;

[0030] Send the vehicle insulation resistance value Riso to the power domain controller PDCS;

[0031] Among them, the calculation method of Riso is: the voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND superimposed, that is, Ubattery=Up1+Un1=Up2+Un2, so we get formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2;

[0032] The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, and Un2 collected by the BMS hardware are set to be known parameters for the battery management system BMS software, and the values ​​of A, B, C, Ubattery, Un1, and Un2 are known parameters for the battery management system BMS software;

[0033] Rp and Rn are unknown numbers, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, and Un2 are substituted into the quotient equation to derive the correlation calculation formula for the unknown parameters Rp and Rn and the known parameters A, B, C, Ubattery, Un1, and Un2. Then, based on the correlation calculation formula and combined with the collected known values ​​Ubattery, Un1, and Un2, the values ​​of Rp and Rn are solved.

[0034] According to one embodiment of the present invention, starting the insulation detection task of the power domain controller PDCS on the battery management system BMS based on the system parameters includes:

[0035] Starting the vehicle, waking up the power domain controller PDCS based on a key ignition signal, and waking up the battery management system BMS based on a hard-wired wake-up signal PDCS-Wakeup-BMS sent by the power domain controller PDCS;

[0036] The power domain controller PDCS implements and completes the whole vehicle high-voltage process of the electric vehicle, the main positive high-voltage contactor and the main negative high-voltage contactor are closed, and at the same time, the power domain controller PDCS sends an insulation detection enable instruction to the battery management system BMS through CAN communication. After receiving the insulation detection enable instruction, the battery management system BMS starts the insulation detection task.

[0037] According to one embodiment of the present invention, collecting the system parameters based on the hardware part of the battery management system BMS includes:

[0038] The hardware circuit of the battery management system BMS calculates the original value of the insulation resistance through software, and the collection and implementation mechanism of the required associated data is as follows:

[0039] The MCU outputs a 3.3V high-level signal Do_Q3_Enable to enable transistor Q3 to close. The voltage of Ubattery is obtained by collecting the 0-2.5V analog signal AI_Pack+_Pack-_AD and calculating.

[0040] The MCU outputs a 3.3V high-level signal Do_Q2_Enable to enable transistor Q2 to close. The voltage of Un1 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating.

[0041] The microcontroller MCU outputs a 3.3V high-level signal Do_Q1_Enable to enable transistor Q1 to close, and the voltage of Un2 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating.

[0042] According to one embodiment of the present invention, determining the calculation logic of the original insulation resistance value based on the software portion of the battery management system BMS and calculating the original insulation resistance value based on the calculation logic includes:

[0043] The voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND superimposed, that is, Ubattery=Up1+Un1=Up2+Un2, so we get formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2;

[0044] The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, and Un2 collected by the BMS hardware are set to be known parameters for the battery management system BMS software, and the values ​​of A, B, C, Ubattery, Un1, and Un2 are known parameters for the battery management system BMS software;

[0045] Rp and Rn are unknown numbers, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, and Un2 are substituted into the quotient equation to derive the correlation calculation formula for the unknown parameters Rp and Rn and the known parameters A, B, C, Ubattery, Un1, and Un2. Then, based on the correlation calculation formula and combined with the collected known values ​​Ubattery, Un1, and Un2, the values ​​of Rp and Rn are solved.

[0046] According to one embodiment of the present invention, the data processing of the original insulation resistance value includes:

[0047] After the MCU enables Q2 and closes, the battery management system BMS insulation detection sampling delay is 100ms, and the Un1 voltage is sampled 5 times with a sampling period of 10ms. After the software filters the data, the voltage of Un1(a) is output; the voltage Un1 is sampled 5 times with a sampling period of 10ms, and the software filters the data and outputs the voltage Un1(b). At this time, if the software of the battery management system BMS determines that KRiso1 = |Un1(a) / Un1(b)| ≥ 0.99, the value is assigned so that Un1(b) = Un1;

[0048] After the MCU enables Q1 and closes, it samples the voltage Un2 five times with a delay of 100ms, with a sampling period of 10ms. After the software filters and processes the data, it outputs the voltage Un2(a). After a delay of 500ms, it samples the voltage Un2 five times with a sampling period of 10ms. After the software filters and processes the data, it outputs the voltage Un2(b). At this time, if the software of the battery management system BMS determines that KRiso2 = |Un2(a) / Un2(b)| ≥ 0.99, it assigns a value so that Un2 = Un2(b).

[0049] If the original insulation resistance value cannot be calculated within the maximum calculation time of 20 seconds, it is determined that the insulation circuit of the battery management system BMS has a fault and reported;

[0050] After the MCU enables Q1 and disconnects, it samples the voltage Un1 for a total of 5 times with a delay of 100ms, with a sampling period of 10ms. After the software filters and processes the data, it outputs the voltage of Un1(a). It samples the voltage Un1 for a total of 5 times with a delay of 500ms, with a sampling period of 10ms. After the software filters and processes the data, it outputs the voltage Un1(b). At this time, if the software of the battery management system BMS determines that KRiso1 = |Un1(a) / Un1(b)|≥0.99, then the value is assigned so that Un1(b) = Un1.

[0051] According to one embodiment of the present invention, determining the insulation detection result of the electric vehicle based on the original insulation resistance value after data processing includes:

[0052] After the battery management system BMS uploads the insulation resistance raw value data Rp of the battery pack Pack+_GND and the insulation resistance raw value data Rn of the battery pack Pack-GND to the system parameter startup power domain controller PDCS via CAN communication, the software of the system parameter startup power domain controller PDCS processes the insulation resistance raw value data Rp of the battery pack Pack+_GND and the insulation resistance raw value data Rn of the battery pack Pack-_GND;

[0053] If Rp is less than Rn, the system parameter starts the power domain controller PDCS software assignment so that Riso = Rp;

[0054] If Rp is greater than Rn, the system parameter starts the power domain controller PDCS software assignment so that Riso = Rn;

[0055] If Rp is equal to Rn, the system parameter starts the power domain controller PDCS software assignment so that Riso = Rp = Rn;

[0056] After the data comparison and assignment, the system parameters start the power domain controller PDCS to send the Riso value to the Tbox in real time via Ethernet. The TBox is used for vehicle big data communication and data transfer. The mobile app and the backend system, as the user end, complete the real-time viewing of the vehicle insulation information through the Tbox's vehicle big data communication data transfer.

