WO2022062943A1 - 一种车辆的能耗分析方法、装置和车辆 - Google Patents

一种车辆的能耗分析方法、装置和车辆 Download PDF

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WO2022062943A1
WO2022062943A1 PCT/CN2021/118049 CN2021118049W WO2022062943A1 WO 2022062943 A1 WO2022062943 A1 WO 2022062943A1 CN 2021118049 W CN2021118049 W CN 2021118049W WO 2022062943 A1 WO2022062943 A1 WO 2022062943A1
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energy consumption
factor
preset period
vehicle
contribution information
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PCT/CN2021/118049
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English (en)
French (fr)
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邓俊松
龙荣深
何锐邦
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广州小鹏汽车科技有限公司
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

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  • the invention relates to the technical field of automobiles, in particular to a method, device and vehicle for analyzing energy consumption of a vehicle.
  • the global energy supply is in short supply and the energy supply is in short supply, which increases the operating cost of the vehicle. Therefore, the energy consumption of the vehicle is analyzed to find out the factors that affect the energy consumption, so as to prompt the owner to better reduce energy consumption and save costs.
  • Embodiments of the present invention provide a method for analyzing energy consumption of a vehicle, so as to improve the accuracy of analyzing energy consumption of a vehicle.
  • Embodiments of the present invention also provide an energy consumption analysis device for a vehicle and a vehicle, so as to ensure the implementation of the above method.
  • the present invention discloses a method for analyzing energy consumption, the method comprising:
  • the energy consumption parameter information includes the following energy consumption factors: driving behavior energy consumption factor, vehicle use behavior energy consumption factor, environmental energy consumption factor, and vehicle operation energy consumption factor ;
  • the energy consumption analysis is performed based on the energy consumption parameter information in the preset period, and the energy consumption analysis result in the preset period is determined.
  • the energy consumption analysis is performed based on the energy consumption parameter information in a preset period, and the corresponding energy consumption analysis result is determined, including:
  • the energy consumption analysis is performed according to the weights of the energy consumption factors corresponding to the influence of the energy consumption in the preset period, and the corresponding energy consumption analysis results are determined.
  • the determining, respectively, the weight of each energy consumption factor corresponding to the impact on energy consumption in the preset period includes:
  • the energy consumption analysis is performed according to the corresponding weights of the energy consumption factors in the preset period, and the corresponding energy consumption analysis results are determined, including:
  • the energy consumption analysis result in the preset period is determined according to the contribution information of each energy consumption factor to the energy consumption in the preset period.
  • the energy consumption parameter information further includes the value of each energy consumption factor
  • Determining the contribution information of each energy consumption factor to energy consumption in the preset period according to the weight of each energy consumption factor corresponding to the influence of energy consumption in the preset period including:
  • Weighted calculation is performed according to the corresponding weight of each energy consumption factor on energy consumption and the value of each energy consumption factor in a preset period, to obtain a weighted calculation result;
  • the contribution information of the energy consumption factor to the energy consumption in the preset period is determined.
  • the method further includes:
  • the energy consumption problem diagnosis result is generated according to the contribution information of each energy consumption factor to energy consumption in the preset period and the contribution information of each energy consumption factor to energy consumption in the previous preset period.
  • the energy consumption problem diagnosis result is generated according to the contribution information of each energy consumption factor to energy consumption in a preset period and the contribution information of each energy consumption factor to energy consumption in the previous preset period, including:
  • the energy consumption problem diagnosis result is generated according to the energy consumption factor with the largest change degree of the contribution information and the first preset rule
  • the energy consumption problem diagnosis result is generated according to the energy consumption factor with the largest change degree of the contribution information and the second preset rule;
  • the energy consumption factor with the largest contribution information change among the energy consumption factors whose contribution information change degree is greater than zero the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is less than zero, and the third preset rule , to generate diagnostic results for energy consumption problems.
  • the method further includes:
  • the corresponding energy consumption statistical information and energy consumption change information in the preset period of the vehicle are generated.
  • An embodiment of the present invention also provides a device for analyzing energy consumption of a vehicle, and the device includes:
  • the energy consumption parameter information acquisition module is used to acquire energy consumption parameter information that affects vehicle energy consumption in a preset period, the energy consumption parameter information includes the following energy consumption factors: driving behavior energy consumption factor, vehicle use behavior energy consumption factor, environment Energy consumption factor and vehicle operation energy consumption factor;
  • the analysis module is configured to perform energy consumption analysis based on the energy consumption parameter information in the preset period, and determine the energy consumption analysis result in the preset period.
  • the analysis module includes:
  • a weight determination sub-module which is used to respectively determine the weight of each energy consumption factor corresponding to the influence on energy consumption in a preset period
  • the weight analysis sub-module is used to analyze the energy consumption according to the weight of each energy consumption factor corresponding to the influence of the energy consumption in the preset period, and determine the corresponding energy consumption analysis result.
