Automatic identification and evaluation equipment and method for bad charging behavior of new energy vehicles

Abstract

The present invention discloses an automatic identification and evaluation device and method for bad charging behavior of new energy vehicles. The device includes a host, a data transmission module, a microprocessor module, an OBD decoding module and an OBD connector; the host is provided with a data receiving module, a charging behavior acquisition module, a charging behavior recognition module, a behavior comprehensive evaluation module and a storage module; the charging behavior acquisition module, the charging behavior recognition module and the behavior comprehensive evaluation module are connected in sequence, and the charging behavior recognition module and the behavior comprehensive evaluation module are both connected to the storage module. The present invention is directed to a bad behavior identification method for charging behavior of new energy vehicles, a quantifiable comprehensive evaluation method and corresponding equipment, which can automatically identify a series of bad charging behaviors and give a comprehensive evaluation of the behaviors, and better solve the problem of the impact of bad charging behaviors on the power batteries of new energy vehicles and the problem of managing the charging behaviors of drivers.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy vehicles, and specifically relates to an automatic identification and evaluation device and method for bad charging behavior of new energy vehicles. Background Art

[0002] At present, the power batteries of new energy vehicles generally use electrochemical batteries, such as ternary lithium batteries or lithium iron phosphate batteries. The service life of this type of electrochemical battery is generally six to ten years, and there are a certain number of charge and discharge times. As one of the most important components of new energy vehicles, the service life and capacity of the power battery determine the service life of the vehicle.

[0003] The charging behavior of the battery is a very important factor affecting the battery life and capacity. Good charging behavior can effectively reduce battery degradation and ensure the battery life; on the contrary, bad charging behavior will greatly reduce the battery life, cause serious battery capacity degradation, and even cause battery virtual power, that is, the actual capacity of the battery is much smaller than the displayed capacity, causing safety hazards.

[0004] At present, there is some experience with bad charging behavior, which can be obtained through manual observation, and the identification of a single bad behavior is not very meaningful. It is necessary to conduct statistical analysis on the number of bad behaviors within a certain period of time to have guiding significance. At present, there is no automatic identification method for bad charging behavior, a quantitative comprehensive evaluation method and corresponding equipment, and it is impossible to objectively evaluate and guide the charging behavior of drivers. Especially in the current situation where public transportation companies use a large number of new energy vehicles, and one car has multiple drivers charging, companies urgently need a set of objective and quantitative charging behavior automatic identification and comprehensive evaluation methods and equipment to standardize and evaluate drivers and protect corporate assets. Summary of the invention

[0005] The main purpose of the present invention is to overcome the shortcomings and deficiencies of the prior art and to provide an automatic identification and evaluation device and method for bad charging behavior of new energy vehicles, which can automatically identify and evaluate bad charging behavior, quantify bad charging behavior, and quantify the charging behavior evaluation of the driver.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] The present invention provides an automatic identification and evaluation device for bad charging behavior of new energy vehicles, comprising a host, a data transmission module, a microprocessor module, an OBD decoding module and an OBD connector, wherein the host is connected to the microprocessor module via the data transmission module, the microprocessor module is connected to the OBD decoding module, and the OBD decoding module is connected to the OBD connector; the host is provided with a data receiving module, a charging behavior acquisition module, a charging behavior recognition module, a behavior comprehensive evaluation module and a storage module; the charging behavior acquisition module, the charging behavior recognition module and the behavior comprehensive evaluation module are connected in sequence, and the charging behavior recognition and behavior comprehensive evaluation modules are both connected to the storage module;

[0008] The OBD connector is used to collect data from the driving computer of the new energy vehicle and is plugged into the OBD port of the vehicle to work;

[0009] The OBD decoding module is used to decode the driving computer data through the OBD protocol and transmit the battery data of the new energy vehicle power battery to the host wirelessly or wiredly;

[0010] The microprocessor module is responsible for scheduling the OBD decoding module and the data transmission module, organizing the decoded data according to the rules, and the data transmission module outputs the data;