[0057] The system parameters start the power domain controller PDCS to perform an insulation resistance detection alarm processing algorithm based on the Riso value, thereby promptly alerting the driver and after-sales maintenance personnel when the vehicle insulation working condition is poor; the insulation resistance detection alarm processing algorithm includes:

[0058] When Riso≤50K, a level 3 insulation resistance detection alarm is performed;

[0059] When Riso≤120K, a level 2 insulation resistance detection alarm is performed;

[0060] When Riso≤250K, a level 1 insulation resistance detection alarm is performed.

[0061] To achieve the above objectives, a second embodiment of the present invention provides an insulation detection system for an electric vehicle, comprising:

[0062] Definition module, used to define the system parameters of the insulation monitoring module of the battery management system BMS;

[0063] A first detection module is configured to start an insulation detection task of the battery management system BMS by the power domain controller PDCS based on the system parameters;

[0064] A parameter acquisition module, configured to acquire the system parameters based on the hardware of the battery management system BMS;

[0065] a calculation module, configured to determine a calculation logic for an original insulation resistance value based on a software portion of the battery management system BMS and calculate the original insulation resistance value based on the calculation logic;

[0066] A data processing module, configured to process the original insulation resistance value;

[0067] The second detection module is used to determine the insulation detection result of the electric vehicle based on the original value of the insulation resistance after data processing.

[0068] To achieve the above-mentioned object, a third embodiment of the present invention provides an electric vehicle, which includes any embodiment of the insulation detection system for an electric vehicle in the second aspect.

[0069] To achieve the above-mentioned object, an electronic device provided in a fourth embodiment of the present invention includes:

[0070] a memory for storing computer-executable instructions; and

[0071] A processor is used to run the computer executable instructions to execute any embodiment of the insulation detection method for an electric vehicle in the first aspect.

[0072] To achieve the above-mentioned purpose, the fifth aspect of the present invention proposes a non-transitory computer-readable storage medium, on which computer-executable instructions are stored. When the instructions are executed by a computer, the computer executes any embodiment of the insulation detection method for an electric vehicle in the first aspect.

[0073] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned through practice of the present invention.

[0074] Compared with the prior art, the beneficial effects of the embodiments of the present application are:

[0075] The present invention provides an insulation detection method, system, and electric vehicle for electric vehicles. The method realizes data detection of the insulation resistance of electric vehicles through the leadership of the battery management system (BMS) and the assistance of the power domain controller (PDCS). Specifically, the method has the following advantages:

[0076] (1) The design scheme adopts the unbalanced bridge method, which uses a single bridge arm. It saves the cost of hardware components and reduces the difficulty of hardware design and software design, thereby improving the reliability of the insulation detection design scheme of the battery management system BMS.

[0077] (2) The software data processing algorithm of the battery management system BMS delays data collection when the multiple hardware switches Q2 and Q1 are opened and closed respectively, so as to avoid the interference of electromagnetic noise generated by the moment of opening and closing of the hardware switches on the software data collection.

[0078] (3) The battery management system BMS collects insulation detection-related data multiple times, and at the same time introduces the filter sensitivity coefficients KRiso1 and KRiso2 of the insulation resistance value of the battery management system BMS. In this way, when the effective insulation resistance collection value is obtained, it can also be determined whether the battery management system BMS has an insulation resistance hardware collection failure.

[0079] (4) The battery management system (BMS) is responsible for collecting, calculating, and uploading the parsed raw insulation resistance data to the power domain controller (PDCS). The power domain controller (PDCS) further implements a multi-level insulation resistance alarm and early warning mechanism, thereby improving the system reliability of insulation resistance monitoring.

[0080] (5) The power domain controller PDCS sends the Riso value to the Tbox in real time via Ethernet. The mobile app and the backend system, as the user end, can complete the real-time viewing of the vehicle insulation information through the data transfer of Tbox, so that users and after-sales maintenance personnel can remotely understand the insulation resistance operating status in the vehicle and realize the synchronization of the vehicle data and the backend system.

[0081] To better understand the technical means of the present invention and to facilitate implementation in accordance with the description, and to make the above-mentioned and other purposes, features, and advantages of the present invention more readily apparent, preferred embodiments are described below in detail with reference to the accompanying drawings. Other features and advantages of the present invention will be explained in the subsequent description and, in part, will become apparent from the description or be demonstrated through the practice of the present invention. The purposes and other advantages of the present invention may be achieved and attained through the structures particularly noted in the description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] In order to more clearly illustrate the technical solutions in the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0083] FIG1 is a flow chart of an insulation detection method for an electric vehicle according to an embodiment of the present invention;

[0084] FIG2 is a flow chart of an insulation detection method for an electric vehicle according to a specific embodiment of the present invention;

[0085] FIG3 is a schematic structural diagram of an insulation detection system for an electric vehicle according to an embodiment of the present invention;

[0086] FIG4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0087] The embodiments of the present invention are described in detail below, wherein examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0088] With the increasing popularity and intelligence of electric vehicles, their safety is receiving increasing attention, especially the insulation safety of power batteries. Since power batteries have high voltage levels, a high-voltage leak can be dangerous. Therefore, insulation testing of electric vehicles is a measure to ensure human safety and protect equipment. Therefore, how to effectively test the insulation resistance of electric vehicles is an urgent problem that needs to be solved in the industry.

[0089] To this end, the present invention provides an insulation detection method and system for an electric vehicle and the electric vehicle.

[0090] Specifically, the insulation detection method and system for an electric vehicle and the electric vehicle according to embodiments of the present invention are described below with reference to the accompanying drawings.

[0091] FIG1 is a flow chart of an insulation detection method for an electric vehicle provided according to an embodiment of the present invention, and FIG2 is a flow chart of an insulation detection method for an electric vehicle provided according to a specific embodiment of the present invention; it should be noted that the insulation detection method for an electric vehicle according to the embodiment of the present invention can be applied to the insulation detection system for an electric vehicle according to the embodiment of the present invention, which can be configured on an electronic device or in a server.

[0092] The electronic device may be a PC or a mobile terminal (eg, a smart phone, a tablet computer, etc.), which is not limited in this embodiment of the present invention.

[0093] 1-2 , this embodiment provides an insulation detection method for an electric vehicle, which implements data detection of the insulation resistance of the electric vehicle through the leadership of a battery management system BMS and the assistance of a power domain controller PDCS.

[0094] Among them, the hardware corresponding to the insulation detection method of electric vehicles is mainly divided into two parts, namely the battery pack part and the vehicle part.

