Vehicle diagnostic device, vehicle diagnostic method, and vehicle diagnostic program

Abstract

A vehicle diagnostic device is provided with: a feature data acquisition unit that acquires a plurality of pieces of feature data included in a predetermined output mode of a vehicle; an actual data acquisition unit that acquires output data based on actual travel of the vehicle in a past predetermined period and actual measurement data indicating actual measurement of parameters required for vehicle diagnosis during travel of the vehicle in the predetermined period; an equivalent pattern generation unit that generates an equivalent output pattern that is considered to be equivalent to a predetermined output pattern by intercepting points or intervals similar to a plurality of pieces of feature data from the output data for a predetermined period; and an actual measurement extraction unit that extracts actual measurements for each point or each section included in the equivalent output pattern from the actual measurement data during the predetermined period.

Description

Technical Field

[0001] The present invention relates to a vehicle diagnostic device, a vehicle diagnostic method, and a vehicle diagnostic program. Background Art

[0002] In recent years, the development of vehicles equipped with an electric motor driven by electric power stored in a secondary battery (for example, a lithium-ion battery; hereinafter also simply referred to as "battery") has made remarkable progress. Against this background, a device for estimating the degree of deterioration of a battery has been proposed. For example, Patent Document 1 discloses a device that estimates the life of a secondary battery based on a battery state composed of a current value and a voltage value of the battery and the total driving distance of the vehicle.

[0003] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2007-195312 Summary of the Invention Problems to be Solved by the Invention

[0004] Currently, a method is being studied in which a vehicle is driven on a measuring instrument such as a chassis dynamometer based on the Worldwide harmonized Light duty Test Cycle (WLTC) to estimate the degree of deterioration of the battery. However, it is difficult to reproduce the driving cycle of the WLTC (actually drive the vehicle on the measuring instrument) for all vehicles to be inspected or tested from the viewpoints of equipment, time, and labor. Therefore, other solutions need to be studied.

[0005] The present invention has been completed to solve the above problems, and an object thereof is to provide a vehicle diagnostic device, a vehicle diagnostic method, and a vehicle diagnostic program that can judge (diagnose) the state of a vehicle according to a diagnostic method when the vehicle actually travels in a specified driving mode even if the vehicle does not actually travel in the specified driving mode. Means for Solving the Problems

[0006] A vehicle diagnostic device according to an aspect of the present invention is a vehicle diagnostic device that diagnoses a vehicle, and includes: a characteristic data acquisition unit that acquires a plurality of characteristic data included in a specified output mode of the vehicle; an actual data acquisition unit that acquires output data based on the actual driving of the vehicle in a past specified period and actual measurement data indicating actual measurements of parameters required for vehicle diagnosis during the driving of the vehicle in the specified period; an equivalent mode generation unit that generates an equivalent output mode regarded as equivalent to the specified output mode by intercepting points or intervals similar to the plurality of characteristic data from the output data in the specified period; and an actual measurement extraction unit that extracts the actual measurements of each point or each interval included in the equivalent output mode from the actual measurement data in the specified period.

[0007] Another aspect of the vehicle diagnosis method of the present invention includes: an equivalent mode generation step of generating an equivalent output mode regarded as equivalent to the specified output mode by intercepting points or intervals similar to a plurality of characteristic data included in the specified output mode from the output data based on the actual driving of the vehicle in a past specified period; and an actual measurement extraction step of extracting the actual measurements of each point or each interval included in the equivalent output mode from the actual measurement data representing the actual measurements of the parameters required for vehicle diagnosis during the driving of the vehicle in the specified period.

[0008] A vehicle diagnosis program according to yet another aspect of the present invention is a program for causing a computer to execute the above vehicle diagnosis method.

[0009] According to the present invention, even if the vehicle is not actually driven in the specified driving mode, it is possible to judge (diagnose) the vehicle state according to the diagnosis method when driving in the above specified driving mode. Description of the Drawings

[0010] Figure 1 is a block diagram showing the schematic structure of a vehicle diagnosis device according to an embodiment of the present invention. Figure 2 is a graph showing the WLTC driving mode as an example of the specified driving mode of the vehicle. Figure 3 is an enlarged graph showing the WLTC driving mode. Figure 4 is a block diagram showing the schematic structure of the above vehicle. Figure 5 is an explanatory diagram schematically showing the general process of vehicle diagnosis of the above vehicle diagnosis device. Figure 6 is a flowchart showing the specific process of the vehicle diagnosis method in the above vehicle diagnosis device. Figure 7 is a graph showing an example of the actual driving data acquired by the actual data acquisition unit of the above vehicle diagnosis device and the generated equivalent driving mode. Figure 8 is an explanatory diagram showing the distribution of speed and acceleration included in the above WLTC driving mode. Figure 9 is an explanatory diagram showing the relationship between the characteristic points in the unit grid and the measured values. Figure 10 is a graph showing the relationship between the power consumption of the battery and the SOC before and after the deterioration of the battery. Figure 11 is a graph showing another example of the above specified driving mode. Figure 12 It is an explanatory diagram showing a calculation method of an index indicating the consistency between evaluation graphic data and data intercepted from actual driving data. Figure 13 It is an explanatory diagram showing the relationship between the corrected total energy consumption and the corrected SOC in the equivalent driving mode. Figure 14 It is a block diagram showing other structures of the control unit of the vehicle diagnostic device. Figure 15 It is an explanatory diagram schematically including a circuit including the battery and vehicle loads. Figure 16 It is a graph showing the change of the total resistance before battery degradation with the passage of time in the equivalent driving mode. Figure 17 It is to increase Figure 16 A graph shown by increasing the magnification of the vertical axis. Figure 18 It is in Figure 15 An explanatory diagram showing the voltage before the voltage drop in the internal resistance of the battery in the circuit shown. Figure 19 It is a graph schematically showing the change of the output voltage before battery degradation with the passage of time. Figure 20 It is a graph showing the discharge temperature characteristics of the battery. Figure 21 It is an explanatory diagram showing the change patterns of the equivalent driving mode and the height information of the vehicle together. Figure 22 It is to magnify and show Figure 21 An explanatory diagram of a part of any period in the change pattern of the equivalent driving mode and height information. Figure 23A It is a graph showing the time series data of the instantaneous fuel consumption in one cycle of the equivalent driving mode. Figure 23B It is a graph showing the change of the cumulative value of each interval of the fuel injection amount. Figure 24A It is a graph showing the time series data of the instantaneous CO2 emission amount in one cycle of the equivalent driving mode. Figure 24B It is a graph showing the change of the cumulative value of each interval of the CO2 emission amount. Figure 25 It is a graph showing the driving mode serving as the reference for the vehicle. Figure 26 It is an explanatory diagram showing the distribution of each feature point included in the driving mode as a specified output mode. Figure 27 It is a scatter diagram showing the distribution of all feature points extracted from actual driving data at a specified time interval. Figure 28 It is an explanatory diagram showing an example of an equivalent output mode. Figure 29A It is a line graph showing the cumulative value of the instantaneous fuel consumption attached to each feature point included in the above-mentioned specified output mode. Figure 29B It is a line graph showing the cumulative value of the instantaneous fuel consumption attached to each point included in the above-mentioned equivalent output mode. Figure 30A It is a line graph showing the cumulative value of the instantaneous CO2 emissions attached to each feature point included in the above-mentioned specified output mode. Figure 30B It is a line graph showing the cumulative value of the instantaneous CO2 emissions attached to each point included in the above-mentioned equivalent output mode. Figure 31 It is a line graph showing the change in height during the above-mentioned vehicle driving. Figure 32 It is a line graph showing the change in the intake air temperature of the engine. Detailed implementation mode

[0011] Hereinafter, an exemplary implementation mode of the present invention will be described with reference to the accompanying drawings.

[0012] [1. Structure of vehicle diagnostic device] Figure 1 It is a block diagram showing the schematic structure of the vehicle diagnostic device 1 of the present implementation mode. The vehicle diagnostic device 1 is, for example, a device for diagnosing a vehicle based on the energy consumption state in the vehicle. The vehicle to be the diagnostic object of the vehicle diagnostic device 1 can be a vehicle equipped with an engine (including a hybrid vehicle), a vehicle equipped with a secondary battery such as a lithium-ion battery (hereinafter also simply referred to as a battery), or a vehicle equipped with a fuel cell.

[0013] Specifically, the above-mentioned energy consumption state refers to the energy consumption amount or energy consumption rate. In a vehicle equipped with an engine, it is the fuel consumption amount or fuel consumption rate of gasoline, light oil, etc. In a vehicle equipped with a battery, it is the power consumption amount or power consumption rate. In a vehicle equipped with a fuel cell, it is, for example, the hydrogen consumption amount. In addition, as diagnostic items when diagnosing a vehicle, in a vehicle equipped with an engine and a fuel cell, there are deterioration of the fuel consumption rate or deterioration of the drive system, etc. In a vehicle equipped with a battery, there are deterioration of the drive system, deterioration of the power consumption rate, or battery deterioration degree (deterioration rate), etc. Hereinafter, an example of diagnosing a vehicle equipped with a battery will be described.

[0014] The vehicle diagnostic device 1 is constituted by an information processing device such as a personal computer, for example. The vehicle diagnostic device 1 includes a storage unit 2, a data acquisition unit 3, a display unit 4, an input unit 5, and a control unit 6.

[0015] The storage unit 2 is a memory that stores various data, and can be constituted by, for example, a hard disk, an SSD (solid state drive), an optical disk, a magnetic disk, or a non-volatile memory. The storage unit 2 includes a characteristic data storage unit 21, a reference consumption amount storage unit 22, and a program storage unit 23.

[0016] The characteristic data storage unit 21 stores characteristic data of a plurality of sections included in a specified driving mode of the vehicle. The specified driving mode is, for example, a mode based on WLTC, that is, a WLTC driving mode. In addition, the specified driving mode may be a driving mode based on UDDS (Urban Dynamometer Driving Schedule) used in North America, etc., in addition to the WLTC driving mode.

