Method for monitoring energy consumption of vehicle, controller and vehicle

Abstract

The invention provides a method for monitoring vehicle energy consumption, a controller and a vehicle, and relates to the technical field of energy consumption monitoring. According to the method, by splitting the first energy consumption related to the vehicle-mounted power consumption equipment and the second energy consumption related to the driving behavior, the limitation that a high energy consumption source is not distinguished in the related technology is broken through, and a foundation is laid for deep attribution analysis when the energy consumption is abnormal. The contribution degree of the performance degradation or power distribution mode of the vehicle-mounted power consumption equipment to the corresponding energy consumption abnormality is quantified in a targeted manner, and the energy consumption abnormality attribution information for fitting the external driving environment is generated based on the first energy consumption and the first contribution degree and / or the second energy consumption and the second contribution degree, so that the core cause behind the high energy consumption can be accurately mined. The method can make up for the defect that only data such as average fuel consumption / average power consumption, residual endurance and high energy consumption are displayed in an isolated manner, so that the root cause of high energy consumption is clear at a glance. Meanwhile, the attribution information is also helpful for the user to accurately formulate an improvement scheme for reducing energy consumption.

Description

Technical Field

[0001] This application relates to the field of energy consumption monitoring technology, and more specifically, to a method, controller, and vehicle for monitoring vehicle energy consumption in the field of energy consumption monitoring technology. Background Technology

[0002] With the continuous advancement of automotive technology and the improvement of people's living standards, the target audience for vehicles is becoming increasingly broad. However, this also brings about a growing number of vehicle-related problems, including the issue of energy consumption monitoring during vehicle operation.

[0003] In related technologies, information indicating abnormal energy consumption is simply displayed on the vehicle's screen in isolation, such as the vehicle's average fuel consumption / average electricity consumption, remaining range, and high energy consumption, lacking in-depth causal analysis. This prevents users from implementing energy-saving improvement measures.

[0004] Therefore, there is an urgent need for a method to monitor vehicle energy consumption in order to pinpoint the root causes of high energy consumption and assist users in developing improvement plans to reduce energy consumption. Summary of the Invention

[0005] This application provides a method, controller, and vehicle for monitoring vehicle energy consumption. The method can accurately pinpoint the root cause of high energy consumption and assist users in developing improvement plans to reduce energy consumption.

[0006] In a first aspect, a method for monitoring vehicle energy consumption is provided. The method includes: when the actual energy consumption of the vehicle is abnormal, determining a first energy consumption generated by the operation of on-board power-consuming equipment and a second energy consumption affected by driving behavior; when the first energy consumption is abnormal, determining a first contribution of the performance degradation degree of the on-board power-consuming equipment to the abnormality of the first energy consumption; and / or, when the second energy consumption is abnormal, determining a second contribution of the power distribution mode to the abnormality of the second energy consumption based on the vehicle's target power distribution mode and current power distribution mode; and generating attribution information for the abnormal energy consumption of the vehicle under external driving conditions based on the first energy consumption and the first contribution, and / or, the second energy consumption and the second contribution.

[0007] In the technical solution, the first energy consumption related to the vehicle-mounted power-consuming device and the second energy consumption related to the driving behavior are split, breaking the limitation of not distinguishing the high energy consumption source in the related art, and laying a foundation for deep attribution analysis when the energy consumption is abnormal. Further, the contribution of the performance degradation of the vehicle-mounted power-consuming device or the power distribution mode to the corresponding energy consumption abnormality is quantified, and the energy consumption abnormality attribution information that fits the external driving environment is generated based on the first energy consumption and the first contribution, and / or the second energy consumption and the second contribution, which can accurately explore the core inducement behind the high energy consumption. For example, is the high energy consumption caused by the running parameters of the vehicle-mounted power-consuming device itself or affected by the performance degradation, and / or is the high energy consumption caused by the driving behavior or affected by the power distribution mode. The scheme can make up for the deficiency of only displaying the average fuel consumption / average power consumption, residual endurance, and energy consumption deviation, etc. in isolation, so that the root cause of high energy consumption is clear at a glance. At the same time, the attribution information of the energy consumption abnormality is also helpful for the user to accurately formulate an improvement scheme for reducing energy consumption. In addition, for any vehicle type (fuel vehicle, electric vehicle, or hybrid vehicle), the above scheme can generate the attribution information of the energy consumption abnormality of the vehicle in the external driving environment.

[0008] In combination with the first aspect, in some possible implementation manners, the method for determining that the actual energy consumption of the vehicle is abnormal includes: obtaining a vehicle type of the vehicle and environment information of the external driving environment; determining a benchmark energy consumption of the vehicle when driving based on the vehicle type and the environment information; and determining that the actual energy consumption is abnormal in a case where an energy consumption deviation between the actual energy consumption and the benchmark energy consumption is greater than a preset deviation.

[0009] In the technical solution, the vehicle type and the external driving environment information (which can include road condition environment and weather environment) are obtained, which provides an adaptive premise for determining the benchmark energy consumption and avoids the determination deviation caused by a universal standard. The benchmark energy consumption of the vehicle when driving is determined based on these key factors, which can establish a reasonable comparison basis that fits the actual scenario. Further, whether the actual energy consumption is abnormal is explicitly defined by whether the energy consumption deviation between the actual energy consumption and the benchmark energy consumption is greater than the preset deviation. The steps are progressive, which can provide a scientific and rigorous energy consumption abnormality determination logic and ensure the accuracy of the abnormality determination. At the same time, it also provides a reliable premise for subsequent attribution analysis and avoids invalid analysis. In addition, in the scheme, the actual energy consumption is determined to be abnormal when the actual energy consumption is much greater than the benchmark energy consumption corresponding to the current road condition and the current weather, which considers the influence of the actual external environment on the energy consumption, which exists for any vehicle. This also makes the attribution information of the scheme pay more attention to the influence of the running of the vehicle-mounted power-consuming device and the driving behavior on the actual energy consumption abnormality.

[0010] In some possible implementation manners, in combination with the first aspect and the foregoing implementation manners, before the first energy consumption generated by the running of the vehicle-mounted power-consuming device and the second energy consumption affected by the driving behavior are determined, the method further includes: determining whether a device state of the vehicle is in a preset state, the preset state being used to indicate that a target hardware device in the vehicle is not abnormal, the target hardware device being a device that increases energy consumption when running in a fault condition; and determining the first energy consumption generated by the running of the vehicle-mounted power-consuming device and the second energy consumption affected by the driving behavior includes: determining the first energy consumption and the second energy consumption in a case where the device state is in the preset state.

[0011] In the foregoing technical solution, the determination of whether the target hardware device of the vehicle is in the preset state without abnormality can effectively exclude the interference of hardware faults on actual energy consumption abnormalities. Further, the determination of the first energy consumption and the second energy consumption can set rigorous triggering conditions for the attribution analysis of energy consumption abnormalities, and ensure that the subsequent attribution analysis focuses on the two core factors of the running of the vehicle-mounted power-consuming device and the driving behavior. Meanwhile, the foregoing solution can further improve the pertinence of an improvement scheme for reducing energy consumption formulated by a user, and better solve the limitations in the related art.

[0012] In some possible implementation manners, in combination with the first aspect and the foregoing implementation manners, the determination of the first contribution degree of the performance degradation degree of the vehicle-mounted power-consuming device to the first energy consumption abnormality includes: obtaining a reference energy consumption generated by the running of the vehicle-mounted power-consuming device without performance degradation, the reference energy consumption and the first energy consumption being identical in the running state of the vehicle-mounted power-consuming device and the vehicle state of the vehicle when the reference energy consumption and the first energy consumption are determined; determining a deviation amplitude of the first energy consumption relative to the reference energy consumption; and determining the first contribution degree based on the deviation amplitude, the deviation amplitude being positively correlated with the first contribution degree.