[0095] The battery pack part includes the insulation monitoring module of the battery and battery management system BMS; the vehicle part includes the power domain controller PDCS and the communication data management controller TBOX.

[0096] Specifically, the method includes:

[0097] S110, defining system parameters of the insulation monitoring module of the battery management system BMS;

[0098] The system parameters defining the insulation monitoring module of the battery management system BMS include:

[0099] The battery management system BMS collects and calculates the voltage of the battery pack Pack+_GND as Up;

[0100] The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack+_GND as Rp;

[0101] The battery management system BMS collects and calculates the voltage of the battery pack Pack-_GND as Un;

[0102] The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack-_GND as Rn;

[0103] The battery management system BMS collects and calculates the voltage of the battery pack Pack+_Pack- as Ubattery;

[0104] A=R1+R2, B=R3+R4, C=(R3+R4) / / R2;

[0105] Among them, A is called by the software formula and is defined as the simplified calculation coefficient of resistance; B is called by the software formula and is defined as the simplified calculation coefficient of resistance; C is called by the software formula and is defined as the simplified calculation coefficient of resistance;

[0106] R1 is the voltage divider resistor 1 of the positive arm of the unbalanced bridge method; R2 is the voltage divider resistor 2 of the positive arm of the unbalanced bridge method; R3 is the voltage divider resistor 1 of the negative arm of the unbalanced bridge method; R4 is the voltage divider resistor 2 of the negative arm of the unbalanced bridge method;

[0107] Un1(a) shows the first time the software delays 10ms to collect data after Q2 is closed. The data is filtered and output to the battery management system (BMS) for calculation of the battery pack-GND voltage. Un1(b) shows the second time the software delays 10ms to collect data after Q2 is closed. The data is filtered and output to the battery management system (BMS) for calculation of the battery pack-GND voltage.

[0108] Un2(a) is the first time the software delays 10ms to collect data after Q1 is closed. After filtering and processing the data, the battery management system BMS collects and calculates the voltage between the battery pack Pack and GND. Un2(b) is the second time the software delays 10ms to collect data after Q1 is closed. After filtering and processing the data, the battery management system BMS collects and calculates the voltage between the battery pack Pack and GND.

[0109] Determine the filter sensitivity coefficients of the insulation resistance value of the battery management system BMS KRiso1 = |Un1(a) / Un1(b)|, KRiso2 = |Un2(a) / Un2(b)|;

[0110] Send the vehicle insulation resistance value Riso to the power domain controller PDCS;

[0111] Among them, the calculation method of Riso is: the voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND superimposed, that is, Ubattery=Up1+Un1=Up2+Un2, so we get formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2;

[0112] The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, and Un2 collected by the BMS hardware are known parameters to the battery management system BMS software. The values ​​of A, B, C, Ubattery, Un1, and Un2 are known parameters to the battery management system BMS software.

[0113] Rp and Rn are unknowns, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, and Un2 are substituted into the equations to derive the correlation calculation formulas for the unknown parameters Rp and Rn and the known parameters A, B, C, Ubattery, Un1, and Un2. Then, based on the correlation calculation formulas and combined with the collected known values ​​Ubattery, Un1, and Un2, the values ​​of Rp and Rn are solved.

[0114] S120, starting the insulation detection task of the power domain controller PDCS on the battery management system BMS based on the system parameters;

[0115] Among them, the insulation detection tasks of the power domain controller PDCS on the battery management system BMS based on system parameters include:

[0116] After the driver turns the key to start the vehicle, the power domain controller PDCS is awakened based on the key ignition signal, and the battery management system BMS is awakened based on the hard-wired wake-up signal PDCS-Wakeup-BMS sent by the power domain controller PDCS;

[0117] The power domain controller PDCS implements the high-voltage process of the electric vehicle. The main positive high-voltage contactor and the main negative high-voltage contactor are closed. At the same time, the power domain controller PDCS sends an insulation detection enable instruction to the battery management system BMS through CAN communication. After receiving the insulation detection enable instruction, the battery management system BMS starts the insulation detection task.

[0118] S130, collecting system parameters based on the hardware part of the battery management system BMS;

[0119] Among them, the hardware part of the battery management system BMS collects system parameters including:

[0120] The hardware circuit of the battery management system (BMS) calculates the original value of the insulation resistance through software. The collection and implementation mechanism of the required associated data is as follows:

[0121] The MCU outputs a 3.3V high-level signal Do_Q3_Enable to enable transistor Q3 to close. The voltage of Ubattery is obtained by collecting the 0-2.5V analog signal AI_Pack+_Pack-_AD and calculating.

[0122] The MCU outputs a 3.3V high-level signal Do_Q2_Enable to enable transistor Q2 to close. The voltage of Un1 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating.

[0123] The microcontroller MCU outputs a 3.3V high-level signal Do_Q1_Enable to enable transistor Q1 to close, and the voltage of Un2 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating.

[0124] S140, determining a calculation logic for the original insulation resistance value based on the software portion of the battery management system BMS and calculating the original insulation resistance value based on the calculation logic;

[0125] The method of determining the calculation logic of the original value of the insulation resistance based on the software portion of the battery management system BMS and calculating the original value of the insulation resistance based on the calculation logic includes:

[0126] The voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND superimposed, that is, Ubattery=Up1+Un1=Up2+Un2, so we get formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2;

[0127] The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, and Un2 collected by the BMS hardware are known parameters to the battery management system BMS software. The values ​​of A, B, C, Ubattery, Un1, and Un2 are known parameters to the battery management system BMS software.

[0128] Rp and Rn are unknowns, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, and Un2 are substituted into the equations to derive the correlation calculation formulas for the unknown parameters Rp and Rn and the known parameters A, B, C, Ubattery, Un1, and Un2. Then, based on the correlation calculation formulas and combined with the collected known values ​​Ubattery, Un1, and Un2, the values ​​of Rp and Rn are solved.

[0129] S150, performing data processing on the original value of insulation resistance;

[0130] The data processing of the original insulation resistance value includes:

[0131] Step 1: After the MCU enables Q2 and closes, the battery management system (BMS) performs insulation detection sampling with a delay of 100ms and samples the Un1 voltage five times with a sampling period of 10ms. The software then filters and processes the data, outputting the Un1(a) voltage. The voltage Un1 is then sampled five times with a sampling period of 10ms, and the software then filters and processes the data, outputting the Un1(b) voltage. At this point, if the BMS software determines that KRiso1 = |Un1(a) / Un1(b)| ≥ 0.99, then the value is assigned so that Un1(b) = Un1.