[0017] Figure 2 is a graph showing an example of the WLTC driving mode at the time of vehicle certification. The WLTC driving mode is a mode showing the change in the vehicle speed with respect to the driving time, and is composed of a plurality of parts such as low speed (Low), medium speed (Medium), high speed (High), or extra high speed (Extra High). When a new vehicle is registered, the power consumption rate or fuel consumption rate during driving in the WLTC driving mode is measured, and is registered as certification data by a specified agency as the power consumption rate or fuel consumption rate when the vehicle is new. Furthermore, in the case where a limit on the battery degradation degree after a specified driving is set in the future, it may be necessary to measure the battery degradation degree by some method at the time of inspection, etc., and consider the power consumption rate during WLTC driving that is the same as at the time of measurement and registration. In a vehicle (a battery vehicle, a gasoline vehicle, or a fuel cell vehicle), if the drive system deteriorates due to long-term use, it is considered that the power consumption rate or fuel consumption rate deteriorates.

[0018] As described above, at the time of regular inspection of the vehicle, it is actually difficult to reproduce the WLTC driving cycle for all vehicles to be inspected. Therefore, in the present embodiment, an equivalent mode (equivalent driving mode) to the WLTC driving mode at the time of certification is generated based on the driving data during a specified period before the inspection, and using this equivalent driving mode, diagnosis is performed according to the diagnosis method when the vehicle is driven in the WLTC driving mode. In addition, the details of the diagnosis method of the present embodiment will be described later.

[0019] Figure 3 is an enlarged representation of Figure 2The curve graph of the WLTC driving mode. The above characteristic data is, for example, at least one of the vehicle speed and acceleration in each time interval when the WLTC driving mode is divided into a plurality of time intervals. Hereinafter, the characteristic data in each interval is also referred to as a Profile. For example, Profile P1 is the vehicle speed V satisfying V0 ≤ V ≤ V1 and the acceleration a obtained from a = dv / dt. In Figure 3 where m and n are positive integers. In the present embodiment, the n Profiles P1 to Pn included in one cycle of the WLTC driving mode are stored in advance in the characteristic data storage unit 21 as a Profile Table.

[0020] Figure 1 As shown, the reference consumption storage unit 22 stores the energy consumption (for example, power consumption) of each WLTC driving mode in the vehicle as the reference energy consumption. The program storage unit 23 stores an operation program for operating the control unit 6.

[0021] The data acquisition unit 3 is an actual data acquisition unit that acquires, from the vehicle, the actual driving data for a past specified period and the actual consumption data indicating the consumption of the driving energy (for example, power) of the vehicle during driving in the specified period. Here, the above actual driving data is data indicating the state of the vehicle during actual driving and includes, for example, at least one of the vehicle speed and acceleration. In addition, in a vehicle equipped with an internal combustion engine such as an engine, the actual driving data includes, in addition to the above vehicle speed or acceleration, data such as the engine speed or torque data (details will be described later).

[0022] In addition, when the characteristic data is stored in advance (initially) in the characteristic data storage unit 21, it can be considered that the characteristic data storage unit 21 alone (even without the data acquisition unit 3) constitutes the characteristic data acquisition unit. In addition, when the characteristic data is stored in advance in the characteristic data storage unit 21, the data acquisition unit 3 can also acquire the characteristic data from the characteristic data storage unit 21. In this case, it can also be considered that the data acquisition unit 3 constitutes the characteristic data acquisition unit. In addition, the characteristic data can also be stored in the characteristic data storage unit 21 after being acquired from the outside by the data acquisition unit 3. In this case, it can be considered that the data acquisition unit 3 alone constitutes the characteristic data acquisition unit, or it can be considered that the data acquisition unit 3 and the characteristic data storage unit 21 are integrated to constitute the characteristic data acquisition unit.

[0023] In addition, the vehicle diagnostic device 1 does not necessarily need to have the characteristic data storage unit 21 and can also acquire the characteristic data from the outside (for example, an external server) only via the data acquisition unit 3. That is, the characteristic data acquired from the outside by the data acquisition unit 3 may not be stored in the memory corresponding to the characteristic data storage unit 21. In this case, the data acquisition unit 3 also constitutes the characteristic data acquisition unit that acquires the characteristic data.

[0024] In addition, when data on the reference energy consumption amount is stored in advance (initially) in the reference consumption amount storage unit 22, it can be considered that the reference consumption amount storage unit 22 alone (even without the data acquisition unit 3) constitutes the reference consumption amount acquisition unit. Further, when data on the reference energy consumption amount is stored in advance in the reference consumption amount storage unit 22, the data acquisition unit 3 can also acquire the data on the reference energy consumption amount from the reference consumption amount storage unit 22. In this case, it can also be considered that the data acquisition unit 3 constitutes the reference consumption amount acquisition unit. Further, the data on the reference energy consumption amount can also be stored in the reference consumption amount storage unit 22 after being acquired from the outside by the data acquisition unit 3. In this case, it can be considered that the data acquisition unit 3 alone constitutes the reference consumption amount acquisition unit, or it can be considered that the data acquisition unit 3 and the reference consumption amount storage unit 22 are integrated to constitute the reference consumption amount acquisition unit.

[0025] In addition, the vehicle diagnostic device 1 does not necessarily need to include the reference consumption amount storage unit 22, and it can also acquire the data on the reference energy consumption amount from the outside (e.g., an external server) only via the data acquisition unit 3. That is, the data on the reference energy consumption amount acquired from the outside by the data acquisition unit 3 may not be stored in the memory corresponding to the reference consumption amount storage unit 22. In this case, the data acquisition unit 3 also constitutes the reference consumption amount acquisition unit that acquires the data on the reference energy consumption amount.

[0026] The data acquisition unit 3 is constituted by, for example, a communication unit capable of communicating with the vehicle in a wired or wireless manner. For example, the above communication unit may include a cable and an adapter (in the case of wired) communicably connected to an OBDII (On Board Diagnostics) terminal of a network 100N in the vehicle such as a CAN (Controller Area Network) (refer to Figure 4 ). It may also include a transceiver circuit (a modulation circuit, a demodulation circuit) and an antenna (in the case of wireless).

[0027] The display unit 4 is constituted by a display device such as a liquid crystal display device that displays information. The input unit 5 is constituted by an input device such as a keyboard, a touchpad, a touch panel, or a mouse. In addition, the above actual consumption amount data can also be directly input through the input unit 5. In this case, the input unit 5 constitutes the data acquisition unit 3.

[0028] The control unit 6 is composed of a central arithmetic processing unit called a CPU (Central Processing Unit). The control unit 6 includes a main control unit 61, an equivalent mode generation unit 62, a total consumption calculation unit 63, a determination unit 64, and a prediction unit 65. The main control unit 61 controls the operations of various parts of the vehicle diagnostic device 1. The functions of the equivalent mode generation unit 62, the total consumption calculation unit 63, the determination unit 64, and the prediction unit 65 will be described together in the subsequent operation description.

[0029] In addition, the total consumption calculation unit 63 is included in the actual measurement extraction unit 6P. The actual measurement extraction unit 6P extracts the actual measurements of each point or each interval included in the equivalent driving mode from the actual measurement data during the specified period obtained by the data acquisition unit 3. Here, the actual measurement refers to the actual measurement of parameters required for vehicle diagnosis, such as the energy consumption during vehicle driving (for example, the power consumption if it is an electric vehicle, or the fuel injection amount if it is a gasoline vehicle), the SOC (State Of Charge; charge rate) of the battery, the voltage value and current value of the battery, the emissions of components contained in the exhaust gas (CO2, CO, NOx, etc.), the amount of dust generated from the tires or brakes, and so on.

[0030] [2. Structure example of the vehicle] Next, a structure example of the vehicle that is the diagnosis object of the vehicle diagnostic device 1 of the present embodiment will be described. Figure 4 It is a block diagram showing the schematic structure of the vehicle 100. The vehicle 100 includes: a motor 101, an inverter 102, an HV (high voltage) battery 103 composed of, for example, a lithium-ion battery, an in-vehicle charging unit (charger) 104, a PTC (Positive Temperature Coefficient) heater 105, an A / C compressor 106, a DC-DC converter 107, an LV (low voltage) battery 108 (for example, a 12V battery), a power control ECU 109, a battery management ECU 110, a data recording device 111, an HVAC (Heating, Ventilation, and Air Conditioning) ECU 112, a display 113, a brake ECU 114, and a vehicle speed sensor 115. In addition, each ECU is an Electronic Control Unit. In Figure 4 it, the power supply path from the HV battery 103 is represented by a double line, and the transmission paths of various signals are represented by straight lines.

[0031] The actual driving data and actual consumption data of the vehicle 100 are stored, for example, in the data recording device 111 and transmitted to the vehicle diagnostic device 1 in a wired or wireless manner via the in-vehicle network 100N (refer to Figure 1 ). The actual driving data is obtained based on the detection result of the vehicle speed of the vehicle speed sensor 115 with respect to the passage of time. The actual consumption data is acquired by the battery management ECU 110 that manages the HV battery 103.

[0032] In addition, each ECU may also have a memory inside. For example, the battery management ECU 110 may store information on the battery power of the HV battery 103 in the internal memory. In addition, the brake ECU 114 may store vehicle speed information in the internal memory. Furthermore, the display 113 may store the SOC information of the HV battery 103 in the internal memory.

[0033] [3. General Process of Vehicle Diagnosis] Figure 5 is an explanatory diagram schematically showing the general process of vehicle diagnosis of the vehicle diagnostic device 1. For example, at the time of new model registration, certification based on WLTC is accepted in advance. And after the vehicle is purchased, the first inspection, the second inspection, the third inspection,... are carried out after a certain period (more than once) or regularly. In this inspection, the battery degradation degree, etc. are calculated to diagnose the vehicle. In addition, unless otherwise specified, the following battery refers to Figure 4 the HV battery 103.