[0013] In the foregoing technical solution, the reference energy consumption identical to the running state of the vehicle-mounted power-consuming device without performance degradation and the vehicle state when the first energy consumption is determined is obtained, which can accurately quantify the influence of performance degradation, provide an accurate reference benchmark, and avoid attribution analysis deviation caused by the state difference of the vehicle-mounted power-consuming device and the vehicle. The determination of the first contribution degree based on the deviation amplitude of the first energy consumption relative to the reference energy consumption can intuitively reflect the energy consumption increment caused by performance degradation, so that the influence degree of performance degradation on the first energy consumption abnormality can be quantified. That is, the solution provides a scientific and rigorous implementation path for the determination of the first contribution degree, can make the attribution analysis of the energy consumption abnormality caused by the running of the vehicle-mounted power-consuming device more credible, and help a user to clearly grasp the energy consumption influence caused by performance degradation and formulate a more targeted energy reduction scheme.

[0014] In a possible implementation manner, the second contribution degree of the power distribution mode to the second energy consumption anomaly is determined based on a deviation between the current power distribution mode and the target power distribution mode, and the deviation is positively correlated with the third contribution degree.

[0015] In the technical solution, the third contribution degree is determined based on the deviation between the current power distribution mode and the target power distribution mode, and the greater the deviation, the greater the contribution of the power distribution mode to the second energy consumption anomaly. This is because the power distribution mode mismatch amplifies the energy consumption generated by the driving behavior. The fourth contribution degree is determined by judging whether the driving behavior matches the current power distribution mode, and when the driving behavior matches the current power distribution mode, the contribution of the power distribution mode to the second energy consumption anomaly is small. This is because the driving behavior mismatch amplifies the energy consumption generated by the driving behavior. The second contribution degree is obtained based on the preset weights, which can give differentiated weights of the core influence dimension and be more suitable for actual vehicle scenarios. The scheme provides a hierarchical quantization and logically rigorous implementation path for determining the second contribution degree, so that the influence degree of the power distribution mode on the energy consumption anomaly caused by the driving behavior is more accurate, and the attribution analysis system can be improved. At the same time, it can help users to clearly distinguish the influence of mode adaptation and behavior matching on the energy consumption anomaly, and further improve the pertinence of the energy consumption reduction scheme.

[0016] In a possible implementation manner, the first preset weight and the second preset weight are determined as follows. In a case where the vehicle is a fuel vehicle, the first preset weight is determined as a first weight, and the second preset weight is determined as a second weight, the first weight being smaller than the second weight. In a case where the vehicle is a hybrid vehicle or an electric vehicle, the first preset weight is determined as a third weight, and the second preset weight is determined as a fourth weight, the third weight being greater than the fourth weight.

[0017] In the technical solution, the first preset weight and the second preset weight are set differentially based on the vehicle type. Specifically, the first preset weight given to the fuel vehicle is less than the second preset weight. This is because the power source of the fuel vehicle is only the engine, and the sensitivity of its energy consumption to driving behavior is much higher than the power distribution mode itself. Whether the driving behavior matches the current power distribution mode directly determines whether the engine is in the economic speed range, and this matching deviation has a more significant impact on energy consumption. The first preset weight given to the hybrid vehicle or electric vehicle is greater than the second preset weight. This is because the power distribution mode of the hybrid vehicle and electric vehicle is the core of energy consumption optimization, and the influence of driving behavior can be flexibly buffered by the power distribution mode. The different weight settings in this scheme can adapt to the differences in the logic of the power characteristics and energy consumption of different vehicle types, avoid the contribution determination deviation caused by uniform weight, further improve the accuracy of determining the second contribution, and help obtain more accurate attribution information.

[0018] In combination with the first aspect and the above implementation manners, in some possible implementation manners, based on the first energy consumption and the first contribution, and / or, the second energy consumption and the second contribution, the attribution information of the energy consumption anomaly of the vehicle in the external driving environment is generated, including: in a case where the first contribution is greater than a first preset value, determining that the attribution information includes first attribution information, the first attribution information indicating that the performance degradation is severe and causes the energy consumption anomaly; in a case where the first contribution is less than or equal to the first preset value, determining that the attribution information includes second attribution information, the second attribution information indicating that the energy consumption anomaly is related to the operating parameter of the vehicle-mounted power consumption device; and / or, in a case where the second contribution is greater than a second preset value, determining that the attribution information includes third attribution information, the third attribution information indicating that the energy consumption anomaly is related to the power distribution mode; in a case where the second contribution is less than or equal to the second preset value, determining that the attribution information includes fourth attribution information, the fourth attribution information indicating that the driving behavior causes the energy consumption anomaly.

[0019] In the technical solution, the first contribution is compared with the first preset value, which can accurately distinguish whether the energy consumption anomaly of the vehicle-mounted power consumption device is caused by severe performance degradation or operating parameters, and clearly identify the core cause of the energy consumption anomaly. The second contribution is compared with the second preset value, which can define whether the driving behavior related energy consumption anomaly is caused by the power distribution mode or the driving behavior itself, and comprehensively cover the core abnormal causes. This scheme can provide a concrete and practical attribution determination path, avoiding the generation of ambiguous attribution information. This can help users quickly locate the problem core and further assist users in developing targeted and practical energy reduction schemes, effectively addressing the lack of deep causal analysis in related technologies.

[0020] In a possible implementation manner of the first aspect and the above implementation manners, after the attribution information of the abnormal energy consumption of the vehicle in the external driving environment is generated, the method further includes: generating driving suggestion information based on the attribution information, a vehicle type of the vehicle, and environment information of the external driving environment; splitting the driving suggestion information according to a recommendation priority to obtain multiple groups of suggestion information; and outputting each group of suggestion information according to the recommendation priority.

[0021] In the above technical solution, the driving suggestion information is generated based on the attribution information, the vehicle type, and the environment information of the external driving environment, which converts the abstract attribution into an operable guidance that fits the actual scenario. The driving suggestion information is split according to the recommendation priority to obtain multiple groups of suggestion information, which can help the user to sort out the emergency suggestion information, the regular suggestion information, and the long-term suggestion information, and avoid information clutter. Further, each group of suggestion information is output according to the recommendation priority, which can facilitate the user to preferentially perform a high-value energy consumption reduction scheme. The above solution takes the accurate attribution information in the foregoing solution as a link, and builds a bridge from deep attribution analysis to actual energy consumption reduction action, so that the user not only knows the root cause of the abnormal energy consumption, but also obtains a hierarchical and ordered energy consumption reduction scheme. Meanwhile, the landing and practicality of the energy consumption reduction scheme can be improved.

[0022] In a second aspect, a device for monitoring energy consumption of a vehicle is provided. The device includes a determination module configured to: determine a first energy consumption generated by running a vehicle-mounted power-consuming device and a second energy consumption affected by a driving behavior when actual energy consumption of the vehicle is abnormal; determine a first contribution degree of a performance degradation degree of the vehicle-mounted power-consuming device to the abnormal first energy consumption when the first energy consumption is abnormal; and / or determine a second contribution degree of a power distribution mode to the abnormal second energy consumption when the second energy consumption is abnormal based on a target power distribution mode and a current power distribution mode of the vehicle; and a generation module configured to generate attribution information of the abnormal energy consumption of the vehicle in an external driving environment based on the first energy consumption and the first contribution degree, and / or the second energy consumption and the second contribution degree.

[0023] In a third aspect, a controller is provided. The controller includes a storage module and a processing module. The storage module is configured to store executable program code, and the processing module is configured to call and run the executable program code from the storage module, so that the controller performs the method in the first aspect or any possible implementation manner of the first aspect.