  • the weight determination submodule includes:
  • a 100-kilometer energy consumption determination unit configured to determine the 100-kilometer energy consumption of the vehicle within a preset period
  • the regression analysis unit is used to use each energy consumption factor in the preset period as an independent variable and the energy consumption per 100 kilometers as a dependent variable, perform regression analysis on the independent variable and the dependent variable, and determine the corresponding energy consumption factors of each energy consumption factor in the preset period. consumption influence weight.
  • the weight analysis submodule includes:
  • a contribution information determination unit configured to determine the contribution information of each energy consumption factor to energy consumption in the preset period according to the weight of each energy consumption factor corresponding to the impact on energy consumption in the preset period;
  • the contribution information analysis unit is configured to determine the energy consumption analysis result in the preset period according to the contribution information of each energy consumption factor to the energy consumption in the preset period.
  • the energy consumption parameter information further includes the value of each energy consumption factor
  • the contribution information determining unit is configured to perform weighted calculation according to the corresponding weight of each energy consumption factor on energy consumption and the value of each energy consumption factor in a preset period, to obtain a weighted calculation result; for one energy consumption factor, calculate the The product of the value of the energy consumption factor and the weight of the influence of the energy consumption factor on energy consumption, to obtain a multiplication result; according to the multiplication result and the weighted calculation result, determine the contribution information of the energy consumption factor to energy consumption in a preset period .
  • the device also includes:
  • the last preset period contribution information acquisition module is used to acquire the contribution information of each energy consumption factor to the energy consumption in the last preset period
  • the energy consumption problem diagnosis result generation module is configured to generate energy consumption problem diagnosis results according to the contribution information of each energy consumption factor to energy consumption in the preset period and the contribution information of each energy consumption factor to energy consumption in the previous preset period.
  • the energy consumption problem diagnosis result generation module includes:
  • the change degree determination sub-module is used to determine the contribution information corresponding to each energy consumption factor according to the contribution information of each energy consumption factor to energy consumption in the preset period and the contribution information of each energy consumption factor to energy consumption in the previous preset period degree of change;
  • the first diagnosis result generation sub-module is configured to generate a diagnosis result of the energy consumption problem according to the energy consumption factor with the largest change degree of the contribution information and the first preset rule if the change degree of the contribution information corresponding to each energy consumption factor is less than zero;
  • the second diagnosis result generating sub-module is configured to generate a diagnosis result of the energy consumption problem according to the energy consumption factor with the largest change degree of the contribution information and the second preset rule if the change degree of the contribution information corresponding to each energy consumption factor is greater than zero;
  • the third diagnosis result generating sub-module is used for otherwise, according to the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is greater than zero, and the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is less than zero.
  • the energy consumption factor and the third preset rule are used to generate energy consumption problem diagnosis results.
  • the device also includes:
  • the energy consumption statistical change information generation module is configured to generate the corresponding energy consumption statistical information and energy consumption change information in the preset period of the vehicle based on the energy consumption per 100 kilometers of the vehicle in the preset period.
  • Embodiments of the present invention also provide a vehicle including a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors.
  • One or more programs include a method for performing energy consumption analysis of a vehicle as described in any of the embodiments of the present invention.
  • the embodiment of the present invention further provides a readable storage medium, when the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the energy consumption of the vehicle according to any one of the embodiments of the present invention Analytical method.
  • the embodiments of the present invention include the following advantages:
  • energy consumption parameter information that affects vehicle energy consumption in a preset period may be acquired, and then based on the energy consumption parameter information in the preset period, the energy consumption of the vehicle in the preset period is analyzed to determine the energy consumption in the preset period.
  • the vehicle energy consumption is comprehensively analyzed by various factors, so as to improve the accuracy of the vehicle energy consumption analysis.
  • FIG. 1 is a flow chart of steps of an embodiment of a method for analyzing energy consumption of a vehicle according to the present invention
  • FIG. 2 is a flow chart of steps of an optional embodiment of a method for analyzing energy consumption of a vehicle according to the present invention
  • FIG. 3 is a flow chart of steps of another embodiment of a method for analyzing energy consumption of a vehicle according to the present invention.
  • FIG. 4 is a structural block diagram of an embodiment of an energy consumption analysis device for a vehicle according to the present invention.
  • FIG. 5 is a structural block diagram of an optional embodiment of an apparatus for analyzing energy consumption of a vehicle according to the present invention.
  • the embodiment of the present invention provides a method for analyzing vehicle energy consumption, which analyzes vehicle energy consumption by synthesizing the influence of various factors such as people, vehicles, and environment on vehicle energy consumption, thereby improving the accuracy of vehicle energy consumption analysis.
  • FIG. 1 there is shown a flow chart of steps of an embodiment of a method for analyzing energy consumption of a vehicle according to the present invention, which may specifically include the following steps:
  • Step 102 Obtain energy consumption parameter information that affects vehicle energy consumption within a preset period, where the energy consumption parameter information includes the following energy consumption factors: driving behavior energy consumption factor, vehicle use behavior energy consumption factor, environmental energy consumption factor, and vehicle operation energy consumption factor energy consumption factor.