[0034] Here, in the first inspection, the vehicle diagnostic device 1 obtains the actual driving data and actual consumption data during a specified period before the first inspection from the vehicle 100 (refer to Figure 4 ), and calculates (estimates) the battery consumption based on these data. Then, the vehicle diagnostic device 1 compares the calculated battery consumption with the battery consumption at the time of WLTC certification to diagnose the battery degradation degree.

[0035] In the second inspection, the vehicle diagnostic device 1 obtains the actual driving data and actual consumption data during a specified period before the second inspection from the vehicle 100, and calculates the battery consumption based on these data. Then, the vehicle diagnostic device 1 compares the calculated battery consumption with the battery consumption at the time of WLTC certification to diagnose the battery degradation degree. In addition, the vehicle diagnostic device 1 may also compare the calculated battery consumption with the battery consumption calculated at the previous inspection (here, the first inspection) to diagnose the battery degradation degree.

[0036] In the third inspection, the vehicle diagnostic device 1 obtains the actual driving data and the actual consumption data during a specified period before the third inspection from the vehicle 100, and calculates the battery consumption based on these data. Then, the vehicle diagnostic device 1 compares the calculated battery consumption with the battery consumption during WLTC certification to diagnose the battery degradation degree. In addition, the vehicle diagnostic device 1 can also compare the calculated battery consumption with the battery consumption calculated during the previous inspection (here, the second inspection) to diagnose the battery degradation degree.

[0037] For inspections after the fourth time, the same diagnosis as above can also be performed. In addition, in each inspection, the battery consumption during vehicle driving in any period before battery degradation can be used instead of the battery consumption during WLTC certification.

[0038] [4. Regarding the vehicle diagnosis method] Figure 6 is a flowchart showing the specific process of the vehicle diagnosis method in the vehicle diagnostic device 1. In addition, here, Figure 3 the graphical table shown is stored in the characteristic data storage unit 21, and the power consumption of each WLTC driving mode in the vehicle 100 (refer to Figure 4 ) is stored in the reference consumption storage unit 22 as information on the reference energy consumption. In addition, hereinafter, the vehicle diagnosis at the first inspection will be described, but the inspections after the second time are the same.

[0039] First, the data acquisition unit 3 of the vehicle diagnostic device 1 obtains the actual driving data of a past specified period from the vehicle 100, and the actual consumption data indicating the energy consumption, that is, the power consumption, of the vehicle 100 during driving in the above-mentioned specified period (S1; actual data acquisition process). Figure 7 shows an example of the actual driving data acquired by the data acquisition unit 3. For example, when the vehicle 100 has driven for 90 minutes during the period from one week before the first inspection to the inspection time, the actual driving data and the actual power consumption data for this 90-minute period are stored in, for example, the data recording device 111 of the vehicle 100 (refer to Figure 4 ). The data acquisition unit 3 obtains the above-mentioned actual driving data and actual consumption data from the data recording device 111 through communication via the network 100N.

[0040] Next, the equivalent mode generation unit 62 intercepts and connects the intervals similar to a plurality of characteristic data (graphs) from the actual driving data of the above-mentioned specified period, thereby generating an equivalent driving mode regarded as equivalent to a specified driving mode (here, the WTLC driving mode) (S2; equivalent mode generation process). Figure 7 shows an example of the above-mentioned equivalent driving mode. In Figure 7The following is an example: Intercept from the actual driving data intervals similar to the characteristic files of the three parts, namely the low-speed, medium-speed, and high-speed parts (excluding the ultra-high-speed part) of the WLTC driving mode represented by Figure 3 to generate an equivalent driving mode.

[0041] Here, the similarity judgment can also be made based on whether the speed or acceleration included in the characteristic data is within a specified range compared to the speed or acceleration included in the actual driving data. In addition, pattern matching of the waveform of the characteristic data and the waveform represented by the actual driving data can also be performed to judge similarity.

[0042] Furthermore, a distribution (scatter plot) representing the relationship between speed and acceleration can be created based on the actual driving data, and compared with Figure 8 the distribution (scatter plot) representing the relationship between speed and acceleration in the characteristic data extracted (sampled) from the WLTC driving mode shown. Points with even partial overlap can be judged as similar. In addition, as shown in the upper part of Figure 9 , in the two-dimensional coordinate representing the relationship between speed and acceleration, a unit grid centered on the characteristic points of the speed and acceleration included in the characteristic data (represented by "WLTC" in Figure 9 ) can also be considered. The unit grid is composed of a range of arbitrary speeds and a range of arbitrary accelerations, and its size can be set appropriately. When the measured values (points representing the speed and acceleration of the actual driving data) are included in the unit grid, the measured values can also be judged as points similar to the characteristic data.

[0043] In addition, as shown in the lower part of Figure 9 , when multiple measured values are included in the unit grid, the power consumption (or SOC) corresponding to the points of the multiple measured values can also be averaged and associated with the power consumption of the characteristic data.

[0044] In short, the equivalent mode generation unit 62 only needs to generate an equivalent driving mode by intercepting points or intervals similar to multiple characteristic data from the actual driving data during the above-specified period.

[0045] Next, the total consumption calculation unit 63 calculates the total energy consumption (total power consumption) obtained by summing the power consumption (power consumed) for each point (multiple sampled points) or each section included in the equivalent driving pattern generated in S2 based on the actual consumption data acquired in S1 (S3; total consumption calculation process). More specifically, the total consumption calculation unit 63 extracts and sums the actual measured values (here, power consumption) for each point or each section included in the equivalent driving pattern generated in S2 from the actual consumption data acquired in S1, that is, the actual measurement data during vehicle driving in the above-mentioned specified period, thereby calculating the above-mentioned total energy consumption. Therefore, the total consumption calculation process in S3 is included in the actual measurement value extraction process.

[0046] For example, one cycle of the equivalent driving pattern is the same as one cycle of the WLTC driving pattern (here, from the low-speed part to the high-speed part). The total energy consumption W in the equivalent driving pattern is represented by the sum of the number of graphs of the power consumption in each section similar to the respective characteristic data. That is, for the total energy consumption W, if the power consumption in each section is set as Ws1, Ws2, Ws3, ……, and the number of graphs is set as n, it is represented by ΣWsk (k is an integer from 1 to n). Additionally, when multiple points are extracted (sampled) from the equivalent driving pattern, it is only necessary to consider replacing the sum of the power consumption in each above-mentioned section with the sum of the power consumption at each point extracted from the equivalent driving pattern (the same applies hereinafter).

[0047] Next, the determination unit 64 determines the state of the vehicle 100 (e.g., battery degradation rate) based on the reference energy consumption pre-acquired by the data acquisition unit 3 and stored in the reference consumption storage unit 22, that is, the pre-acquired power consumption for each WLTC driving pattern and the total energy consumption calculated in S3 (S4; determination process). The following shows a specific determination method.

[0048] Figure 10 It is a graph showing the relationship between the power consumption of the battery and the SOC at the initial stage (before battery degradation) and during inspection (after battery degradation). If the battery degradation rate is set as Wr (%), it is calculated by Wr = Wage / Wint. Here, Wage represents the power consumption of the battery when the SOC is 0% after battery degradation, and Wint represents the power consumption of the battery when the SOC is 0% in the state before battery degradation.

[0049] Wint and Wage are obtained as follows: Functions representing the change rate of SOC (the relationship between power consumption and SOC) are obtained before and after battery degradation, and the value when SOC = 0% is obtained from the above functions. Here, for ease of understanding, the above functions are represented by linear functions. Additionally, the above functions can also be higher-order functions of degree two or more. In this case, the consideration method is the same as the example shown below.

[0050] Let the SOC of the initial battery, i.e., the SOC before battery degradation, be SOC1 (= 100%), the SOC after one cycle of the WLTC driving mode be SOC2, and the power consumption during one cycle of the WLTC driving mode be W2. The above reference energy consumption is equivalent to the power consumption W2. When the decrease in SOC during one cycle of the WLTC driving mode is set as ΔSOC(Initial), ΔSOC(Initial) = SOC1 - SOC2. When the straight line representing the change rate of SOC before battery degradation is represented by Y = AX + B, the slope A of the straight line is A = dSOC / dw = ΔSOC(Initial) / W2. Let B = 1 (= 100%), and by substituting Y = 0 (= 0%) into the above formula, X = -(1 / A) = Wint can be obtained.

[0051] On the other hand, the total energy consumption W during one cycle of the equivalent driving mode is ΣWsk as described above (k is an integer from 1 to n). When the decrease in SOC during one cycle of the equivalent driving mode is set as ΣΔSOCk (k is an integer from 1 to n), ΣΔSOCk = SOC1 - SOC2. When the straight line representing the change rate of SOC after battery degradation is represented by Y’ = A’X’ + B’, the slope A’ of the straight line is A’ = dSOC / dw = ΣΔSOCk / ΣWsk. Let B’ = 1 (= 100%), and by substituting Y’ = 0 (= 0%) into the above formula, X’ = -(1 / A’) = Wage can be obtained.

[0052] If the battery degradation rate Wr (= Wage / Wint) is equal to or higher than a specified value (e.g., 80%), the determination unit 64 determines that the state of the battery is okay and causes the display unit 4 to display this meaning (refer to Figure 1 ). On the other hand, if the battery degradation rate Wr is less than the specified value, the determination unit 64 causes the display unit 4 to display the meaning of battery degradation.

[0053] Next, the prediction unit 65 predicts the degree of battery degradation or the power consumption (power consumption amount) for each WTLC driving mode at a time point after a specified time has elapsed since the completion of the vehicle 100 (SOC1 = 100%) based on the degree of battery degradation (degradation rate Wr) determined by the determination unit 64 (S5; prediction process). For example, in the diagnosis of the first inspection (shortly before 3 years have passed since the vehicle was newly purchased), when the battery degradation rate Wr is 98%, the prediction unit 65 considers the decrease amount (2%) of the degradation rate Wr. In the diagnosis of the second inspection (shortly before 2 years have passed since the first inspection), Wr = 96% is predicted. In the diagnosis of the third inspection (shortly before 2 years have passed since the second inspection), Wr = 94% is predicted.