[0024] In a fourth aspect, a vehicle is provided. The vehicle includes a storage and a processor. The storage is configured to store executable program code, and the processor is configured to call and run the executable program code from the storage, so that the vehicle performs the method in the first aspect or any possible implementation manner of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 This is a schematic diagram of a scenario for monitoring vehicle energy consumption provided in an embodiment of this application; Figure 2 This is a system architecture diagram for vehicle energy consumption analysis provided in an embodiment of this application; Figure 3 This is a schematic flowchart illustrating a method for monitoring vehicle energy consumption provided in an embodiment of this application; Figure 4 This is another system architecture diagram for vehicle energy consumption analysis provided in the embodiments of this application; Figure 5 This is a schematic diagram of the structure of a device for monitoring vehicle energy consumption provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a controller provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application. Detailed Implementation

[0026] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0027] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0028] Figure 1 This is a schematic diagram of a scenario for monitoring vehicle energy consumption provided in an embodiment of this application.

[0029] When a vehicle experiences abnormal energy consumption, relevant technologies typically provide a warning through color changes of indicator lights on the dashboard and / or by displaying text on the dashboard.

[0030] Specifically, Example 1 is given below, such as Figure 1 The fuel-powered vehicle A shown in (a) will receive the following alert when its fuel consumption is abnormal: the fuel warning light will illuminate, indicating "Low fuel, refueling required." Example 2 is given below, such as... Figure 1The reminding mode of the electric vehicle B shown in (b) in the figure when the energy consumption is abnormal is that the color of the power indicator light changes very deeply, indicating that the remaining power is less than 10% of the power, and prompting "the power is very low, please charge immediately". The following example 3 is given as Figure 1 The reminding mode of the hybrid vehicle C shown in (c) in the figure when the energy consumption is abnormal is that the color of the power indicator light changes very deeply, prompting "the power is very low", and prompting "there is more remaining oil, and the engine can be started to drive the vehicle". That is, for the above different types of vehicles, the related art only displays the indication information when the energy consumption is abnormal on the vehicle display screen, only prompts the user that the energy consumption is abnormal, or gives simple suggestion information, and does not give the attribution information when the energy consumption is abnormal.

[0031] In order to solve the problems in the related art, the present application provides a method for monitoring vehicle energy consumption. When the actual energy consumption of the vehicle is abnormal, the core cause is deeply analyzed to assist the user in formulating an improvement scheme for reducing energy consumption.

[0032] Before introducing the method for monitoring vehicle energy consumption in the present application, the present application introduces Figure 2 the system architecture diagram for vehicle energy consumption analysis, and the above method for monitoring vehicle energy consumption relies on the system architecture diagram.

[0033] As shown in Figure 2 , the system architecture for vehicle energy consumption analysis can be divided into a data collection layer, an analysis calculation layer and a suggestion output layer. Among them, the data collection layer is used to collect all data related to energy consumption, including data quantifying energy consumption (such as fuel consumption and / or power consumption) and data affecting energy consumption (such as driving behavior data, power distribution mode, running parameters and performance decay parameters of vehicle-mounted power-consuming equipment, environmental temperature, road conditions and the state of the target hardware device in the vehicle (whether the data is faulty)) and the like. The analysis calculation layer is used to analyze whether the actual energy consumption of the vehicle is abnormal through all the above data, and when the actual energy consumption is abnormal, the attribution information of the vehicle energy consumption abnormality in the external driving environment is generated through the analysis rules and all the above data. The suggestion output layer is used to generate driving suggestion information based on the attribution information and the environmental information of the external driving environment, and output the driving suggestion information.

[0034] The method for monitoring vehicle energy consumption in the present application will be described below in combination with Figure 2 and Figure 3 Figure 3 is a schematic flowchart of the method for monitoring vehicle energy consumption provided by the embodiments of the present application.

[0035] It should be understood that the method for monitoring vehicle energy consumption provided by the embodiments of the present application can be applied to vehicles (such as vehicle A).

[0036] ​For example, as Figure 3 As shown in FIG. 3, the method 300 includes steps 301-303.

[0037] In step 301, when the actual energy consumption of the vehicle is abnormal, the first energy consumption generated by the running of the on-board power-consuming device and the second energy consumption affected by the driving behavior are determined.

[0038] It should be understood that the vehicle in step 301 described above can be any one of a fuel vehicle, an electric vehicle and a hybrid vehicle. When the vehicle is a fuel vehicle, the actual energy consumption described above is the actual fuel consumption; when the vehicle is an electric vehicle, the actual energy consumption described above is the actual electric consumption; and when the vehicle is a hybrid vehicle, the actual energy consumption described above is the actual fuel consumption and / or the actual electric consumption.

[0039] It should also be understood that the on-board power-consuming device in step 301 described above refers to a device that is independent of the driving behavior of the vehicle and consumes energy when running, such as devices in the air conditioning system (including air blower, defroster and compressor, etc.), cabin electrical devices (including seat heating device, seat ventilation device, audio, steering wheel heating device and atmosphere lamp, etc.), vehicle body accessories (including vehicle lights, windshield wiper motor, window lifting motor and rearview mirror heating device, etc.) and other auxiliary devices (including dashcam, air purifier, etc.). In addition, the on-board power-consuming device does not include devices related to vehicle driving, such as driving motor.

[0040] Further, the driving behavior in step 301 described above refers to the driving behavior that controls the state of the vehicle, including power control behavior (pedaling behavior of the accelerator pedal), mode control behavior (adjusting the power distribution mode from the current energy-saving mode to the power-enhanced mode) and trajectory control behavior (lane changing behavior), etc.

[0041] In addition, the actual energy consumption in step 301 described above is abnormal, which means that the actual energy consumption is too high.

[0042] The determination process of “abnormal actual energy consumption of the vehicle” is given as follows.

[0043] In one possible implementation, the method for determining the abnormal actual energy consumption of the vehicle in step 301 includes: obtaining the vehicle type of the vehicle and the environment information of the external driving environment; determining the reference energy consumption when the vehicle is running based on the vehicle type and the environment information; and determining that the actual energy consumption is abnormal when the energy consumption deviation between the actual energy consumption and the reference energy consumption is greater than a preset deviation.

[0044] It should be understood that the vehicle type in the above scheme refers to the type classified according to the power source and driving mode of the vehicle, including a fuel vehicle, an electric vehicle, and a hybrid vehicle. The power source of the fuel vehicle is fuel, and the driving mode is driving through an engine, which generates power by using fuel to drive the vehicle to travel. The power source of the electric vehicle is electric energy, and the driving mode is driving through a drive motor, which relies on the electric energy stored in the on-board battery, and the drive motor converts the electric energy into kinetic energy to drive the vehicle to travel. The power source of the hybrid vehicle is fuel and electric energy, and the driving mode is driving through the drive motor alone, driving through the engine alone, or driving through the drive motor and the engine in a cooperative manner.

[0045] It should also be understood that the external driving environment in the above scheme refers to the driving environment other than the vehicle itself, including a road condition environment and a weather environment. Optionally, the environment information of the road condition environment can include a climbing road condition, a congested road condition, and a muddy road condition. Optionally, the environment information of the weather environment can include a high-temperature environment, a heavy snow environment, and a heavy rain environment.

[0046] In the above technical scheme, the vehicle type and the external driving environment information (which can include the road condition environment and the weather environment) are obtained, which provides an adaptive premise for determining the reference energy consumption and avoids the determination deviation caused by the universal standard. The reference energy consumption of the vehicle during driving is determined based on these key factors, which can establish a reasonable comparison basis that fits the actual scene. Further, whether the actual energy consumption is abnormal is explicitly defined by whether the energy consumption deviation between the actual energy consumption and the reference energy consumption is greater than a preset deviation. The above steps are progressive, which can provide a scientific and rigorous energy consumption abnormality determination logic to ensure the accuracy of the abnormality determination. At the same time, it also provides a reliable premise for subsequent attribution analysis, avoiding invalid analysis. In addition, in the scheme, the actual energy consumption is determined to be abnormal when the actual energy consumption is much greater than the reference energy consumption corresponding to the current road condition and the current weather, which considers the influence of the actual external environment on the energy consumption, which exists for any vehicle. This also makes the attribution information of the scheme pay more attention to the influence of the running of the on-board power-consuming equipment and the driving behavior on the abnormality of the actual energy consumption.