[0132] Step 2: After the MCU enables Q1 and closes, it samples the voltage Un2 five times with a delay of 100ms, with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un2 (a). After a delay of 500ms, it samples the voltage Un2 five times with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un2 (b).

[0133] At this time, if the software of the battery management system BMS determines that KRiso2=|Un2(a) / Un2(b)|≥0.99, then the value is assigned so that Un2=Un2(b);

[0134] Step 3: If the original insulation resistance value cannot be calculated within the maximum calculation time of 20 seconds, the battery management system (BMS) insulation circuit acquisition fault is determined and reported;

[0135] Step 4: After the MCU enables Q1 and turns it off, it samples the voltage Un1 five times with a delay of 100ms, with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un1(a). After a delay of 500ms, it samples the voltage Un1 five times with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un1(b).

[0136] At this time, if the software of the battery management system BMS determines that KRiso1 = |Un1(a) / Un1(b)|≥0.99, then the value is assigned so that Un1(b) = Un1.

[0137] S160, determining an insulation test result of the electric vehicle based on the original insulation resistance value after data processing;

[0138] Among them, the insulation test results of electric vehicles are determined based on the original insulation resistance value after data processing, including:

[0139] After the battery management system BMS uploads the insulation resistance raw value data Rp of the battery pack Pack+_GND and the insulation resistance raw value data Rn of the battery pack Pack-GND to the system parameter startup power domain controller PDCS through CAN communication, the software of the system parameter startup power domain controller PDCS processes the insulation resistance raw value data Rp of the battery pack Pack+_GND and the insulation resistance raw value data Rn of the battery pack Pack-_GND;

[0140] If Rp is less than Rn, the system parameters start the power domain controller PDCS software assignment so that Riso = Rp;

[0141] If Rp is greater than Rn, the system parameters start the power domain controller PDCS software assignment so that Riso = Rn;

[0142] If Rp is equal to Rn, the system parameters start the power domain controller PDCS software assignment so that Riso = Rp = Rn;

[0143] After data comparison and value assignment, the system parameters start the power domain controller (PDCS) to send the Riso value to the Tbox in real time via Ethernet. The TBox is used for vehicle big data communication and data transfer. The mobile app and backend system, as the user end, complete the real-time viewing of the vehicle insulation information through the Tbox's vehicle big data communication data transfer.

[0144] System parameters initiate the power domain controller (PDCS) to perform an insulation resistance detection and alarm processing algorithm based on the Riso value, thereby promptly alerting the driver and after-sales maintenance personnel when the vehicle's insulation condition is poor. The insulation resistance detection and alarm processing algorithm includes:

[0145] When Riso≤50K, a level 3 insulation resistance detection alarm is performed;

[0146] When Riso≤120K, a level 2 insulation resistance detection alarm is performed;

[0147] When Riso≤250K, a level 1 insulation resistance detection alarm is performed.

[0148] The insulation detection method for an electric vehicle provided by an embodiment of the present invention realizes data detection of the insulation resistance of an electric vehicle through the leadership of the battery management system BMS and the assistance of the power domain controller PDCS, and has the following advantages:

[0149] (1) The design scheme adopts the unbalanced bridge method, which uses a single bridge arm. It saves the cost of hardware components and reduces the difficulty of hardware design and software design, thereby improving the reliability of the insulation detection design scheme of the battery management system BMS.

[0150] (2) The software data processing algorithm of the battery management system BMS delays data collection when the multiple hardware switches Q2 and Q1 are opened and closed respectively, so as to avoid the interference of electromagnetic noise generated by the moment of opening and closing of the hardware switches on the software data collection.

[0151] (3) The battery management system BMS collects insulation detection-related data multiple times, and at the same time introduces the filter sensitivity coefficients KRiso1 and KRiso2 of the insulation resistance value of the battery management system BMS. In this way, when the effective insulation resistance collection value is obtained, it can also be determined whether the battery management system BMS has an insulation resistance hardware collection failure.

[0152] (4) The battery management system (BMS) is responsible for collecting, calculating, and uploading the parsed raw insulation resistance data to the power domain controller (PDCS). The power domain controller (PDCS) further implements a multi-level insulation resistance alarm and early warning mechanism, thereby improving the system reliability of insulation resistance monitoring.

[0153] (5) The power domain controller PDCS sends the Riso value to the Tbox in real time via Ethernet. The mobile app and the backend system, as the user end, can complete the real-time viewing of the vehicle insulation information through the data transfer of Tbox, so that users and after-sales maintenance personnel can remotely understand the insulation resistance operating status in the vehicle and realize the synchronization of the vehicle data and the backend system.

[0154] Corresponding to the insulation detection methods for electric vehicles provided in the above-mentioned embodiments, an embodiment of the present invention further provides an insulation detection system for electric vehicles. Since the insulation detection system for electric vehicles provided in this embodiment of the present invention corresponds to the insulation detection methods for electric vehicles provided in the above-mentioned embodiments, the implementation methods of the insulation detection method for electric vehicles are also applicable to the insulation detection system for electric vehicles provided in this embodiment and will not be described in detail in this embodiment.

[0155] FIG3 is a schematic structural diagram of an insulation detection system for an electric vehicle according to an embodiment of the present invention;

[0156] 3 , the insulation detection system 300 for an electric vehicle includes: a definition module 310 , a first detection module 320 , a parameter acquisition module 330 , a calculation module 340 , a data processing module 350 , and a second detection module 360 ​​, wherein:

[0157] A definition module 310 is used to define system parameters of an insulation monitoring module of a battery management system BMS;

[0158] The first detection module 320 is used to start the insulation detection task of the power domain controller PDCS on the battery management system BMS based on the system parameters;

[0159] The parameter acquisition module 330 is used to acquire system parameters based on the hardware part of the battery management system BMS;

[0160] A calculation module 340 is configured to determine a calculation logic for the original insulation resistance value based on a software portion of the battery management system BMS and calculate the original insulation resistance value based on the calculation logic;

[0161] The data processing module 350 is used to process the original insulation resistance value;

[0162] The second detection module 360 ​​is used to determine the insulation detection result of the electric vehicle based on the original insulation resistance value after data processing.