[0054] The same prediction can also be made for the power consumption. For example, in the diagnosis of the first inspection, when the total energy consumption amount for each cycle of the equivalent driving mode regarded as equivalent to one cycle of the WLTC driving mode is ΣWsk, the prediction unit 65 predicts ΣWsk - α (α is an arbitrary value based on experiments or experience) in the diagnosis of the second inspection, and predicts ΣWsk - 2α in the diagnosis of the third inspection.

[0055] By making such a prediction by the prediction unit 65, for the user of the vehicle 100, it is possible to notify the user of the period of the battery life based on the prediction result.

[0056] As described above, the total consumption calculation unit 63 of the vehicle diagnosis device 1 generates an equivalent driving mode regarded as equivalent to a specified driving mode (WLTC driving mode) based on the past actual driving data of the vehicle 100 and calculates the total energy consumption amount ΣWsk. Thus, even if the vehicle 100 is not actually driven in the specified driving mode, it is possible to obtain information on the consumption amount equivalent to the consumption amount of the driving energy (power consumption amount) obtained when driving in the specified driving mode. Therefore, even if the vehicle 100 is not actually driven in the specified driving mode, the determination unit 64 can determine (diagnose) the vehicle state according to the diagnosis method when driving in the specified driving mode.

[0057] In particular, in the present embodiment, the data acquisition unit 3 acquires data indicating the power consumption amount of the vehicle 100 during driving during a specified period from the vehicle 100 as the actual consumption data. Then, the total consumption calculation unit 63 sums up the power consumption amounts at each point or each interval included in the equivalent driving mode based on the actual consumption data, and calculates the total energy consumption amount ΣWsk. Thus, the determination unit 64 can appropriately determine the degree of degradation of the battery (HV battery 103) storing electric power as the state of the vehicle 100 based on the reference energy consumption amount and the total energy consumption amount.

[0058] In addition, in the present embodiment, the above-mentioned reference energy consumption is the consumption of the electric power stored in the battery when the vehicle 100 travels in a specified driving mode (WLTC driving mode). In this case, the determination unit 64 can use the consumption of the battery when traveling in the specified driving mode as a reference to determine the degree of battery degradation during the inspection.

[0059] In S1, the data acquisition unit 3 acquires the actual driving data and the actual consumption data from the data recording device 111 (refer to Figure 4 ) mounted on the vehicle 100. In this case, since the vehicle diagnostic device 1 can directly access the vehicle 100 to acquire the actual driving data and the like, this acquisition is rapid and easy.

[0060] In the present embodiment, the above-mentioned specified driving mode is the WLTC driving mode. In this case, even if the vehicle 100 does not actually travel in the WLTC driving mode, the determination unit 64 can determine (diagnose) the vehicle state according to the diagnostic method when traveling in the WLTC driving mode.

[0061] Figure 11 It is a graph showing another example of the specified driving mode. As shown in the figure, as the specified driving mode of the vehicle 100, a driving mode other than the WLTC driving mode can also be used. For example, the actual driving data obtained before battery degradation or at an arbitrary timing can be used as the specified driving mode. Here, the actual driving data obtained before battery degradation or at an arbitrary timing can be the driving data after 1 month from the time of WLTC certification, or the driving data after 1 year from the time of WLTC certification, or the driving data of the equivalent driving mode generated in the previous inspection.

[0062] A plurality of graphs extracted from the actual driving data before battery degradation are pre-stored in the feature data storage unit 21 as a graph table. During the inspection, an interval similar to each graph (feature data) is intercepted from the actual driving data during the specified period before the inspection and an equivalent driving mode is generated, whereby vehicle diagnosis (for example, diagnosis of the degree of battery degradation) can be performed in the same manner as in the present embodiment.

[0063] [5. Regarding the Consistency Judgment of the Mode] Figure 12 It is an explanatory diagram showing a calculation method of an index indicating the consistency (certainty) of the evaluation graph data and the data intercepted from the actual driving data in the above S2. In S2, when intercepting an interval similar to a plurality of feature data (graphs) from the actual driving data and generating an equivalent driving mode, the deviation between the graph data and the intercepted data can also be calculated as the certainty of the final combined graph.

[0064] For example, when the acceleration in an arbitrary graph is set as a#table, the acceleration in an interval similar to the above graph in the actual driving data is set as a#real, and the total time of n graphs is set as t#total, the consistency (certainty) Pk between the data of the k-th graph and the data of the interval similar to the k-th graph intercepted from the actual driving data is expressed as Pk = (a#real / a#table) × dt / t#total. Here, k is an arbitrary integer from 1 to n. Therefore, the consistency P of all the data of the n graph data is expressed as Σ|Pk|.

[0065] Therefore, if the consistency P is equal to or higher than a specified value (for example, 0.80), the consistency between each graph data and the data intercepted from the actual driving data is high, and it can be determined that the reliability of the generated equivalent driving pattern is high. On the contrary, if the consistency P is less than the specified value, the consistency between each graph data and the data intercepted from the actual driving data is low, and it can be determined that the reliability of the generated equivalent driving pattern is low.

[0066] [6. Calibration of data considering usage status and surrounding environment] The driving load of the actual vehicle 100 is affected by the usage status of the vehicle 100 (such as the use of the 12V battery and air conditioner), the surrounding environment (rain, wind, road (ramp, turn)), etc. Therefore, it is preferable to measure and estimate the power consumption caused by these main reasons based on the actual driving data, etc., and correct the power consumption of the comparison data. Hereinafter, the correction of the power consumption considering the usage status, etc. will be described.

[0067] For example, the power of the LV battery 108 (refer to Figure 4 ) is consumed by the use of electronic components, audio, HVAC blower, lights, wipers, or heating wires, etc. mounted on the vehicle 100. Since power is supplied from the HV battery 103 shown in Figure 4 to the LV battery 108 via the DC-DC converter 107, the power consumption in the LV battery 108 affects the power consumption of the HV battery 103. The power consumption of the LV battery 108 can be calculated based on the values of the ammeter and voltmeter provided in the power supply path. For example, when the power consumed by arbitrary electronic components, etc. is set as W LV , the voltage value and current value at this time are set as V LV and I LV respectively, W LV = V LV × I LV . Therefore, in the case where there are N electronic components, etc., the total power consumed by the N electronic components, etc. is ΣW LV (N).

[0068] In the initial no-load state, i.e., in one cycle of the WLTC driving mode, if the minimum necessary power consumption of electronic components etc. is set to W LV (Initial), and the difference in power consumption of electronic components etc. between WLTC certification and inspection is set to ΔW LV , then ΔW LV = ΣW LV (N) - W LV (Initial).

[0069] On the other hand, as an influence of the surrounding environment of the vehicle 100, the influence of the driving resistance of the vehicle 100 is considered here. If the driving resistance of the vehicle 100 is set to F RL , then F RL is represented by the following formula. F RL = Crr × (mg + m add g) + A × ρ × Cd × (v veh 2 + v win 2 ) + (mg + madd g) × sinθ Among them, Crr: Rolling resistance coefficient (the value owned by the manufacturer can be used, or the measured value at the initial stage (such as at the time of type certification) etc. can be referred to) m: Vehicle weight g: Acceleration due to gravity m add : Occupant + load weight (can also be measured by in-vehicle sensors (load sensor, vehicle height sensor, etc.)) A: Projected frontal area of the vehicle ρ: Air density Cd: Air resistance coefficient v veh : Vehicle speed v win : Wind speed (can also be estimated based on cloud information) sinθ: Slope (can be calculated by in-vehicle sensors (G sensor, Gyro sensor, etc.), or the slope data of the digital map can be used).

[0070] If the increased power consumption due to the driving resistance of the vehicle 100 is set to ΔW RL , then it is represented by ΔW RL = F RL × V veh .

[0071] Figure 13Represents the relationship between the corrected total energy consumption Wc in the equivalent driving mode and the SOC representing the corrected SOC CO The corrected total energy consumption Wc is represented by Wc = ΣWsk - (ΔW LV + ΔW RL ) In the equation (Y’ = A’X’ + B’) of the straight line representing the change rate of the SOC after battery degradation, the value of Y’ when X’ = Wc is SOC CO . That is, the SOC when subtracting the power consumption amount of (ΔW LV + ΔW RL ) from the total energy consumption ΣWsk (= SOC CO ) is used as the SOC in one cycle of the equivalent driving mode.

[0072] As described above, when the data acquisition unit 3 further acquires data related to the usage state or surrounding environment of the vehicle 100 from the vehicle 100, the total consumption calculation unit 63 removes the power consumption amount of the battery consumed due to the usage state or surrounding environment of the vehicle 100 (ΔW LV + ΔW RL ) and calculates the total energy consumption of the battery (the corrected Wc). In this way, considering the driving load (usage state, surrounding environment) of the vehicle 100, the total energy consumption Wc is calculated, so vehicle diagnosis can be performed more appropriately compared to the no-load state during WLTC certification.

[0073] [7. Other Diagnostic Methods for Vehicles] In the vehicle diagnostic device 1 of this embodiment, it is also possible to diagnose the state of the vehicle 100 (such as the degree of battery degradation) using parameters other than the power consumption. Figure 14 It is a block diagram showing another structure of the control unit 6 of the vehicle diagnostic device 1. In addition, the structure other than the control unit 6 is the same as Figure 1 .

[0074] As Figure 14 shown, in addition to the above-mentioned total consumption calculation unit 63, the actual measurement extraction unit 6P of the control unit 6 also includes a resistance change amount calculation unit 66, a voltage change amount calculation unit 67, a total injection amount calculation unit 68, and a total emission amount calculation unit 69. In addition, the actual measurement extraction unit 6P only needs to include at least one of the total consumption calculation unit 63, the resistance change amount calculation unit 66, the voltage change amount calculation unit 67, the total injection amount calculation unit 68, and the total emission amount calculation unit 69. Hereinafter, other diagnostic methods for the vehicle 100 will be described.