[0047] In some embodiments, the external driving environment includes a road condition environment and a weather environment, the environment information of the road condition environment includes a current road condition, the environment information of the weather environment includes a current weather, and the reference energy consumption of the vehicle when driving is determined based on the vehicle type and the environment information, including: comparing the vehicle type with a plurality of sample vehicle types in a reference table, determining a target vehicle type matching the vehicle type from the plurality of sample vehicle types; comparing the current road condition with a plurality of sample road conditions corresponding to the target vehicle type in the reference table, determining a target road condition matching the current road condition from the plurality of sample road conditions; comparing the current weather with a plurality of sample weathers corresponding to the target road condition in the reference table, determining a target weather matching the current weather from the plurality of sample weathers; and determining the energy consumption corresponding to the target weather in the reference table as the reference energy consumption of the vehicle when driving.

[0048] It is worth noting here that one sample vehicle type in the above-mentioned reference table corresponds to one sample road condition and one sample weather. The above-mentioned reference table can be understood as the sum of the energy consumption generated by the vehicle in the standard driving state and the on-board power-consuming equipment in the standard operating state under the sample weather and the sample road condition (i.e., the reference energy consumption).

[0049] Wherein, the standard driving state is affected by the sample road condition, and the standard operating state is affected by the sample weather. Optionally, when the sample road condition is a congested road condition, the standard driving state is uniform driving at a speed less than a preset speed and infrequent start-stop; when the sample weather is sunny and the temperature is 30°C, the operating temperature of the on-board air conditioner is 25°C. Wherein, when determining the reference energy consumption, the influence of the performance decay and the fault loss of the on-board power-consuming equipment is not considered.

[0050] The determination process of the "first energy consumption and the second energy consumption" is as follows.

[0051] In some embodiments, the determining, in step 301, the first energy consumption generated by the running of the vehicle-mounted power-consuming device and the second energy consumption affected by the driving behavior, comprises: for any running power-consuming device in the vehicle, determining the energy consumption generated by the power-consuming device as the product of the actual power when the power-consuming device is running and the working time length; determining the sum of the energy consumption generated by each power-consuming device as the first energy consumption; obtaining the first total energy consumption of the vehicle at a first time and the second total energy consumption of the vehicle at a second time, the first time being a time before the driving behavior is performed, and the second time being a time after the driving behavior is performed; determining whether a target event occurs between the first time and the second time, the target event being an event that can increase energy consumption and is irrelevant to the driving behavior; in the case that no target event occurs between the first time and the second time, determining the second energy consumption as the difference between the second total energy consumption and the first total energy consumption; in the case that a target event occurs between the first time and the second time, determining a third total energy consumption generated by the target event; obtaining the second energy consumption by subtracting the third total energy consumption from the difference between the second total energy consumption and the first total energy consumption.

[0052] It should be understood that the above-mentioned first time can be regarded as a time when the driving behavior is not performed and is about to be performed. The above-mentioned second time can be regarded as a time when the driving behavior is just performed.

[0053] Optionally, the target event includes an event of running of the vehicle-mounted power-consuming device, a power adjustment event of the engine / drive motor, etc.

[0054] In a possible implementation, before the determining, in step 301, the first energy consumption generated by the running of the vehicle-mounted power-consuming device and the second energy consumption affected by the driving behavior, the method 300 further comprises: determining whether a device state of the vehicle is in a preset state, the preset state being used to indicate that a target hardware device in the vehicle does not fail, the target hardware device being a device that increases energy consumption when running in a failure case; and the determining, in step 301, the first energy consumption generated by the running of the vehicle-mounted power-consuming device and the second energy consumption affected by the driving behavior comprises: in the case that the device state is in the preset state, determining the first energy consumption and the second energy consumption.

[0055] It should be understood that in the above-mentioned scheme, the influence of the target hardware device exception is not considered when the first energy consumption and the second energy consumption are determined. Optionally, the target hardware device exception includes engine carbon deposition and tire pressure exception. In addition, performance degradation does not belong to failure, which is natural loss or aging loss after normal use, and is an irreversible phenomenon that the performance of the target hardware device naturally degrades with use time after long-term use.

[0056] In the technical solution, the target hardware device of the vehicle is determined to be in the preset state, which can effectively exclude the interference of hardware failure on actual energy consumption failure. Further, the first energy consumption and the second energy consumption are determined, which can set strict triggering conditions for the attribution analysis of energy consumption anomalies, and ensure that the subsequent attribution analysis focuses on the two core factors of vehicle power consumption device operation and driving behavior. At the same time, the above scheme can further improve the pertinence of the user's improvement scheme for reducing energy consumption, and better solve the limitations in the related art.

[0057] In some embodiments, after determining whether the device state of the vehicle is in the preset state, the method 300 further includes: in the case that the device state is not in the preset state, determining that the attribution information includes fifth attribution information, and the fifth attribution information includes a failure of the target hardware device affecting energy consumption.

[0058] Step 302, in the case that the first energy consumption is abnormal, determining a first contribution degree of the performance degradation degree of the vehicle power consumption device to the first energy consumption being abnormal; and / or, in the case that the second energy consumption is abnormal, determining a second contribution degree of the power distribution mode to the second energy consumption being abnormal based on the target power distribution mode and the current power distribution mode of the vehicle.

[0059] It should be understood that the first energy consumption being abnormal in step 302 above refers to the first energy consumption being too high, greater than the first preset energy consumption; and the second energy consumption being abnormal refers to the second energy consumption being too high, greater than the second preset energy consumption.

[0060] It should also be understood that in step 302 above, the performance degradation degree refers to the degree of natural degradation of the performance of the vehicle power consumption device after normal use, i.e., not to the level of failure. For example, when the vehicle power consumption device is a vehicle air conditioner, the decrease in the working efficiency of the air conditioner compressor in the vehicle air conditioner is a performance degradation. After the performance degradation of the vehicle power consumption device, the working efficiency is reduced, and the vehicle usually increases the current / power output to maintain performance, thereby increasing energy consumption. The greater the performance degradation degree, the greater the contribution degree to the first energy consumption being abnormal.

[0061] It should also be understood that in step 302 above, the power distribution mode refers to the power distribution rule of the vehicle to the power source, and the target power distribution mode refers to the optimal power distribution mode that should be taken when the vehicle is running under the current external driving environment. Under the target power distribution mode, the energy consumption of the vehicle running is the lowest.

[0062] Wherein, when the vehicle is running, if the current power distribution mode deviates from the target power distribution mode, the power source will run in a non-economic interval. For example, the target power distribution mode is the energy saving mode (low engine speed), and the current power distribution mode is the power enhancement mode (high engine speed), even if the driving behavior is reasonable (constant speed driving), the engine will generate extra energy consumption because the speed is too high. Conversely, the target power distribution mode is the power enhancement mode, and the current power distribution mode is the energy saving mode, which will also cause the vehicle to be forced to pull high power due to insufficient power, which also increases energy consumption. The more the current power distribution mode deviates from the target power distribution mode, the greater the contribution to the abnormality of the second energy consumption.

[0063] In addition, generally, when the vehicle is running, the current driving behavior matches the current power distribution mode, but the driving demand may change temporarily. When the above driving behavior matches the current power distribution mode, the engine / drive motor runs in the economic interval, and the energy consumption is minimized. When they do not match, the power source is forced to deviate from the economic interval: for example, the energy saving mode encounters sudden acceleration behavior, and the engine / drive motor needs to output power overload, the energy conversion efficiency decreases, further increasing energy consumption. For example, the energy consumption of constant speed behavior in sports mode is higher than that in energy saving mode. When the driving behavior does not match the current power distribution mode, the contribution to the abnormality of the second energy consumption is large.