[0163] The insulation detection system for electric vehicles provided by the embodiment of the present invention realizes data detection of the insulation resistance of electric vehicles through the leadership of the battery management system BMS and the assistance of the power domain controller PDCS, and has the following advantages:

[0164] (1) The design scheme adopts the unbalanced bridge method, which uses a single bridge arm. It saves the cost of hardware components and reduces the difficulty of hardware design and software design, thereby improving the reliability of the insulation detection design scheme of the battery management system BMS.

[0165] (2) The software data processing algorithm of the battery management system BMS delays data collection when the multiple hardware switches Q2 and Q1 are opened and closed respectively, so as to avoid the interference of electromagnetic noise generated by the moment of opening and closing of the hardware switches on the software data collection.

[0166] (3) The battery management system BMS collects insulation detection-related data multiple times, and at the same time introduces the filter sensitivity coefficients KRiso1 and KRiso2 of the insulation resistance value of the battery management system BMS. In this way, when the effective insulation resistance collection value is obtained, it can also be determined whether the battery management system BMS has an insulation resistance hardware collection failure.

[0167] (4) The battery management system (BMS) is responsible for collecting, calculating, and uploading the parsed raw insulation resistance data to the power domain controller (PDCS). The power domain controller (PDCS) further implements a multi-level insulation resistance alarm and early warning mechanism, thereby improving the system reliability of insulation resistance monitoring.

[0168] (5) The power domain controller PDCS sends the Riso value to the Tbox in real time via Ethernet. The mobile app and the backend system, as the user end, can complete the real-time viewing of the vehicle insulation information through the data transfer of Tbox, so that users and after-sales maintenance personnel can remotely understand the insulation resistance operating status in the vehicle and realize the synchronization of the vehicle data and the backend system.

[0169] In one embodiment of the present invention, the definition module 310 is specifically used for the battery management system BMS to collect and calculate the voltage of the battery pack Pack+_GND as Up;

[0170] The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack+_GND as Rp;

[0171] The battery management system BMS collects and calculates the voltage of the battery pack Pack-_GND as Un;

[0172] The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack-_GND as Rn;

[0173] The battery management system BMS collects and calculates the voltage of the battery pack Pack+_Pack- as Ubattery;

[0174] A=R1+R2, B=R3+R4, C=(R3+R4) / / R2;

[0175] Among them, A is called by the software formula and is defined as the simplified calculation coefficient of resistance; B is called by the software formula and is defined as the simplified calculation coefficient of resistance; C is called by the software formula and is defined as the simplified calculation coefficient of resistance;

[0176] R1 is the voltage divider resistor 1 of the positive arm of the unbalanced bridge method; R2 is the voltage divider resistor 2 of the positive arm of the unbalanced bridge method; R3 is the voltage divider resistor 1 of the negative arm of the unbalanced bridge method; R4 is the voltage divider resistor 2 of the negative arm of the unbalanced bridge method;

[0177] Un1(a) shows the first time the software delays 10ms to collect data after Q2 is closed. The data is filtered and output to the battery management system (BMS) for calculation of the battery pack-GND voltage. Un1(b) shows the second time the software delays 10ms to collect data after Q2 is closed. The data is filtered and output to the battery management system (BMS) for calculation of the battery pack-GND voltage.

[0178] Un2(a) is the first time the software delays 10ms to collect data after Q1 is closed. After filtering and processing the data, the battery management system BMS collects and calculates the voltage between the battery pack Pack and GND. Un2(b) is the second time the software delays 10ms to collect data after Q1 is closed. After filtering and processing the data, the battery management system BMS collects and calculates the voltage between the battery pack Pack and GND.

[0179] Determine the filter sensitivity coefficients of the insulation resistance value of the battery management system BMS KRiso1 = |Un1(a) / Un1(b)|, KRiso2 = |Un2(a) / Un2(b)|;

[0180] Send the vehicle insulation resistance value Riso to the power domain controller PDCS;

[0181] Among them, the calculation method of Riso is: the voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND superimposed, that is, Ubattery=Up1+Un1=Up2+Un2, so we get formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2;

[0182] The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, and Un2 collected by the BMS hardware are known parameters to the battery management system BMS software. The values ​​of A, B, C, Ubattery, Un1, and Un2 are known parameters to the battery management system BMS software.

[0183] Rp and Rn are unknowns, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, and Un2 are substituted into the equations to derive the correlation calculation formulas for the unknown parameters Rp and Rn and the known parameters A, B, C, Ubattery, Un1, and Un2. Then, based on the correlation calculation formulas and combined with the collected known values ​​Ubattery, Un1, and Un2, the values ​​of Rp and Rn are solved.

[0184] In one embodiment of the present invention, the first detection module 320 is specifically configured to wake up the power domain controller PDCS based on the key ignition signal after the driver turns the key to start the vehicle, and wake up the battery management system BMS based on the hard-wired wake-up signal PDCS-Wakeup-BMS sent by the power domain controller PDCS;

[0185] The power domain controller PDCS implements the high-voltage process of the electric vehicle. The main positive high-voltage contactor and the main negative high-voltage contactor are closed. At the same time, the power domain controller PDCS sends an insulation detection enable instruction to the battery management system BMS through CAN communication. After receiving the insulation detection enable instruction, the battery management system BMS starts the insulation detection task.

[0186] In one embodiment of the present invention, the parameter acquisition module 330 is specifically used for the hardware circuit of the battery management system BMS to calculate the original value of the insulation resistance through software. The acquisition implementation mechanism of the required associated data is as follows:

[0187] The MCU outputs a 3.3V high-level signal Do_Q3_Enable to enable transistor Q3 to close. The voltage of Ubattery is obtained by collecting the 0-2.5V analog signal AI_Pack+_Pack-_AD and calculating.

[0188] The MCU outputs a 3.3V high-level signal Do_Q2_Enable to enable transistor Q2 to close. The voltage of Un1 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating.

[0189] The microcontroller MCU outputs a 3.3V high-level signal Do_Q1_Enable to enable transistor Q1 to close, and the voltage of Un2 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating.

[0190] In one embodiment of the present invention, the calculation module 340 is specifically used to calculate that the voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND, that is, Ubattery=Up1+Un1=Up2+Un2, thereby obtaining formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2;

[0191] The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, and Un2 collected by the BMS hardware are known parameters to the battery management system BMS software. The values ​​of A, B, C, Ubattery, Un1, and Un2 are known parameters to the battery management system BMS software.