[0011] The data transmission module is used to transmit data to the data receiving module in the host in a wireless or wired manner;

[0012] The data receiving module is used to receive OBD decoding data in a wired or wireless manner;

[0013] The charging behavior acquisition module is used to receive data from the OBD decoding module, collect current charging and non-charging data, and transmit them to the charging behavior identification module;

[0014] The charging behavior recognition module is used to recognize the data transmitted by the charging behavior acquisition module, determine whether it is a bad charging behavior, and transmit the judgment result to the behavior comprehensive evaluation module;

[0015] The charging behavior comprehensive evaluation module is used to give a comprehensive evaluation based on the results identified by the charging behavior identification module and the historical charging behavior;

[0016] The storage module is used to store each charging behavior data, identification results and comprehensive evaluation results in the form of a database.

[0017] As a preferred technical solution, the host is a smart device running the Android system.

[0018] As a preferred technical solution, the battery data includes power level, uncharged time, whether charging is in progress, charging current and battery voltage.

[0019] As a preferred technical solution, the data transmission module is a Bluetooth module or a GSM module.

[0020] As a preferred technical solution, the microprocessor module is an STM32 series chip.

[0021] As a preferred technical solution, each charging behavior data, identification result and evaluation result are stored in a storage module of the host in the form of a data table.

[0022] The present invention also provides a method for automatically identifying and evaluating bad charging behavior of new energy vehicles. The method is applied to the automatic identification and evaluation device for bad charging behavior of new energy vehicles. The method comprises the following steps:

[0023] (1) Collect the driving computer data through the OBD decoding module, read and store;

[0024] (2) Define bad charging behavior, which includes:

[0025] (a) Long-term storage after deep discharge: the power is less than 30% and has not been charged for more than 3 months;

[0026] (b) Over discharge: charge only after the discharge is below 20%;

[0027] (c) Long-term non-charging: The battery level is higher than 30% and has not been charged for more than 3 months;

[0028] (d) Insufficient charging: charging when the power is higher than 30% and stop charging when the power is less than 80%;

[0029] (e) Charging with air conditioning on;

[0030] (f) Charging with fire;

[0031] (g) Four or more consecutive fast charges;

[0032] (3) Let C be whether the charging behavior identified this time is a bad charging behavior, C = 0 means that this time is not a bad charging behavior, C = 1-7 means that this time is a bad charging behavior, and corresponding to the above-mentioned bad charging behaviors (a)-(g), the following parameters are obtained through the OBD decoding module and the stored data:

[0033] The power battery before charging is X1;

[0034] After charging, the power is X2;

[0035] The current charging mode X3 is set to three values: 0-not charged, 1-slow charge, 2-fast charge;

[0036] Time since last charging X4;

[0037] The first three charging modes X5 are set to two values: 0-the first three charging modes are not all fast charging, 1-the first three charging modes are all fast charging;

[0038] Ignition status during charging X6, set to two values: 0-off, 1-on;

[0039] Air conditioning status during charging X7, set to two values: 0-off, 1-on;

[0040] (4) Identify the charging behavior and output the identification result C value to the charging behavior comprehensive evaluation module;

[0041] (5) After each charging behavior recognition module outputs the C value, a comprehensive evaluation of the charging behavior is performed.

[0042] As a preferred technical solution, before step (1), the following steps are also included:

[0043] It will be recognized once after each charge and once a day at a scheduled time.