  • Vehicle energy consumption is the result of the combined effect of many factors, such as people, vehicles and the environment; however, the analysis of vehicle energy consumption in the prior art is mostly carried out for the components of the vehicle itself, ignoring the The impact of people and the environment on vehicle energy consumption. Therefore, the embodiments of the present invention can comprehensively analyze vehicle energy consumption from multiple factors, such as people, vehicles, and the environment, so as to improve the accuracy of vehicle energy consumption analysis.
  • energy consumption parameter information that affects the vehicle energy consumption in a preset period may be acquired.
  • the energy consumption parameter information may refer to information that affects vehicle energy consumption, and may include an energy consumption factor that affects vehicle energy consumption and a value of the energy consumption factor.
  • the energy consumption parameter information may include the following energy consumption factors: a driving behavior energy consumption factor, a vehicle usage behavior energy consumption factor, an environmental energy consumption factor, and a vehicle operation energy consumption factor.
  • the preset period may be the current period, or may be any period in history; the period may be divided according to requirements, such as divided by time, such as 1 week, or divided according to mileage, such as vehicle traveling 500km, etc., the present invention implements The example does not limit this.
  • the driving behavior energy consumption factor may include factors corresponding to various driving behaviors that affect the vehicle energy consumption during the driving process of the vehicle, such as acceleration behavior factors, high-speed driving behavior factors, and the like.
  • the vehicle usage behavior energy consumption factor may include various vehicle usage behavior factors that affect vehicle energy consumption during vehicle driving, such as: air conditioner temperature setting factor and the like.
  • the environmental energy consumption factor may include factors corresponding to various environments that affect the energy consumption of the vehicle during the running of the vehicle, such as a road surface quality factor and the like.
  • the vehicle operation energy consumption factor may include factors corresponding to various vehicle operation conditions that affect the vehicle energy consumption during the driving process of the vehicle, for example, the energy consumption factor of low-voltage electrical appliances.
  • the driving behavior energy consumption factor and the vehicle use behavior energy consumption factor may belong to the factors affecting the energy consumption of vehicles by humans;
  • the environmental energy consumption factor may belong to the factors affecting the energy consumption of the vehicle by the environment ;
  • the vehicle running energy consumption factor may belong to the factor that the vehicle itself affects the vehicle energy consumption.
  • the energy consumption parameter information may also include other energy consumption factors, which are not limited in this embodiment of the present invention.
  • Step 104 Perform energy consumption analysis based on the energy consumption parameter information in the preset period, and determine the energy consumption analysis result in the preset period.
  • the driving behavior energy consumption factor, the vehicle usage behavior energy consumption factor, the environmental energy consumption factor and the vehicle operation energy consumption in the energy consumption parameter information can be integrated factor, carry out energy consumption analysis, and determine the energy consumption analysis results within the preset period.
  • the energy consumption parameter information that affects the energy consumption of the vehicle in the preset period can be obtained, and then the energy consumption of the vehicle in the preset period is analyzed based on the energy consumption parameter information in the preset period, and the predetermined period is determined.
  • the step of performing energy consumption analysis based on the energy consumption parameter information in a preset period, and determining a corresponding energy consumption analysis result includes: respectively determining the corresponding energy consumption factors of each energy consumption factor in the preset period.
  • the weight of the influence of energy consumption according to the weight of each energy consumption factor corresponding to the influence of energy consumption in the preset period, the energy consumption analysis is carried out, and the corresponding energy consumption analysis result is determined.
  • the embodiment of the present invention may first analyze the weight of the influence of each energy consumption factor on the vehicle energy consumption; Determine the energy analysis results.
  • FIG. 2 there is shown a flowchart of steps of an optional embodiment of a method for analyzing energy consumption of a vehicle according to the present invention, which may specifically include the following steps:
  • Step 202 Obtain energy consumption parameter information that affects vehicle energy consumption within a preset period, where the energy consumption parameter information includes the following energy consumption factors: driving behavior energy consumption factor, vehicle usage behavior energy consumption factor, environmental energy consumption factor, and vehicle operation energy consumption factor Energy consumption factor; the energy consumption parameter information also includes the value of each energy consumption factor.
  • the driving behavior energy consumption factor may include multiple factors, such as an acceleration behavior factor, a deceleration behavior factor, a high-speed driving behavior factor, a low-speed driving behavior factor, etc. Of course, it may also include other factors, which are not limited in this embodiment of the present invention .
  • the energy consumption factor for vehicle use behavior may include multiple factors, such as an energy recovery mode preference factor, an energy recovery effect factor, an air conditioner operating intensity factor, and an air conditioner use duration factor, and of course, other factors may also be included, which the embodiment of the present invention addresses. No restrictions apply.
  • the environmental energy consumption factor may include multiple factors, such as a road surface quality factor, an ambient temperature factor, etc. Of course, other factors may also be included, which is not limited in this embodiment of the present invention.