[0192] Rp and Rn are unknowns, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, and Un2 are substituted into the equations to derive the correlation calculation formulas for the unknown parameters Rp and Rn and the known parameters A, B, C, Ubattery, Un1, and Un2. Then, based on the correlation calculation formulas and combined with the collected known values ​​Ubattery, Un1, and Un2, the values ​​of Rp and Rn are solved.

[0193] In one embodiment of the present invention, the data processing module 350 is specifically used for step 1. After the MCU enables Q2 to be closed, the battery management system BMS insulation detection sampling delay is 100ms, and the Un1 voltage is sampled for a total of 5 times with a sampling period of 10ms. After the software filters the data, the voltage of Un1(a) is output; the voltage Un1 is sampled for a total of 5 times with a sampling period of 10ms, and the software filters the data and outputs the voltage Un1(b). At this time, if the software of the battery management system BMS determines that KRiso1=|Un1(a) / Un1(b)|≥0.99, then the value is assigned so that Un1(b)=Un1;

[0194] Step 2: After the MCU enables Q1 and closes, it samples the voltage Un2 five times with a delay of 100ms, with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un2 (a). After a delay of 500ms, it samples the voltage Un2 five times with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un2 (b).

[0195] At this time, if the software of the battery management system BMS determines that KRiso2=|Un2(a) / Un2(b)|≥0.99, then the value is assigned so that Un2=Un2(b);

[0196] Step 3: If the original insulation resistance value cannot be calculated within the maximum calculation time of 20 seconds, the battery management system (BMS) insulation circuit acquisition fault is determined and reported;

[0197] Step 4: After the MCU enables Q1 and turns it off, it samples the voltage Un1 five times with a delay of 100ms, with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un1(a). After a delay of 500ms, it samples the voltage Un1 five times with a sampling period of 10ms. After the software filters the data, it outputs the voltage Un1(b).

[0198] At this time, if the software of the battery management system BMS determines that KRiso1 = |Un1(a) / Un1(b)|≥0.99, then the value is assigned so that Un1(b) = Un1.

[0199] In one embodiment of the present invention, the second detection module 360 ​​is specifically configured to: after the battery management system BMS uploads the insulation resistance raw value data Rp of the battery pack Pack+_GND and the insulation resistance raw value data Rn of the battery pack Pack-GND to the system parameter startup power domain controller PDCS via CAN communication, the software of the system parameter startup power domain controller PDCS performs data processing on the insulation resistance raw value data Rp of the battery pack Pack+_GND and the insulation resistance raw value data Rn of the battery pack Pack-_GND;

[0200] If Rp is less than Rn, the system parameters start the power domain controller PDCS software assignment so that Riso = Rp;

[0201] If Rp is greater than Rn, the system parameters start the power domain controller PDCS software assignment so that Riso = Rn;

[0202] If Rp is equal to Rn, the system parameters start the power domain controller PDCS software assignment so that Riso = Rp = Rn;

[0203] After data comparison and value assignment, the system parameters start the power domain controller (PDCS) to send the Riso value to the Tbox in real time via Ethernet. The TBox is used for vehicle big data communication and data transfer. The mobile app and backend system, as the user end, complete the real-time viewing of the vehicle insulation information through the Tbox's vehicle big data communication data transfer.

[0204] System parameters initiate the power domain controller (PDCS) to perform an insulation resistance detection and alarm processing algorithm based on the Riso value, thereby promptly alerting the driver and after-sales maintenance personnel when the vehicle's insulation condition is poor. The insulation resistance detection and alarm processing algorithm includes:

[0205] When Riso≤50K, a level 3 insulation resistance detection alarm is performed;

[0206] When Riso≤120K, a level 2 insulation resistance detection alarm is performed;

[0207] When Riso≤250K, a level 1 insulation resistance detection alarm is performed.

[0208] In one embodiment of the present invention, an electric vehicle is further provided. The electric vehicle includes the insulation detection system for the electric vehicle discussed in any one of the above embodiments.

[0209] In another embodiment of the present invention, an electronic device is provided, including:

[0210] a memory for storing computer-executable instructions; and

[0211] A processor configured to execute computer-executable instructions to perform the electric vehicle insulation testing method described in any of the above embodiments. The electronic device may include one or more processors and a memory. The memory stores computer-executable instructions that, when executed by the processor, cause the electronic device to perform any of the above embodiments of the electric vehicle insulation testing method. The electronic device may also include a communication interface.

[0212] The processor can be any suitable processing device, such as a microprocessor, microcontroller, integrated circuit, or other suitable processing device. The memory can include any suitable computing system or medium, including but not limited to non-transitory computer-readable media, random access memory (RAM), read-only memory (ROM), hard disk, flash memory, or other memory devices. The memory can store computer-executable instructions that can be executed by the processor to cause the electronic device to perform any embodiment of the above-mentioned electric vehicle insulation detection method. The memory can also store data.

[0213] In an embodiment of the present invention, a processor may execute various modules included in the instructions to implement an embodiment of the electric vehicle insulation detection method in the above-mentioned electric vehicle insulation detection system. For example, an electronic device may implement various modules in the above-mentioned electric vehicle insulation detection system to execute methods S110, S120, S130, S140, S150, and S160 shown in FIG1 and the method shown in FIG2.

[0214] In yet another embodiment of the present invention, a non-transitory computer-readable storage medium is provided. The computer-readable storage medium stores computer-executable instructions, which, when executed by a computer, cause the computer to execute any embodiment of the electric vehicle insulation detection method in the above-mentioned electric vehicle insulation detection system.

[0215] In yet another embodiment of the present invention, a computer program product comprising instructions is provided. When the computer program product is run on a computer, the computer is enabled to execute any one of the insulation detection methods for electric vehicles in the above embodiments.

[0216] Referring now to FIG4 , a schematic diagram illustrating the structure of an electronic device 400 suitable for implementing an embodiment of the present invention is provided for use with an apparatus according to an embodiment of the present invention. The terminal devices in the embodiment of the present invention may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers.

[0217] The electronic device shown in FIG4 is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0218] As shown in Figure 4, electronic device 400 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. Various programs and data required for the operation of electronic device 400 are also stored in RAM 403. Processing device 401, ROM 402, and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0219] Typically, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 400 to communicate with other devices wirelessly or by wire to exchange data.

[0220] Although FIG4 shows an electronic device 400 having various devices, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0221] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present invention are performed.

[0222] It should be noted that the computer-readable medium described above in the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present invention, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0223] In some embodiments, the client and server can communicate using any currently known or later developed network protocol, such as HTTP (HyperText Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or later developed network.