[0075] (7-1. Vehicle Diagnosis Based on the Change in the Internal Resistance of the Battery) Figure 15It is an explanatory diagram schematically including a circuit comprising an HV battery 103 and a vehicle load Rv (Ω). Here, the vehicle load Rv includes electrical components driven by the power supplied from the HV battery 103 (including Figure 4 the powertrain of the inverter 102 such as a heat pump), electrical components driven by the power supplied from the LV battery 108 (such as wipers), and the load (resistance) of other electrical components.

[0076] Let the value of the current output from the HV battery 103 be I (A), and the value of the output voltage be V (V). In addition, let the internal resistance of the HV battery 103 be Rb (Ω). At this time, before the deterioration (initial) of the HV battery 103, the following relationship holds among V, I, Rb, and Rv. That is, the following formula. V = I × (Rv + Rb)......(1) If this formula is transformed, it becomes the following formula. Rv + Rb = V / I......(1a)

[0077] Due to the aging deterioration of the HV battery 103, the internal resistance of the HV battery 103 increases by ΔRb (Ω) compared to before the deterioration (reference). Therefore, after the aging deterioration of the HV battery 103, the following relationship holds. That is, the following formula. V = I × (Rv + Rb + ΔRb)......(2) If this formula is transformed, it becomes the following formula Rv + Rb + ΔRb = V / I......(2a) In addition, the left sides of formulas (1a) and (2) are also referred to as the total resistance.

[0078] The above I and V are recorded as actual battery data, for example, in a data recording device 111 (refer to Figure 4 ). In addition, the value of Rv is known, and the initial value of Rb is obtained from formula (1) or (1a). Therefore, the resistance change amount calculation unit 66 can calculate the change amount ΔRb of the internal resistance based on formula (2a).

[0079] Figure 16 It is a graph showing the equivalent driving mode before battery deterioration generated by replacing the speed on the vertical axis with the total resistance. That is, Figure 16 The graph of shows schematically the change of the total resistance calculated based on formula (1a) with respect to the passage of time by extracting the voltage value V and the current value I of each interval of the equivalent driving mode from the actual battery data (voltage value V, current value I) during a specified period recorded in the data recording device 111. In addition, Figure 17 is a graph showing Figure 16 by increasing the magnification on the vertical axis. In addition, in Figure 17Among them, an approximate curve (dashed line) of the total resistance before battery degradation and an approximate curve (solid line) of the total resistance over time are shown together. If the HV battery 103 degrades, the curve shifts upward (in the direction of increasing total resistance) by an amount of ΔRb. As described above, this ΔRb can be calculated by the resistance change amount calculation unit 66 based on Equation (2a). Additionally, in Figure 17 the change of the average value of the total resistance in each interval is simply approximated by a quadratic curve, but it can also be approximated by a higher-order curve other than the quadratic curve.

[0080] Therefore, by calculating the above change amount ΔRb by the resistance change amount calculation unit 66, the determination unit 64 can determine the state of the vehicle 100 based on the change amount ΔRb. For example, when ΔRb is equal to or greater than the threshold value, the determination unit 64 can determine that the HV battery 103 is degraded, and when ΔRb is less than the threshold value, the determination unit 64 can determine that the HV battery 103 is not degraded.

[0081] In this way, when the actual measurement data includes actual battery data representing the current value I and voltage value V of the HV battery 103 during the operation of the vehicle 100 in a specified period, the resistance change amount calculation unit 66 extracts the current value I and voltage value V of the HV battery 103 in each interval of the equivalent driving mode from the above actual battery data in the specified period, and based on the extracted current value I and voltage value V, obtains the change amount ΔRb of the internal resistance of the HV battery 103 from the reference. Thus, the determination unit 64 can determine the degradation degree of the HV battery 103 based on the change amount ΔRb. Based on the above, it can be considered that the resistance change amount calculation unit 66 constitutes a change amount calculation unit 70 for obtaining the change amount ΔRb.

[0082] (7-2. Vehicle Diagnosis Based on Voltage Change of Battery) Figure 18 is an explanatory diagram showing the voltage Vb before voltage drop of the internal resistance Rb of the HV battery 103 together in the circuit shown in Figure 15 . Additionally, the voltage Vb is known and constant. At this time, before (initial) degradation of the HV battery 103, the following relationship holds among V, Vb, I, Rb, and Rv. That is, the following formula. V = I×(Rv + Rb)……(1) V = Vb - Rb×I……(3)

[0083] If the internal resistance of the HV battery 103 increases by ΔRb due to aging degradation of the HV battery 103, the voltage value V output from the HV battery 103 decreases. The voltage value V after aging degradation of the HV battery 103 at this time is represented by the following formula. V = Vb - (Rb + ΔRb)×I……(4) That is, if ΔRb × I = ΔV, then due to the aging deterioration of the HV battery 103, the voltage value V decreases by ΔV compared to before the deterioration.

[0084] Figure 19 It is a graph showing the equivalent driving pattern before battery deterioration generated by replacing the speed on the vertical axis with the voltage value V of the HV battery 103. That is, Figure 19 The graph of shows schematically the change of the voltage value V calculated based on the formula (3) with respect to the passage of time by extracting the voltage value V of each section of the equivalent driving pattern from the actual battery data (voltage value V) during a specified period recorded in the data recording device 111. It can be seen that if the HV battery 103 deteriorates, the curve shifts downward (the direction in which the voltage value V decreases) by ΔV.

[0085] Therefore, when the actual measurement data includes actual battery data representing the voltage value V of the HV battery 103 during the driving of the vehicle 100 in a specified period as the actual measurement value, the voltage change calculation unit 67 extracts the voltage value V of each section of the equivalent driving pattern from the above actual battery data during the specified period, and can calculate the change amount ΔV of the extracted voltage value V from a reference (for example, the value before deterioration). Thus, the determination unit 64 can determine the state of the vehicle 100 based on the above change amount ΔV. For example, when ΔV is equal to or greater than the threshold value, the determination unit 64 can determine that the HV battery 103 has deteriorated, and when ΔV is less than the threshold value, the determination unit 64 can determine that the HV battery 103 has not deteriorated. In addition, ΔV can be the instantaneous value of the voltage (instantaneous value) or the average value of the voltage in each section. Based on the above situation, it can be considered that the voltage change calculation unit 67 constitutes a change calculation unit 70 that obtains the change amount ΔV.

[0086] In addition, when the work amount W is set to be constant, according to W = V × I, if the voltage value V decreases, the current value I increases. Therefore, if due to the aging deterioration of the HV battery 103, the voltage value V decreases by ΔV compared to before the deterioration, the current value I increases by ΔI. Therefore, when the actual measurement data includes actual battery data representing the current value I of the HV battery 103 during the driving of the vehicle 100 in a specified period as the actual measurement value, the change calculation unit 70 extracts the current value I of each section of the equivalent driving pattern from the above actual battery data during the specified period, and can calculate the change amount ΔI of the extracted current value I from a reference (for example, the value before deterioration). Thus, the determination unit 64 can determine the state of the vehicle 100 based on the above change amount ΔI. For example, when ΔI is equal to or greater than the threshold value, the determination unit 64 can determine that the HV battery 103 has deteriorated, and when ΔI is less than the threshold value, the determination unit 64 can determine that the HV battery 103 has not deteriorated. In addition, ΔI can be the instantaneous value of the current (instantaneous value) or the average value of the current in each section.

[0087] (7-3. Deterioration Judgment of Battery Considering Temperature) Figure 20 It is a graph showing an example of the discharge temperature characteristics of the HV battery 103. As shown in the figure, the HV battery 103 has the characteristic of discharging (the voltage value rapidly approaches zero) within a specified time (about 5 hours in the example of Figure 20 ). In addition, the discharge characteristics of the HV battery 103 vary according to temperature, and there is a tendency for the output voltage to decrease as the temperature decreases. Therefore, for example, if the above battery deterioration judgment is performed at a temperature as low as -20°C, although the HV battery 103 is not deteriorated, due to the low output voltage, there may be a misjudgment that the HV battery 103 is deteriorated.

[0088] Therefore, preferably, when the temperature of the HV battery 103 is within a specified temperature range (for example, 0°C or higher, preferably 20°C or higher), the determination unit 64 determines the state of the vehicle 100 (such as the battery deterioration degree). Thereby, the possibility of the above misjudgment caused by the low temperature of the HV battery 103 can be reduced.

[0089] In addition, the temperature of the HV battery 103 can be detected by a sensor built in or external to the HV battery 103, or the temperature of the cooling water for cooling the HV battery 103 can be used instead. In addition, these temperature values can also be recorded as temperature data in the data recording device 111 (refer to Figure 4 ).

[0090] On the other hand, when the temperature of the HV battery 103 deviates from the specified temperature range (for example, 0°C or higher), from the viewpoint of reducing the above misjudgment, the determination unit 64 may interrupt the determination of the state of the vehicle 100 (such as the battery deterioration degree), but it can also be handled in the following manner.

[0091] That is, when the temperature of the HV battery 103 deviates from the specified temperature range, the determination unit 64 can also correct the voltage value V of the HV battery 103 to the voltage value V' at a specified temperature (for example, 20°C), and determine the state of the vehicle 100. For example, when the temperature of the HV battery 103 is -20°C, the determination unit 64 can also multiply the detected voltage value V of the HV battery 103 by a previously obtained correction coefficient K, correct it to the voltage value V' at a specified temperature (for example, 20°C), and use the corrected voltage value V' to perform the above battery deterioration judgment. By correcting the voltage value V in this way, even when the temperature of the HV battery 103 deviates from the specified temperature range, it is possible to judge the battery deterioration degree while reducing the risk of misjudgment.

[0092] [8. Other Calculation Methods for Vehicle Gradient] In the above [6. Calibration of data considering the usage state and the surrounding environment], the slope θ of the vehicle 100 considered when considering the driving resistance of the vehicle 100 can be obtained without using in-vehicle sensors (G sensor, Gyro sensor, etc.). Hereinafter, other calculation methods of the slope θ will be described.