[0064] In a possible implementation, the determination of the first contribution of the performance degradation degree of the vehicle-mounted power consumption device to the abnormality of the first energy consumption in step 302 comprises: obtaining a reference energy consumption generated by the vehicle-mounted power consumption device running without performance degradation, the reference energy consumption and the first energy consumption being in the same running state of the vehicle-mounted power consumption device and the same vehicle state of the vehicle when the determination is made; determining the deviation amplitude of the first energy consumption relative to the reference energy consumption; and determining the first contribution based on the deviation amplitude, the deviation amplitude being positively correlated with the first contribution.

[0065] It should be understood that the reference energy consumption generated by the vehicle-mounted power consumption device running without performance degradation in the above scheme refers to the reference energy consumption generated by the vehicle-mounted power consumption device running for less than a preset time. Alternatively, the preset time is 7 days. The running state can be characterized by running parameters, including working mode, running time, and adjustment parameters. The vehicle state includes the state of the vehicle itself and the state of the environment.

[0066] In the technical solution, the reference energy consumption that is consistent with the running state of the vehicle-mounted power consumption device and the state of the vehicle without performance attenuation is obtained to determine the first energy consumption, which can accurately quantify the influence of performance attenuation, provide an accurate reference, and avoid attribution analysis deviation caused by the state difference of the vehicle-mounted power consumption device and the vehicle. The first contribution degree is determined based on the deviation amplitude of the first energy consumption relative to the reference energy consumption, which can intuitively reflect the energy consumption increment caused by performance attenuation, so that the influence degree of performance attenuation on the first energy consumption anomaly can be quantified. That is, the scheme provides a scientific and rigorous implementation path for determining the first contribution degree, which can make the attribution analysis of the energy consumption anomaly caused by the running of the vehicle-mounted power consumption device more credible, and help the user to clearly understand the energy consumption influence caused by performance attenuation and formulate more targeted energy reduction schemes.

[0067] In some embodiments, determining the deviation amplitude of the first energy consumption relative to the reference energy consumption includes: determining the difference between the first energy consumption and the reference energy consumption as an energy consumption difference; and determining the ratio between the energy consumption difference and the reference energy consumption as the deviation amplitude.

[0068] In some embodiments, determining the first contribution degree based on the deviation amplitude includes: determining the deviation amplitude as the first contribution degree; or determining the product between the deviation amplitude and a preset reduction coefficient as the first contribution degree.

[0069] It should be understood that the reduction coefficient in the above scheme refers to a calibration factor when the deviation amplitude is converted into the first contribution degree, and the essence is a reasonable conversion of the deviation amplitude to ensure that the first contribution degree is not overestimated or underestimated. Optionally, the reduction coefficient is 0.8.

[0070] In a possible implementation, in step 302, determining the second contribution degree of the power distribution mode when the second energy consumption is abnormal based on the target power distribution mode and the current power distribution mode of the vehicle includes: determining a third contribution degree based on the deviation between the current power distribution mode and the target power distribution mode, the deviation being positively correlated with the third contribution degree; determining a fourth contribution degree based on whether the driving behavior matches the current power distribution mode; and determining the second contribution degree based on the first preset weight and the second preset weight, the third contribution degree and the fourth contribution degree.

[0071] It should be understood that there are multiple power distribution modes that can be adopted by the vehicle, and the multiple power distribution modes can be sorted according to the provided power size (peak power or power response speed). Optionally, for a hybrid vehicle, the multiple power distribution modes include a sport enhancement mode, a standard mode, an energy saving mode, and a pure electric priority mode.

[0072] In the technical solution, the third contribution degree is determined based on the deviation between the current power distribution mode and the target power distribution mode. The greater the deviation, the greater the contribution of the power distribution mode to the second energy consumption abnormal event. This is because the mismatch between the power distribution mode amplifies the energy consumption caused by the driving behavior: even if the driving behavior itself is reasonable (such as normal acceleration), if the current power distribution mode is the energy-saving mode and the target power distribution mode is the power-enhanced mode, the vehicle needs to compensate for the defects caused by the mismatch between the power distribution modes by outputting excess power, thereby increasing energy consumption. By determining the fourth contribution degree by judging whether the driving behavior matches the current power distribution mode, the contribution of the power distribution mode to the second energy consumption abnormal event is small when the driving behavior matches the current power distribution mode. This is because the mismatch between the driving behavior and the current power distribution mode amplifies the energy consumption caused by the driving behavior: when the two do not match, the current power distribution mode cannot provide efficient power support for the driving behavior, and the vehicle needs to output additional power to convert the current power distribution mode into a power distribution mode that matches the driving behavior, thereby causing further increase in energy consumption. The second contribution degree is obtained by fusing the two based on a preset weight, which can give different weights to the core influence dimensions and be more suitable for actual vehicle scenarios. This scheme provides a hierarchical quantization and logically rigorous implementation path for determining the second contribution degree, making the influence of the power distribution mode on the energy consumption abnormality caused by the driving behavior more accurate, and improving the attribution analysis system. At the same time, it can help users to clearly distinguish the influence of mode adaptation and behavior matching on energy consumption abnormality, and further improve the pertinence of the energy reduction scheme.

[0073] In some embodiments, before determining the third contribution degree based on the deviation between the current power distribution mode and the target power distribution mode, the method 300 further includes: obtaining a plurality of power distribution modes, the plurality of power distribution modes being obtained after being sorted according to the available power; and the method for determining the deviation between the current power distribution mode and the target power distribution mode includes: determining a first power distribution mode matching the current power distribution mode and a second power distribution mode matching the target power distribution mode from the plurality of power distribution modes; and determining the number of mode intervals between the first power distribution mode and the second power distribution mode as the deviation between the current power distribution mode and the target power distribution mode.

[0074] It should be understood that the greater the number of mode intervals, the greater the third contribution degree.

[0075] In some embodiments, the deviation is the number of mode intervals between the power distribution modes, and determining the third contribution degree based on the deviation between the current power distribution mode and the target power distribution mode includes: determining the product of the number of mode intervals between the current power distribution mode and the target power distribution mode and a base coefficient as the third contribution degree.

[0076] In some embodiments, the fourth contribution degree is determined based on whether the driving behavior matches the current power distribution mode, including: in the case that the driving behavior matches the current power distribution mode, the fourth contribution degree is determined as a third preset value; in the case that the driving behavior does not match the current power distribution mode and the current power distribution mode can meet the power demand corresponding to the driving behavior, the fourth contribution degree is determined as a fourth preset value; in the case that the driving behavior does not match the current power distribution mode and the current power distribution mode cannot meet the power demand corresponding to the driving behavior, the fourth contribution degree is determined as a fifth preset value; the third preset value is less than the fourth preset value, and the fourth preset value is less than the fifth preset value.

[0077] In a possible implementation manner, the determination method of the first preset weight and the second preset weight includes: in the case that the vehicle is a fuel vehicle, the first preset weight is determined as a first weight, and the second preset weight is determined as a second weight, the first weight being less than the second weight; in the case that the vehicle is a hybrid vehicle or an electric vehicle, the first preset weight is determined as a third weight, and the second preset weight is determined as a fourth weight, the third weight being greater than the fourth weight.

[0078] It should be understood that in the above scheme, the sum of the first weight and the second weight is a preset weight, the preset weight is 1, and the sum of the third weight and the fourth weight is also a preset weight.

[0079] In the above technical scheme, the first preset weight and the second preset weight are differentiated based on the vehicle type. Specifically, the first preset weight given to the fuel vehicle is less than the second preset weight. This is because the power source of the fuel vehicle is only the engine, and the energy consumption is much more sensitive to the driving behavior than the power distribution mode itself. Whether the driving behavior matches the current power distribution mode directly determines whether the engine is in the economic speed interval. The influence of this matching deviation on energy consumption is more significant, and therefore, the second preset weight is higher. The first preset weight given to the hybrid vehicle or the electric vehicle is greater than the second preset weight. This is because the power distribution mode of the hybrid vehicle and the electric vehicle is the core of energy consumption optimization. The oil-electricity coordination strategy of the hybrid vehicle and the power output and energy recovery strategy of the electric vehicle directly determine the energy utilization efficiency. The deviation between the power distribution modes will cause a substantial increase in energy consumption, and the influence of the driving behavior can be flexibly buffered by the power distribution mode, and therefore, the first preset weight is higher. The different weight settings in this scheme can adapt to the differences in the existence of the power characteristics and the energy consumption influence logic of different vehicle models, avoid the determination deviation of the contribution degree caused by the unified weight, further improve the accuracy of the determination of the second contribution degree, and help to obtain more accurate attribution information.