[0224] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0225] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: defines the system parameters of the insulation monitoring module of the battery management system BMS, starts the insulation detection task of the power domain controller PDCS on the battery management system BMS based on the system parameters, collects the system parameters based on the hardware part of the battery management system BMS, determines the calculation logic of the original value of the insulation resistance based on the software part of the battery management system BMS and calculates the original value of the insulation resistance based on the calculation logic, performs data processing on the original value of the insulation resistance, and determines the insulation detection result of the electric vehicle based on the original value of the insulation resistance after data processing.

[0226] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including, but not limited to, object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0227] The flow charts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0228] The units involved in the embodiments of the present invention may be implemented in software or hardware. In some cases, the name of a unit does not limit the unit itself. For example, the first acquisition unit may also be described as a "unit for acquiring at least two Internet Protocol addresses."

[0229] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0230] In the context of the present invention, machine-readable medium can be a tangible medium that can contain or store a program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0231] The above description is merely a preferred embodiment of the present invention and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure involved in the present invention is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also includes other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in the present invention.

[0232] In addition, although adopting specific order to describe each operation, this should not be interpreted as requiring these operations to be executed in the specific order shown or in sequential order.Under certain environment, multitasking and parallel processing may be advantageous.Similarly, although comprising some specific implementation details in the above discussion, these should not be interpreted as limiting the scope of the present invention.Some features described in the context of independent embodiment can also be implemented in single embodiment in combination.On the contrary, the various features described in the context of independent embodiment also can be implemented in multiple embodiments individually or in the mode of any suitable subcombination.

[0233] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms of implementing the claims.

[0234] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be encompassed by the scope of the pending claims.

Claims

1. An insulation detection method for an electric vehicle, characterized in that: include: Define the system parameters of the insulation monitoring module of the battery management system BMS; Based on the system parameters, the power domain controller PDCS starts an insulation detection task for the battery management system BMS; Collecting the system parameters based on the hardware part of the battery management system BMS; Determining a calculation logic of the original value of insulation resistance based on the software part of the battery management system BMS and calculating the original value of insulation resistance based on the calculation logic; Performing data processing on the original value of the insulation resistance; The insulation detection result of the electric vehicle is determined based on the original value of the insulation resistance after data processing.

2. The insulation detection method of an electric vehicle according to claim 1, wherein: The system parameters defining the insulation monitoring module of the battery management system BMS include: The battery management system BMS collects and calculates the voltage of the battery pack Pack+_GND as Up; The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack+_GND as Rp; The battery management system BMS collects and calculates the voltage of the battery pack Pack-_GND as Un; The battery management system BMS collects and calculates the original value data of the insulation resistance of the battery pack Pack-_GND as Rn; The battery management system BMS collects and calculates the voltage of the battery pack Pack+_Pack- as Ubattery; A=R1+R2, B=R3+R4, C=(R3+R4) / / R2; Among them, A is called by the software formula, which is defined as the simplified calculation coefficient of resistance; B is called by the software formula, which is defined as the simplified calculation coefficient of resistance; C is called by the software formula, which is defined as the simplified calculation coefficient of resistance; R1 is the voltage-dividing resistor 1 of the positive arm of the unbalanced bridge method; R2 is the voltage-dividing resistor 2 of the positive arm of the unbalanced bridge method; R3 is the voltage-dividing resistor 1 of the negative arm of the unbalanced bridge method; R4 is the voltage-dividing resistor 2 of the negative arm of the unbalanced bridge method; Un1(a) is the first time after Q2 is closed, the software delays 10ms to collect, and the battery management system BMS collects and calculates the voltage of the battery pack Pack-GND after filtering and processing the data; Un1(b) is the second time after Q2 is closed, the software delays 10ms to collect, and the battery management system BMS collects and calculates the voltage of the battery pack Pack-GND after filtering and processing the data; Un2(a) is the first time after Q1 is closed, the software delays 10ms to collect, and the battery management system BMS collects and calculates the voltage of the battery pack Pack-GND after filtering and processing the data; Un2(b) is the second time after Q1 is closed, the software delays 10ms to collect, and the battery management system BMS collects and calculates the voltage of the battery pack Pack-_GND after filtering and processing the data; Determine the filter sensitivity coefficients KRiso1=|Un1(a) / Un1(b)| and KRiso2=|Un2(a) / Un2(b)| of the insulation resistance value of the battery management system BMS; Send the vehicle insulation resistance value Riso to the power domain controller PDCS; The calculation method of Riso is as follows: the voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND, that is, Ubattery=Up1+Un1=Up2+Un2, so formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2 are obtained; The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, Un2 collected by the BMS hardware are set to be known parameters for the battery management system BMS software, and the values ​​of A, B, C, Ubattery, Un1, Un2 are known parameters for the battery management system BMS software; Rp and Rn are unknown numbers, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, Un2 are substituted to solve the equation to derive the correlation calculation formula for the unknown parameters Rp, Rn and the known parameters A, B, C, Ubattery, Un1, Un2, and then based on the correlation calculation formula and combined with the collected known values ​​Ubattery, Un1 and Un2, the values ​​of Rp and Rn are solved.

3. The insulation detection method of an electric vehicle according to claim 1, wherein: The task of starting the insulation detection of the battery management system BMS by the power domain controller PDCS based on the system parameters includes: Starting the vehicle, waking up the power domain controller PDCS based on a key ignition signal, and waking up the battery management system BMS based on a hard-line wake-up signal PDCS-Wakeup-BMS sent by the power domain controller PDCS; The power domain controller PDCS implements and completes the whole vehicle high-voltage process of the electric vehicle, the main positive high-voltage contactor and the main negative high-voltage contactor are closed, and at the same time, the power domain controller PDCS sends an insulation detection enable instruction to the battery management system BMS through CAN communication, and the battery management system BMS starts the insulation detection task after receiving the insulation detection enable instruction.

4. The insulation detection method of an electric vehicle according to claim 3, wherein: The collecting of the system parameters based on the hardware part of the battery management system BMS includes: The hardware circuit of the battery management system BMS calculates the original value of the insulation resistance through software, and the collection and implementation mechanism of the required associated data is as follows: The MCU outputs a 3.3V high-level signal Do_Q3_Enable to enable transistor Q3 to close, and the voltage of Ubattery is obtained by collecting the 0-2.5V analog signal AI_Pack+_Pack-_AD and calculating; The MCU outputs a 3.3V high-level signal Do_Q2_Enable to enable transistor Q2 to close, and the voltage of Un1 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating; The microcontroller MCU outputs a 3.3V high-level signal Do_Q1_Enable to enable transistor Q1 to close, and then the voltage of Un2 is obtained by collecting the 0-2.5V analog signal AI_Pack-_GND_AD and calculating.