[0093] As Figure 4 shown, the vehicle 100 is equipped with a GPS (Global Positioning System) 116. Through the GPS 116, the height information of the vehicle 100 can be obtained. The above height information of the vehicle 100 is recorded in the data recording device 111.

[0094] Figure 21 An example of an equivalent driving mode (see the following paragraph) and the change mode of the height information of the vehicle 100 extracted in each section of the above equivalent driving mode (see the above paragraph) are shown together. Figure 22 Enlarged representation Figure 21 of a part of any period TA in the equivalent driving mode and the change mode of the height information. In the period TA, when the speed (which can also be the average vehicle speed) of the vehicle 100 is set to be constant (for example, 11.9 m / s), the moving distance L of the vehicle 100 is represented by vehicle speed × sampling time = (11.9 m / s) × (1 × 1 / 10 s). According to Figure 22 the relationship among θ, L, and ΔA in the upper graph of θ [rad.] = arctan(ΔA / L)

[0095] Therefore, Figure 1 and Figure 14 the total consumption calculation unit 63 shown in RL can calculate the driving resistance F of the vehicle 100 by using the above formula when calculating the total energy consumption of the battery (the corrected Wc), and can eliminate the need for in-vehicle sensors such as G sensors and Gyro sensors that directly detect the slope θ, which is one of the parameters required for the calculation of

[0096] [9. Other examples of actual measurement data] As described above, as the actual measurement data obtained by the data acquisition unit 3 (see Figure 1 ), the actual consumption data and the actual battery data are taken as examples, but it is not limited to these data. For example, the actual measurement data may also include actual injection amount data representing the fuel injection amount during the driving of the vehicle 100 during a specified period as the actual measurement amount.

[0097] Figure 23AIt is a graph of time series data of the instantaneous fuel consumption (instantaneous fuel injection amount) in one cycle of the equivalent driving mode when the vehicle 100 is a vehicle driven by a fuel such as gasoline or light oil. The above-mentioned instantaneous fuel consumption is the instantaneous value (unit: g / s) of the fuel injection amount included in the above-mentioned actual injection amount data obtained along with (simultaneously with) the speed data of each characteristic point of the equivalent driving mode. Figure 23B It is a graph showing the change in the cumulative value (total injection amount) of each characteristic point of the above-mentioned instantaneous fuel injection amount. The above-mentioned total injection amount is Figure 14 calculated by the total injection amount calculation unit 68 shown in FIG. by summing up the fuel injection amounts of each characteristic point of the equivalent driving mode based on the above-mentioned actual injection amount data.

[0098] In this way, by calculating the total injection amount by the total injection amount calculation unit 68, the determination unit 64 can diagnose the vehicle 100 based on the above-mentioned total injection amount. For example, when the above-mentioned total injection amount in one cycle of the equivalent driving mode is equal to or greater than the threshold value, the determination unit 64 can determine that the engine is deteriorated, and when the above-mentioned total injection amount is less than the threshold value, the determination unit 64 can determine that the engine is not deteriorated.

[0099] In addition, the above-mentioned actual measurement data may also include actual emission data representing the emissions of a specified component contained in the exhaust gas during the driving of the vehicle 100 in a specified period as actual measurement values. In addition, the above-mentioned specified component may be CO2, may be CO, or may be NOx. In addition, the above-mentioned emissions may also be obtained by detecting the specified component contained in the exhaust gas in an analysis device originally installed in the vehicle 100 and performing calculations. In addition, the above-mentioned emissions may also be obtained by guiding the exhaust gas to an in-vehicle exhaust gas analysis device retrofitted to the vehicle 100.

[0100] Figure 24A It is a graph of time series data of the instantaneous CO2 emissions in one cycle of the equivalent driving mode when the vehicle 100 is a vehicle driven by a fuel such as gasoline or light oil. The above-mentioned emissions are the instantaneous values (unit: g / s) of the CO2 emissions included in the above-mentioned actual emission data obtained along with the speed data of each characteristic point of the equivalent driving mode. Figure 24B It is a graph showing the change in the cumulative value (total emissions) of each characteristic point of the above-mentioned instantaneous CO2 emissions. The above-mentioned total emissions are Figure 14 calculated by the total emissions calculation unit 69 shown in FIG. by summing up the CO2 emissions of each characteristic point of the equivalent driving mode based on the above-mentioned actual emission data.

[0101] In this way, the total emission calculation unit 69 calculates the total emissions, and the determination unit 64 can diagnose the vehicle 100 based on the above total emissions. For example, when the total emissions in one cycle of the equivalent driving mode are equal to or higher than the threshold value, the determination unit 64 can determine that the engine is deteriorated, and when the total emissions are less than the threshold value, the determination unit 64 can determine that the engine is not deteriorated.

[0102] In addition, for example, a detector for measuring the depth of the grooves of the tires of the vehicle 100 and a detector for measuring the rubber dust of the tires can be used in combination, and these measurement data can be used as the actual measurement data described in the present embodiment. In this case, the total value of the tire wear amount in one cycle of the equivalent driving mode is calculated, and based on the calculated total value, the state of the vehicle 100 (the degree of deterioration of the tires (necessity for replacement)) can be determined.

[0103] Similarly, for example, a detector for measuring the metal dust of the brake pads can be used in combination, and the above metal dust measurement data can be used as the actual measurement data described in the present embodiment. In this case, the total value of the brake pad wear amount in one cycle of the equivalent driving mode is calculated, and based on the calculated total value, the state of the vehicle 100 (the degree of deterioration of the brake pads (necessity for replacement)) can be determined.

[0104] Based on the above, it can be considered that the above actual measurement data may also include actual wear amount data indicating the wear amounts of the tires or brake pads during the driving of the vehicle 100 during a specified period as actual measurement amounts, and the determination unit 64 can also determine the state of the vehicle 100 based on the total value of the above actual wear amounts in each section of the equivalent driving mode. In addition, data extracted in each section of the driving mode can be used instead of the accompanying data of each characteristic point to determine the deterioration of the engine.

[0105] The specified driving mode (for example, the WLTC driving mode) described above is an example of a specified output mode. That is, the above output mode may also be the above driving mode indicating the change in the speed of the vehicle 100 with respect to the passage of time during driving. In this case, it can also be considered that the equivalent driving mode regarded as equivalent to the specified driving mode is an example of an equivalent output mode.

[0106] [10. Method for Judging the Degree of Deterioration in a Vehicle Equipped with an Internal Combustion Engine] As described above, the vehicle 100 can be a vehicle other than a vehicle equipped with a battery, or a vehicle equipped with an internal combustion engine (ICE; internal combustion engine) such as an engine. In this case, the fuel consumption (fuel consumption rate) of the vehicle 100 can also be calculated, and when performing vehicle diagnosis, the method described above can be applied for vehicle diagnosis.

[0107] In addition, in the structure where the vehicle 100 is equipped with an engine, vehicle diagnosis (judgment of the degree of deterioration of the engine) can also be performed in the following manner. In addition, the deterioration of the engine means, for example, at least one of a decrease in combustion efficiency from a reference and an increase in the emission amount of a specified component contained in the exhaust gas as the engine is used. Hereinafter, a method for judging the degree of deterioration of the engine will be described. In addition, the flow of the judgment method shown below is the same as the flow shown in the flowchart above Figure 6 The flow shown in the flowchart. In addition, the judgment method shown below can be applied not only to the judgment of the degree of deterioration of engines installed in gasoline vehicles, diesel vehicles, or hybrid vehicles, but also to the judgment of the degree of deterioration of hydrogen internal combustion engines (H2ICE).

[0108] First, the preconditions will be described. Figure 25 Represents the driving mode of the vehicle 100 obtained before the deterioration of the engine. In addition, the above driving mode before the deterioration of the engine can also be the WLTC driving mode. In the feature data storage unit 21 (refer to Figure 1 ), data of each point (each feature point) obtained by sampling the above driving mode at a specified time interval (for example, 100 ms) is stored.

[0109] Figure 26 Is a scatter diagram showing the distribution of data of each feature point. The above scatter diagram is a graph depicting each feature point with the engine speed (rpm) as the horizontal axis and the engine rotational torque (Nm) as the vertical axis. Here, the distribution of each feature point representing the relationship between the engine speed and torque when driving in the mode shown in the above scatter diagram, that is, the driving mode before the deterioration of the engine, is set as the "specified output mode". In addition, the engine speed and torque can be values (internal values) obtained by sensors inside the vehicle 100 or the like, or values (measurement values) obtained by connecting other measurement devices to the vehicle 100.

[0110] In addition, here, information on the fuel consumption amount and its cumulative value corresponding to each feature point of the specified output mode of the vehicle 100 is stored in the reference consumption amount storage unit 22 (refer to Figure 1 ).

[0111] Hereinafter, a specific method for judging the degree of deterioration will be described. The data acquisition unit 3 of the vehicle diagnosis device 1 acquires the actual driving data of the vehicle 100 for a past specified period from the vehicle 100 or an external device and the actual consumption data (corresponding to Figure 6S1). Additionally, the start time of the above-mentioned past specified period is the time (after a lapse of time or after a lapse of years) when a specified date and time has passed since an arbitrary time before the engine deterioration of the vehicle 100. Additionally, the data acquisition unit 3 may also directly acquire the data described later Figure 27 (data representing the relationship between the engine speed and torque) to replace the acquisition of actual driving data in S1.

[0112] Next, the equivalent mode generation unit 62 generates an equivalent output mode regarded as equivalent to a specified output mode by intercepting points similar to a plurality of characteristic data (the above-mentioned respective characteristic points) from the actual driving data during the above-mentioned specified period (corresponding to Figure 6 S2). Additionally, a similar determination method can use the same method as the method described based on the above Figure 8 and Figure 9 . For example, in the actual driving data, the engine speed or torque within a specified range (within the allowable error) of the engine speed or torque included in the specified output mode can be determined as similar.