[0044] As a preferred technical solution, the specific steps of charging behavior identification are:

[0045] If the power battery charge before charging X1 ≤ 30%, and the time since the last charge X3 ≥ 3 months, it is a bad charging behavior (a), C = 1; if not, proceed to the next step;

[0046] Determine whether the power battery charge X1 before charging is ≤20%. If yes, it is a bad charging behavior (b), C=2; if no, proceed to the next step;

[0047] Determine whether the power of the power battery before charging is X1 ≥ 30%, and whether the time since the last charge is X3 ≥ 3 months. If yes, it is a bad charging behavior (c), C = 3; if no, proceed to the next step;

[0048] Determine whether the power battery has a power level of X1 ≥ 30% before charging and a power level of X2 ≤ 80% after charging. If yes, it is a bad charging behavior (d), C = 4; if no, proceed to the next step;

[0049] Determine whether the current charging mode X3>0 and the air conditioning state X7>0. If yes, it is a bad charging behavior (e), C=5; if no, execute the next step;

[0050] Determine whether the current charging mode X3>0 and the ignition state X6>0. If yes, it is a bad charging behavior (f), C=6; if no, execute the next step;

[0051] It is determined whether the current charging mode is X3=2 and the previous three charging modes are X5=1. If yes, it is a bad charging behavior (g), C=7; if no, this charging is not a bad charging, C=0.

[0052] As a preferred technical solution, the specific method for comprehensive evaluation of charging behavior is:

[0053] Assume that S represents the comprehensive evaluation index of charging behavior in the past year, n represents the number of bad charging behaviors in the past year, C is not equal to 0, it is accumulated once, t represents the total number of charging identifications in the past year, in the case of charging, it is accumulated once for each charging, or in the case of non-charging, when it is identified as bad charging, that is, when C is not equal to 0, it is accumulated once, then:

[0054]

[0055] t=t+1

[0056] but:

[0057]

[0058] Because behavior (a) is the most damaging to the power battery, if it occurs once, it may cause the battery to be scrapped, so when C=1, directly set S=1;

[0059] According to the S value, the comprehensive evaluation criteria for charging behavior are as follows:

[0060]

[0061] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0062] 1. The present invention provides a set of automatic identification and evaluation equipment and methods for improper charging behavior of new energy vehicles, which changes the current situation in which the industry lacks effective management of charging behavior and mainly relies on manual and self-discipline, and provides new methods and automated means for the management of charging behavior of new energy vehicles.

[0063] 2. The present invention can automatically identify bad charging behaviors in the daily charging behaviors of new energy vehicles, avoiding manual intervention.

[0064] 3. The present invention can monitor all charging behaviors of new energy vehicles and improve management efficiency.

[0065] 4. The comprehensive evaluation method and device for the driver's charging behavior of the present invention is conducive to the driver's self-improvement and greatly facilitates the management and assessment of the driver. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a schematic diagram of the device structure of the present invention.

[0067] Figure 2 It is a bad behavior identification flow chart of the present invention. DETAILED DESCRIPTION

[0068] The present invention is further described in detail below in conjunction with embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0069] Example

[0070] like Figure 1 As shown, this embodiment provides an automatic identification and evaluation device for bad charging behavior of new energy vehicles, including a host, a data transmission module, a microprocessor module, an OBD decoding module and an OBD connector. The host is connected to the microprocessor module through the data transmission module, the microprocessor module is connected to the OBD decoding module, and the OBD decoding module is connected to the OBD connector; the host is provided with a data receiving module, a charging behavior acquisition module, a charging behavior recognition module, a behavior comprehensive evaluation module and a storage module; the charging behavior acquisition module, the charging behavior recognition module and the behavior comprehensive evaluation module are connected in sequence, and the charging behavior recognition and behavior comprehensive evaluation modules are both connected to the storage module.

[0071] (1) Host: A smart device running the Android system, connected to the OBD decoding module via wired or wireless connection. Data receiving module, charging behavior collection module, charging behavior recognition module, behavior comprehensive evaluation module and storage module.

[0072] (2) OBD decoding module: responsible for decoding the vehicle computer data through the OBD protocol, and transmitting the vehicle power battery power, charging voltage, power and other battery data to the host wirelessly or wiredly.

[0073] (3) OBD connector: It is connected to the OBD decoding module by wire, plugged into the OBD port of the car, and collects the data from the car's driving computer.

[0074] (3) The microprocessor module is responsible for scheduling the OBD decoding module and the data transmission module, organizing the decoded data according to rules, and the data transmission module outputs the data; for example, the STM32 series chip of STMicroelectronics.