  • the energy consumption factor for vehicle operation may include, for example, the energy consumption factor of low-voltage electrical appliances, and of course, may also include other factors, which are not limited in this embodiment of the present invention.
  • the value of the energy consumption factor may refer to the mileage or time traveled by the vehicle under the action of the energy consumption factor, as a proportion of the total mileage or total driving time in the entire preset period.
  • the energy consumption factor is the high-speed behavior factor
  • the value of the mileage of high-speed driving (driving speed greater than 85km/h) in the preset period as a proportion of the total mileage in the preset period can be used as the preset period
  • the value of the inner high-speed behavior factor is the value of the mileage of high-speed driving (driving speed greater than 85km/h) in the preset period as a proportion of the total mileage in the preset period.
  • the energy consumption factor is the air conditioner usage time factor
  • the value of the ratio of the time the vehicle turns on the air conditioner in the preset period to the total travel time in the preset period can be used as the value of the air conditioner usage time factor in the preset period.
  • Step 204 Determine the energy consumption per 100 kilometers of the vehicle in a preset period.
  • the energy consumption per 100 kilometers can refer to the amount of electricity consumed by the vehicle traveling 100 kilometers.
  • the mileage of each trip and the power consumed by each trip in a preset period may be obtained first; then, according to the mileage of each trip and the power consumed by each trip, the The energy consumption per 100 kilometers of the trip; and then calculate the energy consumption per 100 kilometers of the vehicle in the preset period based on the energy consumption per 100 kilometers of each trip, the mileage of each trip and the total mileage of the vehicle in the preset period.
  • the energy consumption per 100 kilometers of the vehicle can be calculated as follows:
  • the remaining power of the vehicle is 40kW ⁇ h (kilowatt-hour), and the charging power of the vehicle during the trip is 20kWh.
  • the remaining power of the vehicle is 35kW h, which can be calculated as follows:
  • the energy consumption per 100 kilometers of each trip of the vehicle in the preset period can be calculated according to the power consumption of each trip in the preset period and the mileage corresponding to each trip. For example, if there are 4 trips in the preset period, The power consumption of each journey is 8kW ⁇ h, 5kW ⁇ h, 3kW ⁇ h, and 1kW ⁇ h, and the mileage corresponding to each journey is 60km, 40km, 25km, and 10km, which can be calculated as follows:
  • the energy consumption per 100 kilometers of each trip in the preset period can be obtained as: 13.3kW ⁇ h/100 kilometers, 12.5kW ⁇ h/100 kilometers, 12kW ⁇ h/100 kilometers, and 10kW ⁇ h/100 kilometers.
  • the energy consumption per 100 kilometers of the vehicle in the preset period can be calculated according to the energy consumption per 100 kilometers of each trip in the preset period, the mileage corresponding to each trip, and the sum of the mileage of each segment of the vehicle in the preset period, such as :
  • There are 4 trips in the preset cycle and the energy consumption per 100 kilometers of each trip is 13.3kW ⁇ h/100km, 12.5kW ⁇ h/100km, 12kW ⁇ h/100km, and 10kW ⁇ h/100km;
  • the mileage corresponding to each trip is 60km, 40km, 25km and 10km, which can be calculated as follows:
  • the energy consumption per 100 kilometers of the vehicle in the current time period is: 12.7kW ⁇ h/100 kilometers.
  • the remaining power of the vehicle at the beginning of the mileage can be collected first; then the charging power of the vehicle within the mileage and the remaining power of the vehicle at the end of the mileage can be collected. Then, according to the vehicle power at the beginning, the charging power, the remaining power of the vehicle at the end, and the preset mileage of the mileage, the energy consumption per hundred kilometers of the vehicle within the current mileage is calculated.
  • the preset mileage is 500km
  • the remaining power of the vehicle at the beginning of the mileage is 40kW ⁇ h
  • the vehicle is charged once within the mileage
  • the charging power is 50kW ⁇ h
  • the remaining power of the vehicle at the end is 28kW h
  • Step 206 Use each energy consumption factor in the preset period as the independent variable and the energy consumption per 100 kilometers as the dependent variable, perform regression analysis on the independent variable and the dependent variable, and determine the corresponding effect of each energy consumption factor on the energy consumption in the preset period. Weights.
  • each energy consumption factor in a preset period can be used as an independent variable, and the energy consumption per 100 kilometers in a preset period can be used as a dependent variable, and then regression analysis is performed on the independent variable and the dependent variable, so as to determine the predicted
  • the weights of the influences on vehicle energy consumption corresponding to each energy consumption factor in the period are set, for example, linear regression analysis, nonlinear regression analysis, or other regression analysis may be performed, which is not limited in this embodiment of the present invention.
  • Step 208 Determine the contribution information of each energy consumption factor to energy consumption in the preset period according to the corresponding weight of each energy consumption factor on the energy consumption in the preset period.
  • the contribution information of each energy consumption factor to the energy consumption in the preset period may be determined according to the weight; wherein, the contribution information It can refer to the contribution degree of each energy consumption factor to energy consumption in a preset period.