[0113] Figure 27 is a scatter diagram showing the distribution of all points (points representing speed and torque) extracted from the actual driving data at a specified time interval (e.g., 100 ms). The equivalent mode generation unit 62 intercepts Figure 27 the points similar to the characteristic points shown in Figure 26 from each of the points shown in, and generates an equivalent output mode. Figure 28 shows an example of the equivalent output mode. The equivalent output mode is a mode in which the engine speed is on the horizontal axis and the engine rotational torque is on the vertical axis, and the distribution of the points indicated by the "○" marks in the figure corresponds to the equivalent output mode. Additionally, in Figure 28 , the points indicated by overlapping "×" marks on the "○" marks represent the characteristic points where there are no similar points in the actual driving data.

[0114] Next, the total consumption calculation unit 63 calculates the total energy consumption obtained by summing the fuel consumptions attached to each of the points (sampled multiple points) included in the equivalent output mode generated in S2 based on the actual consumption data acquired in S1 (corresponding to Figure 6 S3). Additionally, the attached data (fuel consumption) can be an internal value acquired inside the vehicle 100, or a measured value acquired by connecting other measurement devices to the vehicle 100.

[0115] Next, the determination unit 64 determines the state of the vehicle 100 (the degree of deterioration of the engine) based on the reference energy consumption amount that has been acquired in advance by the data acquisition unit 3 and stored in the reference consumption amount storage unit 22, that is, the fuel consumption amount (cumulative value) corresponding to each characteristic point before the engine deterioration acquired in advance, and the total energy consumption amount calculated in S3 (corresponding to Figure 6 S4).

[0116] Figure 29A It is a graph showing the cumulative value of the instantaneous fuel consumption amount (L) attached to each characteristic point included in the specified output mode. Figure 29B It is a graph showing the cumulative value of the instantaneous fuel consumption amount (L) attached to each point included in the equivalent output mode. If the above-mentioned reference energy consumption amount is set as F1 (L) and the above-mentioned total energy consumption amount is set as F2 (L), then it can be considered that F = F2 - F1 is the fuel consumption amount additionally consumed due to the deterioration of the engine over time (years). Therefore, the determination unit 64 can determine the degree of deterioration of the engine based on the value of F (additional fuel consumption amount). For example, when F is equal to or greater than the specified threshold value, it can be determined that the degree of deterioration of the engine is large, and when it is less than the specified threshold value, it can be determined that the degree of deterioration of the engine is small.

[0117] Here, the output of the engine is generally expressed as follows. Engine output (kW) = 2π × torque (Nm) × rotational speed (rpm) / 60 / 1000 In a vehicle equipped with an engine, in addition to the rolling resistance generated by wind and friction with the road surface, all the driving loads generated by current consumption of air conditioners, etc. are reflected as work amounts in the above-mentioned engine output. In addition, there is a correlation between the fuel consumption amount and the engine output. For example, if the engine output increases, the fuel consumption amount also increases.

[0118] Therefore, as described above, by comparing the data (here, the fuel consumption amount) attached to the mode (rotational speed and torque) of the engine output at the initial stage (reference before engine deterioration) and after several years (after engine deterioration), it is possible to determine the degree of deterioration of the engine relative to the initial state without correcting the influence of wind, etc. (also considering the influence of wind, etc.).

[0119] In addition, the specified output mode serving as a reference is a set of points (characteristic points) representing the relationship between the rotational speed and torque of the engine as an internal combustion engine. And the equivalent output mode is a set of points regarded as equivalent to each point included in the above-mentioned specified output mode. Thus, based on the data (here, the fuel consumption amount) attached to each characteristic point included in the specified output mode and the data (here, the fuel consumption amount) attached to each point included in the equivalent output mode, it is possible to reliably determine the degree of deterioration of the engine.

[0120] As described above, an example has been given of using data on fuel consumption as the data attached to each point of the above-described specified output pattern and the above-described equivalent output pattern when determining the degree of deterioration of the engine. However, even if data on the emissions of specified components contained in the exhaust gas is used instead of fuel consumption, the degree of deterioration of the engine can be determined by the same method as described above.

[0121] Figure 30A It is a graph showing the cumulative value of the instantaneous CO2 emissions (g) attached to each characteristic point included in the specified output pattern. Figure 30B It is a graph showing the cumulative value of the instantaneous CO2 emissions (g) attached to each point included in the equivalent output pattern.

[0122] Here, the instantaneous CO2 emissions and their cumulative values before the deterioration of the engine of the vehicle 100 are stored in the reference consumption storage unit 22 as information on the reference energy consumption (see Figure 1 ). And, the cumulative value of the instantaneous CO2 emissions as the above-described reference energy consumption is set to G1 (g). In addition, in S3, when the total consumption calculation unit 63 calculates the total energy consumption obtained by summing the instantaneous CO2 emissions attached to each point included in the equivalent output pattern generated in S2 based on the actual consumption data obtained in S1, this total energy consumption is set to G2 (g). In this case, it can be considered that G = G2 - G1 is the CO2 emissions additionally emitted due to the deterioration of the engine over time (years).

[0123] Therefore, the determination unit 64 can determine the degree of deterioration of the engine based on the value of G (additional CO2 emissions). For example, when G is equal to or greater than a specified threshold value, it can be determined that the degree of deterioration of the engine is large, and when it is less than the specified threshold value, it can be determined that the degree of deterioration of the engine is small. That is, even when using CO2 emissions as the data attached to the mode (rotation speed and torque) of the engine output, the degree of deterioration of the engine can be determined. In addition, even when using the emissions of components other than CO2 (CO, NOx, etc.) contained in the exhaust gas, the degree of deterioration of the engine can be determined by the same method as described above.

[0124] In addition, the attached data (fuel consumption, CO2 emissions, etc.) of the points shown in each scatter diagram can be recorded in a recording medium provided in the vehicle, or can be recorded externally (for example, a cloud server).

[0125] In order to improve the accuracy of the determination of the degree of deterioration of the internal combustion engine described above, the degree of deterioration can also be determined by considering the main causes of the decrease in combustion efficiency or the increase in exhaust emissions.

[0126] Figure 31It is a graph showing the change in height during vehicle travel. If the height during vehicle travel is high, the combustion efficiency of the engine decreases due to the decrease in air pressure. Therefore, in each of the above scatter diagrams, for feature points where the height is above a specified threshold H0 and points similar to the above feature points, the data attached to each point can also be not used (ignored) to determine engine deterioration. That is, the corresponding attached data (fuel consumption or emissions of specified components) can also be removed to calculate the reference energy consumption and the total energy consumption, and the determination unit 64 determines the degree of engine deterioration based on these reference energy consumption and total energy consumption.

[0127] Figure 32 It is a graph showing the change in the intake air temperature of the engine. In addition, the intake air temperature corresponds to the outside air temperature. If the intake air temperature is high, the combustion efficiency of the engine decreases. Therefore, in each of the above scatter diagrams, for feature points where the intake air temperature is above a specified threshold T0 and points similar to the above feature points, the data attached to each point can also be not used to determine engine deterioration.

[0128] In addition, for example, if the humidity becomes high due to an increase in rainfall, the combustion efficiency may decrease. Whether the humidity is high can be determined based on the detection of raindrops by the vehicle's raindrop detection sensor or the operation of the windshield wipers. Therefore, for example, when the detection of raindrops and the operation of the windshield wipers continue for a specified time or more, it is presumed that the humidity is above the threshold, and the data attached to each point at this time can also be not used to determine engine deterioration.

[0129] In addition, in the case of an exhaust catalyst (exhaust purification catalyst), when the temperature is low, the removal effect of harmful components (CO, HC, NOx) in the exhaust gas decreases, and the emissions of specified components (for example, CO2) increase. Therefore, in each of the above scatter diagrams, for feature points where the temperature of the exhaust catalyst is less than a specified threshold and points similar to the above feature points, the data attached to each point can also be not used to determine engine deterioration.

[0130] In addition, when the vehicle accelerates suddenly, due to the excessive supply of fuel to the engine, a temporary increase in exhaust occurs. The increase in exhaust at this time is not proportional to the work done by the engine. Therefore, when the vehicle accelerates suddenly, in each of the above scatter diagrams, the data attached to the corresponding feature points and points similar to the above feature points can also be not used to determine engine deterioration.

[0131] For factors other than the above that affect the combustion efficiency and exhaust removal efficiency of the engine, these factors can also be considered in the same way as above to determine engine deterioration. In addition, correction based on each main cause can also be performed instead of not using the attached data.

[0132] [11. Procedure] The control unit 6 of the vehicle diagnostic device 1 according to this embodiment can be constituted by a computer installed with an operation program (application software). By reading and executing the above program by the computer (for example, the control unit 6), each part of the control unit 6 (the main control unit 61, the equivalent mode generation unit 62, the actual measurement extraction unit 6P (including the total consumption calculation unit 63, etc.), the judgment unit 64, and the prediction unit 65) can be made to operate, and the above-mentioned various processes (each process) can be executed. Such a program is obtained, for example, by downloading from the outside via a network and stored in the program storage unit 23 of the storage unit 2 or the memory in the control unit 6. The above program can also be in the following manner: for example, recorded on a computer-readable recording medium such as a CD-ROM (Compact Disk-Read Only Memory), and the above program is read from the recording medium and stored in the above memory, etc. That is, the program according to this embodiment is a vehicle diagnostic program for causing a computer to execute the vehicle diagnostic method according to this embodiment. In addition, the recording medium according to this embodiment is a computer-readable recording medium on which the above program is recorded.

[0133] [12. Supplementary] Figure 7 The actual driving data during the specified period shown, that is, the actual driving data of the past specified period obtained by the data acquisition unit 3 from the vehicle, is an example of the output data based on the actual driving of the vehicle in the past specified period. In addition, Figure 27 The data of the scatter diagram shown is also an example of the output data based on the actual driving of the vehicle in the past specified period. That is, the output data based on the actual driving of the vehicle in the past specified period can also be the engine output (for example, data representing the relationship between the engine speed and torque).

[0134] The vehicle diagnostic device 1 does not necessarily need to include the judgment unit 64 and the prediction unit 65. For example, the information on the total energy consumption calculated by the total consumption calculation unit 63 can also be sent to an external device, and the determination and prediction of the battery degradation degree of the vehicle can be performed in the external device.