[0075] (4) The data transmission module is used to transmit data to the data receiving module in the host in a wireless or wired manner; the data transmission module can be, for example, a Bluetooth module, a GSM module, etc.

[0076] (5) The data receiving module is used to receive OBD decoding data in a wired or wireless manner; the data receiving module can be, for example, a Bluetooth module, a GSM module, etc.

[0077] (5) Charging behavior acquisition module: used to receive data from the OBD decoding module, collect current charging and non-charging data, and transmit them to the charging behavior identification module. It can collect battery data such as the current power battery power, non-charging time, whether it is charging, charging current, battery voltage, etc.

[0078] (6) Charging behavior identification module: used to identify the data transmitted by the charging behavior collection module, determine whether it is bad charging behavior, and transmit the judgment result to the behavior comprehensive evaluation module.

[0079] (6) Comprehensive behavior evaluation module: used to give a comprehensive evaluation based on the results of the charging behavior recognition module and historical charging behavior.

[0080] (7) Storage module: stores each charging behavior data, recognition results and comprehensive evaluation results in the form of a database.

[0081] This embodiment also provides a method for identifying and evaluating bad charging behavior of new energy vehicles. The method is applied to a device for identifying and evaluating bad charging behavior of new energy vehicles. The method includes the following steps:

[0082] (1) Collect the driving computer data through the OBD decoding module, read and store;

[0083] (2) Define bad charging behavior, which includes:

[0084] (a) Long-term storage after deep discharge: the power is less than 30% and has not been charged for more than 3 months;

[0085] (b) Over discharge: charge only after the discharge is below 20%;

[0086] (c) Long-term non-charging: The battery level is higher than 30% and has not been charged for more than 3 months;

[0087] (d) Insufficient charging: charging when the power is higher than 30% and stop charging when the power is less than 80%;

[0088] (e) Charging with air conditioning on;

[0089] (f) Charging with fire;

[0090] (g) Four or more consecutive fast charges;

[0091] (3) Let C be whether the charging behavior identified this time is a bad charging behavior, C = 0 means that this time is not a bad charging behavior, C = 1-7 means that this time is a bad charging behavior, and corresponding to the above-mentioned bad charging behaviors (a)-(g), the following parameters are obtained through the OBD decoding module and the stored data:

[0092] The power battery before charging is X1;

[0093] After charging, the power is X2;

[0094] The current charging mode X3 is set to three values: 0-not charged, 1-slow charge, 2-fast charge;

[0095] Time since last charging X4;

[0096] The first three charging modes X5 are set to two values: 0-the first three charging modes are not all fast charging, 1-the first three charging modes are all fast charging;

[0097] Ignition status during charging X6, set to two values: 0-off, 1-on;

[0098] Air conditioning status during charging X7, set to two values: 0-off, 1-on;

[0099] (4) Identify the charging behavior and output the identification result C value to the charging behavior comprehensive evaluation module; Figure 2 As shown, the specific steps of charging behavior recognition are:

[0100] If the power battery charge before charging X1 ≤ 30%, and the time since the last charge X3 ≥ 3 months, it is a bad charging behavior (a), C = 1; if not, proceed to the next step;

[0101] Determine whether the power battery charge X1 before charging is ≤20%. If yes, it is a bad charging behavior (b), C=2; if no, proceed to the next step;

[0102] Determine whether the power of the power battery before charging is X1 ≥ 30%, and whether the time since the last charge is X3 ≥ 3 months. If yes, it is a bad charging behavior (c), C = 3; if no, proceed to the next step;

[0103] Determine whether the power battery has a power level of X1 ≥ 30% before charging and a power level of X2 ≤ 80% after charging. If yes, it is a bad charging behavior (d), C = 4; if no, proceed to the next step;

[0104] Determine whether the current charging mode X3>0 and the air conditioning state X7>0. If yes, it is a bad charging behavior (e), C=5; if no, execute the next step;

[0105] Determine whether the current charging mode X3>0 and the ignition state X6>0. If yes, it is a bad charging behavior (f), C=6; if no, execute the next step;

[0106] It is determined whether the current charging mode is X3=2 and the previous three charging modes are X5=1. If yes, it is a bad charging behavior (g), C=7; if no, this charging is not a bad charging, C=0.