[0080] Step 303, based on the first energy consumption and the first contribution degree, and / or, the second energy consumption and the second contribution degree, generate the attribution information of the abnormal energy consumption of the vehicle in the external driving environment.

[0081] It should be understood that the above step 303 describes that the attribution information of the abnormal energy consumption of the vehicle in the external driving environment is generated based on the first energy consumption and the first contribution degree (triggered when the first energy consumption is abnormal), and / or, the second energy consumption and the second contribution degree (triggered when the second energy consumption is abnormal).

[0082] It should also be understood that the attribution information in the above step 303 refers to the reason information of the actual energy consumption abnormality of the vehicle in the external driving environment, and clearly indicates the influencing factors of the energy consumption abnormality.

[0083] In one possible implementation, step 303 includes: in the case that the first contribution degree is greater than a first preset value, determining that the attribution information includes first attribution information, the first attribution information indicating that the performance degradation is severe enough to cause the energy consumption abnormality; in the case that the first contribution degree is less than or equal to the first preset value, determining that the attribution information includes second attribution information, the second attribution information indicating that the energy consumption abnormality is related to the operating parameter of the vehicle-mounted power consumption device; and / or, in the case that the second contribution degree is greater than a second preset value, determining that the attribution information includes third attribution information, the third attribution information indicating that the energy consumption abnormality is related to the power distribution mode; in the case that the second contribution degree is less than or equal to the second preset value, determining that the attribution information includes fourth attribution information, the fourth attribution information indicating that the driving behavior causes the energy consumption abnormality.

[0084] It should be understood that in the above scheme, the first preset value is small, which can be 5%, and the second preset value is also small, which can be 5%.

[0085] In the above technical solution, the first contribution degree is compared with the first preset value, which can accurately distinguish whether the energy consumption abnormality of the vehicle-mounted power consumption device is caused by severe performance degradation or operating parameter, and clearly identify the core cause of the energy consumption abnormality. The second contribution degree is compared with the second preset value, which can define whether the driving behavior related energy consumption abnormality is caused by the power distribution mode or the driving behavior itself, and comprehensively cover the core abnormal inducement. The scheme can provide a concrete and practical attribution determination path, avoiding the generation of ambiguous attribution information. This can help users quickly locate the problem core, further assist users in developing targeted and practical energy reduction schemes, and effectively make up for the short board of lacking deep causal analysis in related technologies.

[0086] In some embodiments, after determining that the attribution information includes the fourth attribution information, the method 300 further includes: determining a fifth contribution degree of the driving behavior smoothness to the second energy consumption abnormality; and determining that the attribution information includes the fourth attribution information includes: determining that the attribution information includes the fourth attribution information in a case that the fifth contribution degree is greater than a sixth preset value, the fourth attribution information indicating that the driving behavior smoothness is lower than a preset smoothness to cause the energy consumption abnormality.

[0087] In some embodiments, before determining the fifth contribution degree of the driving behavior smoothness to the second energy consumption abnormality, the method 300 further includes: determining a sixth contribution degree of the power battery health degree to the second energy consumption abnormality in a case that the vehicle is powered by the power battery; and determining the fifth contribution degree of the driving behavior smoothness to the second energy consumption abnormality includes: determining the fifth contribution degree of the driving behavior smoothness to the second energy consumption abnormality in a case that the sixth contribution degree is less than or equal to a seventh preset value.

[0088] In some embodiments, after determining the sixth contribution degree of the power battery health degree to the second energy consumption abnormality, the method 300 further includes: determining that the attribution information includes fifth attribution information in a case that the sixth contribution degree is greater than the seventh preset value, the fifth attribution information indicating that the power battery health degree causes the energy consumption abnormality.

[0089] In some embodiments, before determining the fifth contribution degree of the driving behavior smoothness to the second energy consumption abnormality, the method 300 further includes: determining a seventh contribution degree of the driving motor performance degradation to the second energy consumption abnormality in a case that the vehicle is driven by the driving motor; and determining the fifth contribution degree of the driving behavior smoothness to the second energy consumption abnormality includes: determining the fifth contribution degree of the driving behavior smoothness to the second energy consumption abnormality in a case that the seventh contribution degree is less than or equal to an eighth preset value.

[0090] In some embodiments, after determining the seventh contribution degree of the driving motor performance degradation to the second energy consumption abnormality, the method 300 further includes: determining that the attribution information includes sixth attribution information in a case that the seventh contribution degree is greater than the eighth preset value, the sixth attribution information indicating that the driving motor performance causes the energy consumption abnormality.

[0091] In some embodiments, before determining the fifth contribution degree of the stability of the driving behavior to the abnormality of the second energy consumption, the method 300 further comprises: determining an eighth contribution degree of a performance degradation of the engine to the abnormality of the second energy consumption when the vehicle is driven by the engine; and determining the fifth contribution degree of the stability of the driving behavior to the abnormality of the second energy consumption comprises: determining the fifth contribution degree of the stability of the driving behavior to the abnormality of the second energy consumption when the eighth contribution degree is less than or equal to a ninth preset value.

[0092] In some embodiments, after determining the eighth contribution degree of the performance degradation of the engine to the abnormality of the second energy consumption, the method 300 further comprises: determining that the attribution information comprises seventh attribution information indicating that the performance of the engine causes the abnormality of the energy consumption when the eighth contribution degree is greater than the ninth preset value.

[0093] In a possible implementation, after the attribution information of the abnormality of the energy consumption of the vehicle in the external driving environment is generated in step 303, the method 300 further comprises: generating driving suggestion information based on the attribution information, the vehicle type of the vehicle, and the environmental information of the external driving environment; splitting the driving suggestion information according to a recommendation priority to obtain multiple groups of suggestion information; and outputting each group of suggestion information according to the recommendation priority.

[0094] It should be understood that, in the above scheme, each group of suggestion information corresponds to a recommendation priority, and the recommendation priority is highest when the corresponding group of suggestion information is emergency suggestion information, followed by conventional suggestion information, and finally long-term suggestion information.

[0095] The emergency suggestion information refers to suggestion information that can take effect immediately in the process of reducing energy consumption. The conventional suggestion information refers to suggestion information that can reduce energy consumption stably by long-term habit actions in the process of reducing energy consumption. The long-term suggestion information refers to suggestion information that can reduce energy consumption by regular maintenance of the vehicle in the process of reducing energy consumption. The three kinds of suggestion information meet the needs of quick effect and gradual optimization. For example, the emergency suggestion information is emergency switching of a power distribution mode, the conventional suggestion information is that acceleration should be smooth, and the long-term suggestion information is regular maintenance of a target hardware device.

[0096] In the technical solution, the driving suggestion information is generated based on the attribution information, the vehicle type and the environment information of the external driving environment, which converts the abstract attribution into the operable guidance that fits the actual scenario. The driving suggestion information is split according to the recommendation priority to obtain multiple groups of suggestion information, which can help the user to sort out the emergency suggestion information, the regular suggestion information and the long-term suggestion information, and avoid the information clutter. Further, the groups of suggestion information are output according to the recommendation priority, which can facilitate the user to preferentially execute the high-value energy consumption reduction scheme. The above scheme takes the accurate attribution information in the previous scheme as the basis, and builds a bridge from the deep attribution analysis to the actual energy consumption reduction action, so that the user not only knows the root cause of the energy consumption anomaly, but also obtains the hierarchical and ordered energy consumption reduction scheme. At the same time, the landing and practicality of the energy consumption reduction scheme can be improved.