  • step 208 may include the following sub-steps:
  • Sub-step 2082 Perform a weighted calculation according to the corresponding weight of each energy consumption factor on the energy consumption and the value of each energy consumption factor within a preset period, to obtain a weighted calculation result.
  • weighted calculation may be performed according to the weight of each energy consumption factor and the value of each energy consumption factor, so as to obtain a weighted calculation result, for example: Assume that the weights of each energy consumption factor corresponding to the impact on energy consumption in the cycle are 25%, 25%, 30%, and 20%, respectively, and the values of each energy consumption factor are 0.78, 0.75, 0.54, and 0.08, respectively, which can be calculated as follows :
  • the weighted calculation result can be obtained as: 0.56.
  • Sub-step 2084 For one energy consumption factor, calculate the product of the value of the energy consumption factor and the weight of the influence of the energy consumption factor on energy consumption, to obtain a multiplication result.
  • each energy consumption factor the value of each energy consumption factor and its corresponding weight may be multiplied to obtain a multiplication result.
  • the weights are 25%, 25%, 30%, and 20%, respectively, and the values of the energy consumption factors are 0.78, 0.75, 0.54, and 0.08, respectively, which can be calculated as follows:
  • the product results of each energy consumption factor can be obtained as: 0.195, 0.187, 0.162 and 0.016, respectively.
  • Sub-step 2086 Determine the contribution information of the energy consumption factor to energy consumption in a preset period according to the product result and the weighted calculation result.
  • the contribution information of each energy consumption factor to energy consumption can be obtained by calculating the ratio of the product result of each energy consumption factor to the weighted calculation result.
  • the product of the contribution information and the energy consumption per 100 kilometers of the vehicle in a preset period can also be calculated to obtain the The contribution value of each energy consumption factor to the energy consumption per 100 kilometers, for example, the energy consumption per 100 kilometers is 12.5kW ⁇ h/100 kilometers, and the calculated contribution value of the acceleration behavior factor is 1kW ⁇ h/100 kilometers, then the contribution value can refer to It is "12.5kW ⁇ h of electricity consumed by the vehicle running for 100 kilometers, 1kW ⁇ h of which is consumed by the acceleration behavior factor".
  • the energy consumption factors in the preset period include: acceleration behavior factor, high-speed driving behavior factor, low-speed driving behavior factor, sport mode preference factor, energy recovery mode preference factor, energy recovery effect factor, air conditioner operation intensity factor, air conditioner use duration factor, Low-voltage electrical energy consumption factor and road surface quality factor; the energy consumption per 100 kilometers of the vehicle in the preset period is 12.1kW ⁇ h/100 kilometers.
  • each energy consumption factor is: 0.78, 0.75, 0.01, 0.54, 0.08, 0.03, 0.9, 0.4, 0.29 and 0.98;
  • each energy consumption factor on energy consumption is: 10%, 4%, 20%, 21%, 13%, 8%, 1%, 7%, 2% and 14%;
  • the weighted calculation result obtained by calculation is: 0.416;
  • the calculated products for each energy factor are: 0.078, 0.03, 0.002, 0.113, 0.010, 0.002, 0.009, 0.028, 0.006 and 0.137;
  • the contribution information of each energy consumption factor to energy consumption is calculated as: 0.187, 0.072, 0.005, 0.272, 0.025, 0.006, 0.022, 0.067, 0.014 and 0.330.
  • the obtained contribution information of the energy consumption factor to the energy consumption may be stored, so as to analyze the historical energy consumption of the vehicle subsequently .
  • Step 210 Determine the energy consumption analysis result in the preset period according to the contribution information of each energy consumption factor to the energy consumption in the preset period.
  • the contribution information of each energy consumption factor to energy consumption in the preset period can be directly determined as the information in the preset period Energy analysis results.
  • a graph may also be generated according to the contribution information of each energy consumption factor to the energy consumption in the preset period; the generated graph is determined as the energy consumption analysis result in the preset period; this is not limited in the embodiment of the present invention.
  • the energy consumption analysis result within a preset period may be displayed on a vehicle display device such as a central control panel, so as to provide the user with a clearer energy consumption analysis result.
  • the energy consumption analysis result may also be stored, so that the subsequent analysis of the historical energy consumption of the vehicle can be performed directly according to the stored energy consumption analysis result.
  • regression analysis is performed on the energy consumption per 100 kilometers of the vehicle and each energy consumption factor in the preset period, and the weight of each energy consumption factor in the preset period corresponding to the impact on energy consumption is determined, and based on the weight
  • the energy consumption analysis results are obtained; and the accuracy of the energy consumption analysis results is further improved.
  • the contribution information of each energy consumption factor to energy consumption can be calculated according to the weight and the value of each energy consumption factor, and the energy consumption analysis result can be generated according to the contribution information, so that the user can know the energy consumption analysis result according to the energy consumption analysis result.