[0107] (5) After each charging behavior recognition module outputs the C value, a comprehensive evaluation of the charging behavior is performed; the specific method for the comprehensive evaluation of the charging behavior is:

[0108] Assume that S represents the comprehensive evaluation index of charging behavior in the past year, n represents the number of bad charging behaviors in the past year, C is not equal to 0, it is accumulated once, t represents the total number of charging identifications in the past year, in the case of charging, it is accumulated once for each charging or in the case of non-charging, when it is identified as bad charging, that is, when C is not equal to 0, it is accumulated once, then:

[0109]

[0110] t=t+1

[0111] but:

[0112]

[0113] Because behavior (a) is the most damaging to the power battery, if it occurs once, it may cause the battery to be scrapped, so when C=1, directly set S=1;

[0114] According to the S value, the comprehensive evaluation criteria for charging behavior are as follows:

[0115]

[0116] Furthermore, before step (1), the method further comprises the following steps:

[0117] The battery is identified once after each charge and once a day at a fixed time; thus, charging behavior data is collected regularly to improve the accuracy of identification.

[0118] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. An automatic identification and evaluation device for bad charging behavior of new energy vehicles, characterized in that: It includes a host, a data transmission module, a microprocessor module, an OBD decoding module and an OBD connector. The host is connected to the microprocessor module through the data transmission module, the microprocessor module is connected to the OBD decoding module, and the OBD decoding module is connected to the OBD connector; the host is provided with a data receiving module, a charging behavior acquisition module, a charging behavior recognition module, a behavior comprehensive evaluation module and a storage module; the charging behavior acquisition module, the charging behavior recognition module and the behavior comprehensive evaluation module are connected in sequence, and the charging behavior recognition and behavior comprehensive evaluation modules are both connected to the storage module; The OBD connector is used to collect data from the driving computer of the new energy vehicle and is plugged into the OBD port of the vehicle to work; The OBD decoding module is used to decode the driving computer data through the OBD protocol and transmit the battery data of the new energy vehicle power battery to the host wirelessly or wiredly; The microprocessor module is responsible for scheduling the OBD decoding module and the data transmission module, organizing the decoded data according to the rules, and the data transmission module outputs the data; The data transmission module is used to transmit data to the data receiving module in the host in a wireless or wired manner; The data receiving module is used to receive OBD decoding data in a wired or wireless manner; The charging behavior acquisition module is used to receive data from the OBD decoding module, collect current charging and non-charging data, and transmit them to the charging behavior identification module; The charging behavior recognition module is used to recognize the data transmitted by the charging behavior acquisition module, determine whether it is a bad charging behavior, and transmit the judgment result to the behavior comprehensive evaluation module; The charging behavior comprehensive evaluation module is used to give a comprehensive evaluation based on the results identified by the charging behavior identification module and the historical charging behavior; The storage module is used to store each charging behavior data, identification results and comprehensive evaluation results in the form of a database; The automatic identification and evaluation method of the automatic identification and evaluation device for the bad charging behavior of new energy vehicles is as follows: (1) Collect the driving computer data through the OBD decoding module, read and store; (2) Define bad charging behavior, which includes: (a) Long-term storage after deep discharge: the battery power is less than 30% and has not been charged for more than 3 months; (b) Over-discharge: charge only after the battery is below 20%; (c) Long-term non-charging: The battery level is higher than 30% and the battery has not been charged for more than 3 months; (d) Insufficient charging: charging when the power level is above 30% and stop charging when the power level is less than 80%; (e) Charging with air conditioning on; (f) Charging with fire; (g) Four or more consecutive fast charges; (3) Let C be whether the charging behavior identified this time is a bad charging behavior. C = 0 means that this time is not a bad charging behavior, and C = 1-7 means that this time is a bad charging behavior. Corresponding to the above-mentioned bad charging behaviors (a)-(g), the following parameters are obtained through the OBD decoding module and stored data: The power battery before charging is X1; After charging, the power is X2; The current charging mode X3 is set to three values: 0-not charged, 1-slow charge, 2-fast charge; Time since last charging X4; The first three charging modes X5 are set to two values: 0-the first three charging modes are not all fast charging, 1-the first three charging modes are all fast charging; Ignition status during charging X6, set to two values: 0-off, 1-on; Air conditioning status during charging X7, set to two values: 0-off, 1-on; (4) Identify the charging behavior and output the identification result C value to the charging behavior comprehensive evaluation module; (5) After each charging behavior recognition module outputs the C value, a comprehensive evaluation of the charging behavior is performed; The specific method for comprehensive evaluation of charging behavior is as follows: Assume that S represents the comprehensive evaluation index of charging behavior in the past year, n represents the number of bad charging behaviors in the past year, C is not equal to 0, it is accumulated once, t represents the total number of charging identifications in the past year, in the case of charging, it is accumulated once for each charging, or in the case of non-charging, when it is identified as bad charging, that is, when C is not equal to 0, it is accumulated once, then: ； t=t+1; but: ； Because behavior (a) is the most damaging to the power battery, if it occurs once, it may cause the battery to be scrapped, so when C=1, directly set S=1; According to the S value, the comprehensive evaluation criteria for charging behavior are as follows: 。 2. The automatic identification and evaluation device for bad charging behavior of new energy vehicles according to claim 1 is characterized in that: The host is a smart device running the Android system.