[0097] In some embodiments, based on the attribution information, the vehicle type of the vehicle and the environment information of the external driving environment, the driving suggestion information is generated, including: comparing the vehicle type with a plurality of sample vehicle types, determining a target vehicle type matching the vehicle type from the plurality of sample vehicle types; obtaining a target driving suggestion rule library corresponding to the target vehicle type; comparing the environment information with a plurality of sample environment information in the target driving suggestion rule library, determining target environment information matching the environment information from the target driving suggestion rule library; comparing the attribution information with a plurality of attribution information corresponding to the target environment information in the target driving suggestion rule library, determining target attribution information matching the attribution information from the plurality of attribution information; and determining the suggestion information corresponding to the target attribution information in the target driving suggestion rule library as the driving suggestion information.

[0098] It should be understood that the above target driving suggestion rule library is determined in advance based on experience.

[0099] In some embodiments, according to the recommendation priority, the groups of suggestion information are output, including: outputting the corresponding group of suggestion information with the highest recommendation priority in the form of displaying in a first target area on the vehicle display screen and outputting through a voice output device, the first target area being a conspicuous area; displaying the corresponding group of suggestion information with the second highest recommendation priority in the form of a pop-up window on the vehicle display screen; and outputting the corresponding group of suggestion information with the lowest recommendation priority through the voice output device.

[0100] Figure 4 FIG. 1 is another system architecture diagram for vehicle energy consumption analysis provided by an embodiment of the present application.

[0101] On the basis of Figure 2 , an exemplary Figure 4The system architecture is shown. Among them, the analysis calculation layer includes an economy analysis model, a stationarity analysis model, a mode efficiency analysis model, a degree of attenuation analysis model and an attribution analysis model. The economy analysis model is used to determine whether the actual energy consumption of the vehicle is abnormal, and in the case that the actual energy consumption of the vehicle is abnormal, determine the first energy consumption generated by the operation of the on-board power-consuming device and the second energy consumption affected by the driving behavior. The degree of attenuation analysis model is used to determine the first contribution degree of the performance attenuation degree of the on-board power-consuming device to the first energy consumption in the case that the first energy consumption is abnormal. The mode efficiency analysis model is used to determine the second contribution degree of the power distribution mode to the second energy consumption in the case that the second energy consumption is abnormal, based on the target power distribution mode and the current power distribution mode of the vehicle. The attribution analysis model is used to generate attribution information of energy consumption abnormality of the vehicle in the external driving environment based on the first energy consumption and the first contribution degree, and / or the second energy consumption and the second contribution degree. The aforementioned suggestion output layer is used to generate driving suggestion information based on the attribution information, the vehicle type of the vehicle and the environmental information of the external driving environment, and output the driving suggestion information.

[0102] In addition, the aforementioned stationarity analysis model is used to analyze the fifth contribution degree of the stationarity of the driving behavior to the second energy consumption in the case that the second energy consumption is abnormal. When the fifth contribution degree is high, the aforementioned attribution information can specifically include that the low stationarity of the driving behavior leads to energy consumption abnormality.

[0103] Figure 5 FIG. 1 is a structural schematic diagram of a device for monitoring vehicle energy consumption provided by an embodiment of the present application.

[0104] For example, as shown in FIG. 5, the device 500 includes: Figure 5 The determination module 501 is configured to: determine the first energy consumption generated by the operation of the on-board power-consuming device and the second energy consumption affected by the driving behavior in the case that the actual energy consumption of the vehicle is abnormal; determine the first contribution degree of the performance attenuation degree of the on-board power-consuming device to the first energy consumption in the case that the first energy consumption is abnormal; and / or, determine the second contribution degree of the power distribution mode to the second energy consumption in the case that the second energy consumption is abnormal, based on the target power distribution mode and the current power distribution mode of the vehicle; The generation module 502 is configured to generate attribution information of energy consumption abnormality of the vehicle in the external driving environment based on the first energy consumption and the first contribution degree, and / or the second energy consumption and the second contribution degree.

[0105] ​Optionally, the apparatus 500 further includes an acquisition module configured to acquire a vehicle type of the vehicle and environment information of the external driving environment; and the determination module 501 is specifically configured to determine the reference energy consumption of the vehicle when driving based on the vehicle type and the environment information; and determine that the actual energy consumption is abnormal when an energy consumption deviation between the actual energy consumption and the reference energy consumption is greater than a preset deviation.

[0106] Optionally, before determining the first energy consumption generated by the running of the vehicle-mounted power-consuming device and the second energy consumption affected by the driving behavior, the determination module 501 is further configured to determine whether a device state of the vehicle is in a preset state, the preset state being used to indicate that a target hardware device in the vehicle is not abnormal, the target hardware device being a device that will increase energy consumption when running in a fault condition; and the determination module 501 is specifically further configured to determine the first energy consumption and the second energy consumption when the device state is in the preset state.

[0107] Optionally, the acquisition module is specifically configured to acquire a reference energy consumption generated by the running of the vehicle-mounted power-consuming device when there is no performance attenuation, the reference energy consumption and the first energy consumption being the same in the running state of the vehicle-mounted power-consuming device and the vehicle state of the vehicle when being determined; and the determination module 501 is specifically further configured to determine a deviation amplitude of the first energy consumption relative to the reference energy consumption; and determine the first contribution degree based on the deviation amplitude, the deviation amplitude being positively correlated with the first contribution degree.

[0108] Optionally, the determination module 501 is specifically further configured to determine a third contribution degree based on a deviation between the current power distribution mode and the target power distribution mode, the deviation being positively correlated with the third contribution degree; determine a fourth contribution degree based on whether the driving behavior matches the current power distribution mode; and determine the second contribution degree based on the first preset weight and the second preset weight, the third contribution degree and the fourth contribution degree.

[0109] Optionally, the determination module 501 is specifically further configured to determine the first preset weight as a first weight and the second preset weight as a second weight when the vehicle is a fuel vehicle, the first weight being less than the second weight; and determine the first preset weight as a third weight and the second preset weight as a fourth weight when the vehicle is a hybrid vehicle or an electric vehicle, the third weight being greater than the fourth weight.

[0110] Optionally, the generating module 502 is specifically configured to: in a case where the first contribution degree is greater than a first preset value, determine that the attribution information comprises first attribution information, the first attribution information indicating that the performance degradation degree is serious and causes the abnormal energy consumption; in a case where the first contribution degree is less than or equal to the first preset value, determine that the attribution information comprises second attribution information, the second attribution information indicating that the abnormal energy consumption is related to the operating parameter of the vehicle-mounted power consumption device; and / or, in a case where the second contribution degree is greater than a second preset value, determine that the attribution information comprises third attribution information, the third attribution information indicating that the abnormal energy consumption is related to the power distribution mode; in a case where the second contribution degree is less than or equal to the second preset value, determine that the attribution information comprises fourth attribution information, the fourth attribution information indicating that the driving behavior causes the abnormal energy consumption.

[0111] Optionally, after the generating module 502 generates the attribution information of the abnormal energy consumption of the vehicle in the external driving environment, the generating module 502 is further configured to generate driving suggestion information based on the attribution information, the vehicle type of the vehicle, and the environmental information of the external driving environment; the apparatus 500 further comprises a splitting module configured to split the driving suggestion information according to a recommendation priority to obtain multiple groups of suggestion information; and an output module configured to output each group of suggestion information according to the recommendation priority.

[0112] Figure 6 FIG. 1 is a structural schematic diagram of a controller according to an embodiment of the present application.

[0113] For example, as shown in FIG. 6, the controller 600 comprises a storage module 601 and a processing module 602, wherein the storage module 601 stores an executable program code 603, and the processing module 602 is configured to invoke and execute the executable program code 603 to execute a method for monitoring vehicle energy consumption. Figure 6

[0114] Figure 7 FIG. 7 is a structural schematic diagram of a vehicle according to an embodiment of the present application.