  • FIG. 3 there is shown a flow chart of steps of another optional embodiment of a method for analyzing energy consumption of a vehicle according to the present invention, which may specifically include the following steps:
  • Step 302 Obtain energy consumption parameter information that affects vehicle energy consumption within a preset period, where the energy consumption parameter information includes the following energy consumption factors: driving behavior energy consumption factor, vehicle use behavior energy consumption factor, environmental energy consumption factor, and vehicle operation energy consumption factor Energy consumption factor; the energy consumption parameter information also includes the value of each energy consumption factor.
  • Step 304 Determine the energy consumption per 100 kilometers of the vehicle in a preset period.
  • Step 306 Use each energy consumption factor in the preset period as the independent variable and the energy consumption per 100 kilometers as the dependent variable, perform regression analysis on the independent variable and the dependent variable, and determine the corresponding effect of each energy consumption factor in the preset period on the energy consumption. Weights.
  • Step 308 Determine the contribution information of each energy consumption factor to the energy consumption in the preset period according to the corresponding weight of each energy consumption factor on the energy consumption in the preset period.
  • Step 310 Determine the energy consumption analysis result in the preset period according to the contribution information of each energy consumption factor to the energy consumption in the preset period.
  • Steps 302 to 310 are similar to the above-mentioned steps 202 to 210, and are not repeated here.
  • Step 312 Acquire the contribution information of each energy consumption factor to energy consumption in the last preset period.
  • Step 314 according to the contribution information of each energy consumption factor to energy consumption in the preset period and the contribution information of each energy consumption factor to energy consumption in the previous preset period, generate a diagnosis result of the energy consumption problem.
  • the contribution information of each energy consumption factor to energy consumption in the previous preset period of the current vehicle can also be obtained; and then the contribution information of each energy consumption factor to energy consumption in the preset period can be compared, and the contribution information of each energy consumption factor to energy consumption in the previous preset period to determine the contribution information of each energy consumption factor to energy consumption in the preset period, compared with the contribution information of each energy consumption factor to energy consumption in the previous preset period.
  • the degree of change of the contribution information and then according to the degree of change, the energy consumption problem of the vehicle is analyzed and diagnosed, and a diagnosis result of energy consumption problem is generated according to the result of the analysis and diagnosis.
  • the change degree of contribution information corresponding to each energy consumption factor can be calculated in the following manner:
  • the change degree of the contribution information the contribution information of the energy consumption factor of the preset period to the energy consumption - the contribution information of the energy consumption factor of the previous preset period to the energy consumption factor to the energy consumption.
  • the energy consumption problem diagnosis result is generated according to the energy consumption factor with the largest change degree of the contribution information and the first preset rule.
  • a first preset rule may be preset, and the first preset rule may refer to the energy consumption problem that the contribution information of each energy consumption factor in the preset period is reduced relative to the contribution information of each energy consumption factor in the previous preset period
  • the diagnosis result may include a first preset energy consumption problem diagnosis result template, and the first preset energy consumption problem diagnosis result template includes the energy consumption factor with the largest degree of change in the contribution information.
  • the first preset energy consumption problem diagnosis result template is such as "Great! The energy consumption factors monitored in this period have been improved in an all-round way, and the ** factor (that is, the energy consumption factor with the greatest degree of change in the contribution information) has dropped particularly significantly, please continue. Keep”.
  • the change degree of the contribution information corresponding to each energy consumption factor is less than zero, it can be considered that the energy consumption of the preset period is relatively lower than the energy consumption of the previous preset period; In a preset period, the energy consumption factor with the greatest change in the contribution information is generated; and then a diagnosis result of the energy consumption problem is generated according to the energy consumption factor with the largest change in the contribution information and the first preset energy consumption problem diagnosis result template. For example, if the energy consumption factor with the largest change in the contribution information is the "acceleration behavior factor", the following energy consumption problem diagnosis results can be generated: "Great! The energy consumption factors monitored in this period have been comprehensively improved, and the acceleration behavior factor has dropped particularly significantly. Please keep it up.” The diagnostic result of the energy consumption problem can then be displayed on a display device of the vehicle.
  • the energy consumption problem diagnosis result is generated according to the energy consumption factor with the largest change degree of the contribution information and the second preset rule.
  • a second preset rule may be preset, and the second preset rule may be a problem of energy consumption in which the contribution information of each energy consumption factor in the preset period is increased relative to the contribution information of each energy consumption factor in the previous preset period
  • the diagnosis result may include a second preset energy consumption problem diagnosis result template, where the second preset energy consumption problem diagnosis result template includes the energy consumption factor with the greatest degree of change in the contribution information.
  • the second preset energy consumption problem diagnosis result template is such as "Very bad! The energy consumption factors monitored in this period are not overall good, and the ** factor (that is, the energy consumption factor with the greatest degree of change in the contribution information) increases particularly significantly, please pay attention to ".
  • the change degree of the contribution information corresponding to each energy consumption factor is greater than zero, it can be considered that the energy consumption of the preset period is relatively higher than the energy consumption of the previous preset period; at this time, the comparison of the preset period can be determined.