3. The automatic identification and evaluation device for bad charging behavior of new energy vehicles according to claim 1 is characterized in that: The battery data includes power level, uncharged time, whether charging is in progress, charging current and battery voltage.

4. The automatic identification and evaluation device for bad charging behavior of new energy vehicles according to claim 1 is characterized in that: The data transmission module is a Bluetooth module or a GSM module.

5. The automatic identification and evaluation device for bad charging behavior of new energy vehicles according to claim 1 is characterized in that: The microprocessor module is an STM32 series chip.

6. The automatic identification and evaluation device for bad charging behavior of new energy vehicles according to claim 1 is characterized in that: Each charging behavior data, identification result and evaluation result are stored in the storage module of the host in the form of a data table.

7. The automatic identification and evaluation device for bad charging behavior of new energy vehicles according to claim 1 is characterized in that: Before step (1), the method further includes the following steps: It will be recognized once after each charge and once a day at a scheduled time.

8. The automatic identification and evaluation device for bad charging behavior of new energy vehicles according to claim 1 is characterized in that: The specific steps of charging behavior identification are: If the power battery’s charge before charging X1≤30%, and the time since the last charge X3≥3 months, it is a bad charging behavior (a), C=1; if not, proceed to the next step; Determine whether the power battery charge X1 before charging is ≤20%. If yes, it is a bad charging behavior (b), C=2; if no, proceed to the next step; Determine whether the power of the power battery before charging is X1 ≥ 30%, and whether the time since the last charge is X3 ≥ 3 months. If yes, it is a bad charging behavior (c), C = 3; if not, proceed to the next step; Determine whether the power of the power battery before charging is X1 ≥ 30%, and whether the power after charging is X2 ≤ 80%. If yes, it is a bad charging behavior (d), C=4; if no, proceed to the next step; Determine whether the current charging mode X3>0 and the air conditioning state X7>0. If yes, it is a bad charging behavior (e), C=5; if no, proceed to the next step; Determine whether the current charging mode X3>0 and the ignition state X6>0. If yes, it is a bad charging behavior (f), C=6; if no, proceed to the next step; Determine whether the current charging mode X3=2 and the previous three charging modes X5=1. If yes, it is a bad charging behavior (g), C=7; if not, this charging is not a bad charging, C=0.

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