[0115] For example, as shown in FIG. 7, the vehicle 700 comprises a storage module 701 and a processing module 702, wherein the storage module 701 stores an executable program code 703, and the processing module 702 is configured to invoke and execute the executable program code 703 to execute a method for monitoring vehicle energy consumption. Figure 7

[0116] In addition, the present application also protects an apparatus, which can comprise a storage module and a processing module, wherein the storage module stores an executable program code, and the processing module is configured to invoke and execute the executable program code to execute a method for monitoring vehicle energy consumption provided by the present application.

[0117] ​​The embodiment can divide the functions of the device according to the method examples described above. For example, each function module can be divided, or two or more functions can be integrated into one processing module. The integrated module can be implemented in the form of hardware. It should be noted that the division of the modules in the embodiment is illustrative, and is only a logical function division. In actual implementation, another division method can be used.

[0118] In the case of dividing each function module according to each function, the device can further include a determination module, a generation module, an acquisition module, a splitting module, and an output module. It should be noted that all related contents of the method embodiments can be applied to the function description of the corresponding function module, and will not be described here.

[0119] It should be understood that the device provided by the embodiment is used to execute the method for monitoring the energy consumption of the vehicle, and thus the same effect as the method can be achieved.

[0120] In the case of using an integrated unit, the device can include a processing module and a storage module. When the device is applied to a vehicle, the processing module can be used to control and manage the actions of the vehicle. The storage module can be used to support the vehicle to execute related executable program codes and the like.

[0121] The processing module can be a processor or a controller, which can implement or execute various exemplary logical blocks, modules, and circuits shown in conjunction with the disclosure of the present application. The processor can also be a combination of computing functions, such as one or more microprocessor combinations, a combination of digital signal processing (DSP) and microprocessors, and the like. The storage module can be a memory.

[0122] In addition, the device provided by the embodiment of the present application can be a chip, an assembly, or a module. The chip can include a connected processor and a memory. The memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the method for monitoring the energy consumption of the vehicle provided by the above embodiment.

[0123] The embodiment also provides a computer readable storage medium, which stores executable program codes. When the executable program codes run on a computer, the computer executes the related method steps to implement the method for monitoring the energy consumption of the vehicle provided by the above embodiment.

[0124] The embodiment also provides a computer program product, which makes the computer execute the related steps to implement the method for monitoring the energy consumption of the vehicle provided by the above embodiment when the computer program product runs on the computer.

[0125] Among them, the device, computer readable storage medium, computer program product or chip provided by the embodiment are used for executing the corresponding method provided above, so the beneficial effects achieved thereby can refer to the beneficial effects in the corresponding method provided above, which will not be repeated here.

[0126] Through the description of the above embodiments, those skilled in the art can understand that, for the convenience and brevity, only the above division of functional modules is taken as an example, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0127] In the embodiments provided in the present application, it should be understood that the disclosed device and method can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0128] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for monitoring vehicle energy consumption, characterized in that, The method includes: In the event of abnormal actual energy consumption of a vehicle, determine the first energy consumption generated by the operation of on-board electrical equipment and the second energy consumption affected by driving behavior; In the event of an abnormality in the first energy consumption, determine the first contribution of the performance degradation of the on-board power-consuming equipment to the occurrence of the abnormality in the first energy consumption; and / or, In the event of an abnormality in the second energy consumption, the second contribution of the power distribution mode to the abnormality in the second energy consumption is determined based on the target power distribution mode and the current power distribution mode of the vehicle. Based on the first energy consumption and the first contribution, and / or the second energy consumption and the second contribution, attribution information for the abnormal energy consumption of the vehicle under external driving conditions is generated.

2. The method according to claim 1, characterized in that, The methods for determining abnormal actual energy consumption of the vehicle include: Obtain the vehicle type and environmental information of the external driving environment; Based on the vehicle type and the environmental information, the baseline energy consumption of the vehicle during operation is determined; If the energy consumption deviation between the actual energy consumption and the reference energy consumption is greater than a preset deviation, it is determined that the actual energy consumption is abnormal.

3. The method according to claim 1, characterized in that, Before determining the first energy consumption generated by the operation of on-board power-consuming equipment and the second energy consumption affected by driving behavior, the method further includes: Determine whether the equipment status of the vehicle is in a preset state. The preset state is used to indicate that the target hardware device in the vehicle is not abnormal. The target hardware device is a device that will increase energy consumption when operating under fault conditions. And, determining the first energy consumption generated by the operation of onboard power-consuming equipment and the second energy consumption affected by driving behavior includes: When the device is in the preset state, the first energy consumption and the second energy consumption are determined.

4. The method according to claim 1, characterized in that, The determination of the performance degradation degree of the vehicle-mounted power-consuming device as the first contribution to the occurrence of an abnormal first energy consumption includes: Obtain a reference energy consumption generated by the operation of the vehicle power-consuming device without performance degradation, wherein the reference energy consumption and the first energy consumption are determined when the operating state of the vehicle power-consuming device and the vehicle state are the same. Determine the deviation of the first energy consumption from the reference energy consumption; The first contribution is determined based on the deviation magnitude, and the deviation magnitude is positively correlated with the first contribution.

5. The method according to claim 1, characterized in that, The determination of the second contribution of the power distribution mode to the occurrence of a second energy consumption anomaly, based on the target power distribution mode and the current power distribution mode of the vehicle, includes: A third contribution is determined based on the deviation between the current power distribution mode and the target power distribution mode, wherein the deviation is positively correlated with the third contribution. A fourth contribution level is determined based on whether the driving behavior matches the current power distribution mode. Based on the first preset weight and the second preset weight, the second contribution is determined for the third contribution and the fourth contribution.

6. The method according to claim 5, characterized in that, The methods for determining the first preset weight and the second preset weight include: When the vehicle is a fuel-powered vehicle, the first preset weight is determined as the first weight, and the second preset weight is determined as the second weight, wherein the first weight is less than the second weight; When the vehicle is a hybrid vehicle or an electric vehicle, the first preset weight is determined as the third weight, and the second preset weight is determined as the fourth weight, wherein the third weight is greater than the fourth weight.

7. The method according to any one of claims 1-6, characterized in that, The process of generating attribution information for abnormal energy consumption of the vehicle under external driving conditions based on the first energy consumption and the first contribution, and / or the second energy consumption and the second contribution, includes: If the first contribution is greater than the first preset value, it is determined that the attribution information includes the first attribution information, which indicates that the performance degradation is severe and causes abnormal energy consumption. If the first contribution is less than or equal to the first preset value, the attribution information is determined to include second attribution information, which indicates that the energy consumption anomaly is related to the operating parameters of the on-board power-consuming equipment; and / or, If the second contribution is greater than the second preset value, it is determined that the attribution information includes third attribution information, and the third attribution information indicates that the energy consumption anomaly is related to the power distribution mode. If the second contribution is less than or equal to the second preset value, the attribution information is determined to include fourth attribution information, which indicates that the driving behavior leads to abnormal energy consumption.

8. The method according to any one of claims 1-6, characterized in that, After generating the attribution information for the abnormal energy consumption of the vehicle under external driving conditions, the method further includes: Based on the attribution information, the vehicle type, and the environmental information of the external driving environment, driving suggestion information is generated; The driving advice information is split according to the recommendation priority to obtain multiple sets of advice information; Based on the recommended priority, output the suggested information for each group.

9. A controller, characterized in that, The controller includes: The storage module is used to store executable program code; A processing module is configured to call and run the executable program code from the storage module, causing the controller to perform the method as described in any one of claims 1 to 8.

10. A vehicle, characterized in that, The vehicles include: Memory, used to store executable program code; A processor for calling and running the executable program code from the memory, causing the vehicle to perform the method as described in any one of claims 1 to 8.

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