  • the energy consumption factor with the largest change in the contribution information is generated; and then a diagnosis result of the energy consumption problem is generated according to the energy consumption factor with the largest change in the contribution information and the second preset energy consumption problem diagnosis result template.
  • the energy consumption factor with the greatest change in the contribution information is the “Pavement Quality Factor”
  • the following energy consumption problem diagnosis result can be generated: “Very bad!
  • the energy consumption factor monitored in this period is not good in general, and the increase in the road surface quality factor is particularly obvious. Please note”.
  • the diagnostic result of the energy consumption problem can then be displayed on a display device of the vehicle.
  • the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is greater than zero the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is less than zero, and
  • the third preset rule is to generate a diagnosis result of the energy consumption problem.
  • a third preset rule may be preset, and the third preset rule may be that the contribution information for some energy consumption factors in the preset period is reduced relative to the contribution information of the energy consumption factors corresponding to the previous preset period, and another part
  • the energy consumption problem diagnosis result in which the contribution information of the energy consumption factor is increased relative to the contribution information of the energy consumption factor corresponding to the previous preset period may include a third preset energy consumption problem diagnosis result template, the third preset energy consumption problem
  • the energy consumption problem diagnosis result template includes the energy consumption factor that contributes the most information change among the energy consumption factors of the reduced part, and the energy consumption factor that contributes the most information change of the energy consumption factors of the increased part.
  • the third preset energy consumption problem diagnosis result template is such as "The current ** factor (that is, the energy consumption factor that contributes the most information change among the energy consumption factors in the reduced part) has improved significantly, please continue to maintain; the current ** factor (that is, the energy consumption factor that contributes the most information change among the energy consumption factors of the rising part) is not performing well, please pay attention.”
  • the change degree of the contribution information corresponding to some energy consumption factors is greater than zero, and the change degree of the contribution information corresponding to another part of the energy consumption factors is less than zero, it can be considered that the influence of some energy consumption factors in the preset period on energy consumption is reduced, and the other part The influence of the energy consumption factor on energy consumption has increased; at this time, it can be determined that the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is greater than zero in the preset period compared with the previous preset period, And the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is less than zero; Among the energy consumption factors less than zero, the energy consumption factor that contributes the largest degree of information change, and the third preset energy consumption problem diagnosis result template, generate an energy consumption diagnosis problem diagnosis result.
  • the energy consumption factor with the largest contribution information change information is the “Motion Mode Preference Factor”, and among the energy consumption factors whose contribution information change degree is greater than zero, the energy consumption factor with the largest contribution information change degree If it is "low-voltage electrical energy consumption factor”, the following energy consumption diagnosis results can be generated: "This issue's exercise mode preference factor has improved significantly, please continue to maintain it; this issue's low-voltage electrical energy consumption factor is not performing well, please pay attention”. The diagnostic result of the energy consumption problem can then be displayed on a display device of the vehicle.
  • the following steps may be further performed:
  • the corresponding energy consumption statistical information and energy consumption change information in the preset period of the vehicle are generated.
  • the energy consumption per 100 kilometers of the vehicle can be used to generate statistical information of energy consumption; then the statistical information of energy consumption is displayed on the display device of the vehicle, In order to inform the user of the energy consumption of the vehicle in a preset period; the statistical information of the energy consumption can also be stored for subsequent analysis of the energy consumption of the vehicle.
  • the statistical information may further include: the mileage traveled by the vehicle in the current cycle, the energy consumption cost, and the like, which are not limited in this embodiment of the present invention.
  • the energy consumption change information corresponding to the vehicle in the preset period may also be generated based on the energy consumption per 100 kilometers of the vehicle in the preset period.
  • the energy consumption per 100 kilometers of the vehicle in each time period in the preset period may be determined, for example, the preset period is one week, and each time period in the preset period may be one day; then In a preset period, the energy consumption per 100 kilometers of the vehicle in each time period is used to generate energy consumption change information. Then, the energy consumption change information is displayed on the display device of the vehicle, so that the user can know the change of the energy consumption of the vehicle.
  • the energy consumption change information may further include: in the previous preset period, the energy consumption per 100 kilometers of the vehicle in each time period; The degree of increase (or decrease), etc., is not limited in this embodiment of the present invention.
  • the energy consumption per 100 kilometers of other vehicles of the same series can also be obtained, and the energy consumption change information can be generated by using the comparison results of the energy consumption per 100 kilometers of this vehicle and other vehicles of the same series, so as to inform the user that his vehicle is different from other vehicles of the same series.
  • the difference in energy consumption per 100 kilometers of a series of vehicles determines whether the current change in energy consumption is an isolated case.
  • a plurality of energy consumption change characteristic rules can be preset, and when the energy consumption of 100 kilometers in the preset period changes relative to the previous preset period, the energy consumption can be matched based on the energy consumption change. Change characteristic rules, and then generate energy consumption change information according to the matched energy consumption change characteristic rules.