5. The insulation detection method of an electric vehicle according to claim 4, wherein: The determining of the calculation logic of the original value of the insulation resistance based on the software part of the battery management system BMS and calculating the original value of the insulation resistance based on the calculation logic comprises: The voltage Ubattery of the battery pack Pack+_Pack- is equivalent to the voltage Up of Pack-_GND plus the voltage Un of Pack+_GND, that is, Ubattery=Up1+Un1=Up2+Un2, so formula (1) Up1=Ubattery-Un1, and formula (2) Up2=Ubattery-Un2 are obtained; The values ​​of the resistors R1, R2, R3, R4 and the voltages Ubattery, Un1, Un2 collected by the BMS hardware are set to be known parameters for the battery management system BMS software, and the values ​​of A, B, C, Ubattery, Un1, Un2 are known parameters for the battery management system BMS software; Rp and Rn are unknown numbers, so based on formula (1) and formula (2), the known parameters A, B, C, Ubattery, Un1, Un2 are substituted to solve the equation to derive the correlation calculation formula for the unknown parameters Rp, Rn and the known parameters A, B, C, Ubattery, Un1, Un2, and then based on the correlation calculation formula and combined with the collected known values ​​Ubattery, Un1 and Un2, the values ​​of Rp and Rn are solved.

6. The insulation detection method of an electric vehicle according to claim 5, wherein: The data processing of the original value of the insulation resistance comprises: After the MCU enables Q2 to close, the battery management system BMS insulation detection sampling delay is 100ms, and the Un1 voltage is sampled 5 times with a sampling period of 10ms. After the software filters the data, the voltage of Un1(a) is output; the voltage Un1 is sampled 5 times with a sampling period of 10ms, and the voltage of Un1(b) is output after the software filters the data; at this time, if the software of the battery management system BMS determines that KRiso1=|Un1(a) / Un1(b)|≥0.99, the value is assigned so that Un1(b)=Un1; After the MCU enables Q1 to close, it samples the voltage Un2 for 5 times with a delay of 100ms, with a sampling period of 10mS, and outputs the voltage of Un2(a) after the software filters the data; it samples the voltage Un2 for 5 times with a delay of 500ms, with a sampling period of 10mS, and outputs the voltage of Un2(b) after the software filters the data; at this time, if the software of the battery management system BMS determines that KRiso2=|Un2(a) / Un2(b)|≥0.99, then the value is assigned so that Un2=Un2(b); If the original value of the insulation resistance cannot be calculated within the maximum calculation time of 20 seconds, it is determined that the insulation circuit of the battery management system BMS has a collection fault and reported; After the MCU enables Q1 to be disconnected, the voltage Un1 is sampled 5 times with a delay of 100ms, the sampling period is 10ms, and the voltage of Un1(a) is output after the software filters the data. The voltage Un1 is sampled 5 times with a delay of 500ms, the sampling period is 10ms, and the voltage of Un1(b) is output after the software filters the data. At this time, if the software of the battery management system BMS determines that KRiso1=|Un1(a) / Un1(b)|≥0.99, the value is assigned so that Un1(b)=Un1.

7. The insulation detection method of an electric vehicle according to claim 6, wherein: The step of determining the insulation detection result of the electric vehicle based on the original insulation resistance value after data processing includes: After the battery management system BMS uploads the insulation resistance original value data Rp of the battery pack Pack+_GND and the insulation resistance original value data Rn of the battery pack Pack-GND to the system parameter startup power domain controller PDCS through CAN communication, the software of the system parameter startup power domain controller PDCS processes the insulation resistance original value data Rp of the battery pack Pack+_GND and the insulation resistance original value data Rn of the battery pack Pack-_GND; If Rp is less than Rn, the system parameter starts the power domain controller PDCS software assignment so that Riso = Rp; If Rp is greater than Rn, the system parameter starts the power domain controller PDCS software assignment so that Riso = Rn; If Rp is equal to Rn, the system parameter starts the power domain controller PDCS software assignment so that Riso=Rp=Rn; After the data comparison and assignment, the system parameters start the power domain controller PDCS to send the Riso value to Tbox in real time through Ethernet. TBox is used for whole vehicle big data communication and data transfer. The mobile app and the backend system as the user end complete the real-time viewing of the whole vehicle insulation information through the whole vehicle big data communication data transfer of Tbox. The system parameters start the power domain controller PDCS to perform the insulation resistance detection alarm processing algorithm processing task based on the Riso value, so as to promptly remind the driver and after-sales maintenance personnel when the vehicle insulation working condition is poor; the insulation resistance detection alarm processing algorithm includes: When Riso≤50K, a level 3 insulation resistance detection alarm is performed; When Riso≤120K, a level 2 insulation resistance detection alarm is performed; When Riso≤250K, a level 1 insulation resistance detection alarm is performed.

8. An insulation detection system for an electric vehicle, characterized in that: include: A definition module is used to define system parameters of the insulation monitoring module of the battery management system BMS; A first detection module is used to start the insulation detection task of the power domain controller PDCS on the battery management system BMS based on the system parameters; A parameter acquisition module, used for acquiring the system parameters based on the hardware part of the battery management system BMS; A calculation module, configured to determine a calculation logic of an original value of insulation resistance based on a software part of the battery management system BMS and calculate the original value of insulation resistance based on the calculation logic; A data processing module, used for performing data processing on the original value of the insulation resistance; The second detection module is used to determine the insulation detection result of the electric vehicle based on the original value of the insulation resistance after data processing.

9. An electric vehicle, characterized in that: The electric vehicle comprises the insulation detection system for the electric vehicle as claimed in claim 8.

10. An electronic device, characterized in that: include: a memory for storing computer executable instructions; as well as A processor, which is used to run the computer executable instructions to execute the insulation detection method for an electric vehicle according to any one of claims 1 to 7.

11. A non-transitory computer-readable storage medium, characterized in that: The storage medium stores computer executable instructions, and when the instructions are executed by a computer, the computer executes the insulation detection method for an electric vehicle according to any one of claims 1 to 7.

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