[0135] The timing for diagnosing the battery degradation degree by the vehicle diagnostic device 1 can also be any timing, at regular intervals, the timing for vehicle inspection or OBD vehicle inspection, etc. OBD vehicle inspection means that during the inspection, a scan tool (external fault diagnostic machine) is connected to the vehicle, and the presence of faults and the operating conditions of various devices are read out to check whether various devices are operating normally.

[0136] Near 100% of the SOC, in order to prevent overcharging of the battery, energy regeneration is usually not performed. Therefore, in the area (time period) where regeneration is not performed, the total energy consumption tends to increase. Therefore, it is preferable to calculate the total energy consumption considering the above area. For example, in the calculation of the total energy consumption, data (power consumption) of the above area is not used.

[0137] The power consumption of the heater (such as Figure 4 the PTC heater 105) during cold start is larger than that when maintaining a certain temperature. Therefore, when the difference between the set temperature and the indoor temperature is large, it is preferable not to use the power consumption value of the heat pump as calculation data for driving resistance.

[0138] It is also possible to create a power consumption map of equipment (such as an air conditioner) based on the external air temperature and the room temperature and record it as a design reference value. The power consumption map can be recorded in the data recording device 111 of the vehicle 100 or in the database of the inspection agency.

[0139] It is also possible to calculate the energy consumption based on the heat unit (heat pump, PTC heater 105, etc.), Figure 4 the drive voltage and drive current of the A / C compressor 106 of

[0140] An example in which the vehicle diagnostic device 1 is provided outside the vehicle 100 has been described, but it may also be provided inside the vehicle 100 and communicably connected to the network 100N.

[0141] In the energy consumption described in this embodiment, in addition to power consumption, power consumption rate, fuel consumption (fuel injection amount), fuel consumption rate, or hydrogen consumption, it also includes emissions of specified components (such as CO, CO2, or NOx) in the exhaust gas.

[0142] The vehicle diagnostic device described in this embodiment includes the vehicle diagnostic device described below. That is, the vehicle diagnostic device for diagnosing a vehicle includes: A characteristic data acquisition unit that acquires a plurality of characteristic data included in a specified driving mode of the vehicle; An actual data acquisition unit that acquires the actual driving data of the vehicle in a past specified period and the actual measurement data indicating the actual measurement values of parameters required for vehicle diagnosis during the vehicle driving in the specified period; An equivalent mode generation unit that generates an equivalent driving mode regarded as equivalent to the specified driving mode by intercepting points or intervals similar to the plurality of characteristic data from the actual driving data in the specified period; and The actual measurement extraction unit extracts the actual measurements of each point or each interval included in the equivalent driving pattern from the actual measurement data during the specified period.

[0143] As described above, embodiments of the present invention have been described, but the scope of the present invention is not limited thereto, and it can be implemented with expansion or modification without departing from the gist of the invention. Industrial Applicability

[0144] The present invention can be used for a vehicle diagnostic device that diagnoses a vehicle based on the consumption state of driving energy in the vehicle. Explanation of Reference Numerals:

[0145] 1: Vehicle diagnostic device; 3: Data acquisition unit (characteristic data acquisition unit, actual data acquisition unit, reference consumption amount acquisition unit); 21: Characteristic data storage unit (characteristic data acquisition unit); 22: Reference consumption amount storage unit (reference consumption amount acquisition unit); 62: Equivalent mode generation unit; 63: Total consumption amount calculation unit; 6P: Actual measurement extraction unit; 64: Judgment unit; 65: Prediction unit; 66: Resistance change amount calculation unit (change amount calculation unit); 67: Voltage change amount calculation unit (change amount calculation unit); 70: Change amount calculation unit; 100: Vehicle; 103: HV battery (battery); 111: Data recording device; P1 to Pn: Graphs (characteristic data).

Claims

1. A vehicle diagnostic device that performs vehicle diagnosis, wherein, Comprising: A feature data acquisition unit that acquires a plurality of feature data included in a specified output mode of the vehicle; An actual data acquisition unit that acquires output data based on the actual driving of the vehicle during a past specified period and actual measurement data indicating actual measurement values of parameters required for vehicle diagnosis during the driving of the vehicle during the specified period; An equivalent mode generation unit that generates an equivalent output mode regarded as equivalent to the specified output mode by intercepting points or intervals similar to the plurality of feature data from the output data during the specified period; and An actual measurement value extraction unit that extracts the actual measurement values of each point or each interval included in the equivalent output mode from the actual measurement data during the specified period.

2. The vehicle diagnosis device according to claim 1, wherein The actual measurement data includes actual consumption data representing the energy consumption during the driving of the vehicle during the specified period as the actual measurement value, The actual measurement value extraction unit includes a total consumption calculation unit that calculates the total energy consumption by extracting and summing the energy consumption of each point or each interval included in the equivalent output mode from the actual consumption data during the specified period.

3. The vehicle diagnosis device according to claim 2, wherein The vehicle diagnosis device comprises: A reference consumption acquisition unit that acquires data of the energy consumption of each of the specified output modes in the vehicle as reference energy consumption data; and A judgment unit that judges the state of the vehicle based on the reference energy consumption and the total energy consumption.

4. The vehicle diagnosis device according to claim 3, wherein The actual data acquisition unit acquires data representing the power consumption of the vehicle during driving during the specified period from the vehicle as the actual consumption data, The total consumption calculation unit sums up the power consumption of each point or each interval included in the equivalent output mode based on the actual consumption data to calculate the total energy consumption, The judgment unit judges the degree of deterioration of the battery storing electric power as the state of the vehicle based on the reference energy consumption and the total energy consumption.

5. The vehicle diagnosis device according to claim 4, wherein The reference energy consumption is the consumption of the electric power stored in the battery when the vehicle travels in a specified driving mode as the specified output mode.

6. The vehicle diagnosis device according to claim 4 or 5, wherein The vehicle diagnosis device further comprises a prediction unit that predicts the degree of deterioration or power consumption of the battery of each specified driving mode as the specified output mode at a moment after a specified time has elapsed since the completion of the vehicle based on the degree of deterioration of the battery judged by the judgment unit.

7. The vehicle diagnosis device according to any one of claims 4 to 6, wherein The actual data acquisition unit further acquires data related to the usage state or surrounding environment of the vehicle from the vehicle, The total power consumption calculation unit excludes the power consumption of the battery consumed due to the usage state of the vehicle or the surrounding environment, and calculates the total energy consumption of the battery.

8. The vehicle diagnostic device according to claim 1, wherein the actual measurement data includes actual battery data representing at least one of the current value and voltage value of the battery during the vehicle's travel within the specified period as the actual measurement value, the actual measurement value extraction unit includes a change amount calculation unit, which extracts at least one of the current value and voltage value of the battery for each point or each interval included in the equivalent output mode from the actual battery data during the specified period, and based on the extracted values, obtains the change amount of the internal resistance of the battery from the reference, the change amount of the extracted voltage value from the reference, or the change amount of the extracted current value from the reference, the vehicle diagnostic device further includes a determination unit, which determines the state of the vehicle based on the change amount calculated by the change amount calculation unit.

9. The vehicle diagnostic device according to claim 8, wherein the determination unit determines the state of the vehicle when the temperature of the battery is within a specified temperature range, and when the temperature of the battery deviates from the specified temperature range, corrects the voltage value of the battery to the voltage value at the specified temperature and determines the state of the vehicle.

10. The vehicle diagnostic device according to claim 1, wherein the actual measurement data includes actual emission data representing the emission amount of a specified component included in the exhaust gas during the vehicle's travel within the specified period as the actual measurement value, the actual measurement value extraction unit includes a total emission calculation unit, which totals the emissions for each point or each interval included in the equivalent output mode based on the actual emission data and calculates the total emissions, the vehicle diagnostic device further includes a determination unit, which determines the state of the vehicle based on the total emissions calculated by the total emission calculation unit.

11. The vehicle diagnostic device according to claim 3, wherein the actual data acquisition unit acquires data representing the fuel consumption of the vehicle during travel within the specified period from the vehicle as the actual consumption data, the total consumption calculation unit totals the fuel consumption attached to each point included in the equivalent output mode based on the actual consumption data and calculates the total energy consumption, the determination unit determines the degree of deterioration of the internal combustion engine as the state of the vehicle based on the reference energy consumption and the total energy consumption.

12. The vehicle diagnostic device according to claim 3, wherein the actual data acquisition unit acquires data representing the emission amount of a specified component included in the exhaust gas of the vehicle during travel within the specified period from the vehicle as the actual consumption data, The total consumption calculation unit sums up the emissions associated with each point included in the equivalent output pattern based on the actual consumption data, and calculates the total energy consumption. The determination unit determines the degree of deterioration of the internal combustion engine as the state of the vehicle based on the reference energy consumption and the total energy consumption.

13. The vehicle diagnostic device according to claim 11 or 12, wherein The specified output pattern is a set of points representing the relationship between the engine speed and torque of the internal combustion engine. The equivalent output pattern is a set of points regarded as equivalent to each point included in the specified output pattern.

14. A vehicle diagnostic method, comprising: An equivalent mode generation step of generating an equivalent output pattern regarded as equivalent to the specified output pattern by intercepting points or intervals similar to a plurality of characteristic data included in the specified output pattern of the vehicle from output data of actual driving of the vehicle during a past specified period; and An actual measurement extraction step of extracting the actual measurements of each point or each interval included in the equivalent output pattern from actual measurement data representing the actual measurements of parameters required for vehicle diagnosis during the driving of the vehicle during the specified period.

15. A vehicle diagnostic program, wherein The vehicle diagnostic program causes a computer to execute the vehicle diagnostic method according to claim 14.

16. The vehicle diagnostic device according to any one of claims 1 to 13, wherein The specified output pattern of the vehicle is the specified driving pattern of the vehicle. The output data based on the actual driving is the actual driving data of the vehicle during a past specified period. The equivalent output pattern is a pattern regarded as equivalent to the specified driving pattern.

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