  • the preset multiple energy consumption change characteristic rules may include: rule 1: energy consumption toggle, energy consumption fluctuates greatly in recent cycles; rule 2: sudden change in energy consumption, the increase or decrease of energy consumption in this cycle is relatively high. Large; rule 3: sudden change in ranking, in the energy consumption ranking of the same series of vehicles, the energy consumption ranking of this cycle has changed greatly; rule 4: energy consumption is maintained, and the energy consumption in recent cycles is kept within a certain range; rule 5: If the energy consumption is a new low or a new high, the energy consumption of the current cycle is the lowest or highest in history, which is not limited in the embodiment of the present invention.
  • the energy consumption change characteristic rule that conforms to the most recent energy consumption change characteristic rule may be preferentially selected to generate the energy consumption change characteristic rule according to the time sequence of the occurrence of the energy consumption change characteristic rule.
  • consumption change information which is not limited in this embodiment of the present invention.
  • the contribution information of each energy consumption factor to energy consumption in the previous preset period can be obtained, and then it is compared with the contribution information of each energy consumption factor to energy consumption in the preset period, and then The energy consumption problem diagnosis result is generated according to the comparison result, so as to inform the user of the current energy consumption problem of the vehicle, so that the user can optimize the use of the vehicle according to the diagnosis result.
  • energy consumption statistics information and energy consumption change information are generated, so that the user can understand the usage of vehicle energy consumption and the change of vehicle energy consumption.
  • FIG. 4 a structural block diagram of an embodiment of an energy consumption analysis device for a vehicle of the present invention is shown, which may specifically include the following modules:
  • the energy consumption parameter information acquisition module 402 is configured to acquire energy consumption parameter information affecting vehicle energy consumption within a preset period, the energy consumption parameter information including the following energy consumption factors: driving behavior energy consumption factor, vehicle use behavior energy consumption factor, Environmental energy consumption factor and vehicle operation energy consumption factor;
  • the analysis module 404 is configured to perform energy consumption analysis based on the energy consumption parameter information in the preset period, and determine the energy consumption analysis result in the preset period.
  • FIG. 5 a structural block diagram of an optional embodiment of an energy consumption analysis device for a vehicle of the present invention is shown, which may specifically include the following modules:
  • the analysis module 404 includes:
  • a weight determination sub-module 4042 configured to respectively determine the weight of each energy consumption factor corresponding to the influence of energy consumption in a preset period
  • the weight analysis sub-module 4044 is configured to perform energy consumption analysis according to the weight of each energy consumption factor corresponding to the influence of the energy consumption in the preset period, and determine the corresponding energy consumption analysis result.
  • the weight determination sub-module 4042 includes:
  • a 100-kilometer energy consumption determination unit 40422 configured to determine the 100-kilometer energy consumption of the vehicle within a preset period
  • the regression analysis unit 40424 is used to use each energy consumption factor in the preset period as an independent variable and the energy consumption per 100 kilometers as a dependent variable, perform regression analysis on the independent variable and the dependent variable, and determine the corresponding energy consumption factors in the preset period. The weight of the impact of energy consumption.
  • the weight analysis sub-module 4044 includes:
  • Contribution information determination unit 40442 configured to determine the contribution information of each energy consumption factor to energy consumption in the preset period according to the weight of each energy consumption factor corresponding to the impact on energy consumption in the preset period;
  • the contribution information analysis unit 40444 is configured to determine the energy consumption analysis result in the preset period according to the contribution information of each energy consumption factor to the energy consumption in the preset period.
  • the energy consumption parameter information further includes the value of each energy consumption factor
  • the contribution information determination unit 40442 is configured to perform weighted calculation according to the corresponding weight of each energy consumption factor on energy consumption and the value of each energy consumption factor in a preset period, to obtain a weighted calculation result; The product of the value of the energy consumption factor and the weight of the energy consumption factor's influence on energy consumption is obtained to obtain a multiplication result; according to the multiplication result and the weighted calculation result, the contribution of the energy consumption factor to energy consumption in a preset period is determined information.
  • the device further includes:
  • the last preset period contribution information acquisition module 406 is used to acquire the contribution information of each energy consumption factor to the energy consumption in the last preset period;
  • the energy consumption problem diagnosis result generation module 408 is configured to generate the energy consumption problem diagnosis result according to the contribution information of each energy consumption factor to energy consumption in the preset period and the contribution information of each energy consumption factor to energy consumption in the previous preset period .
  • the energy consumption problem diagnosis result generation module 408 includes:
  • the change degree determination sub-module 4082 is used to determine the corresponding contribution of each energy consumption factor according to the contribution information of each energy consumption factor to energy consumption in the preset period and the contribution information of each energy consumption factor to energy consumption in the previous preset period the degree of information change;
  • the first diagnosis result generation sub-module 4084 is configured to generate a diagnosis result of energy consumption problem according to the energy consumption factor with the largest change degree of contribution information and the first preset rule if the change degree of the contribution information corresponding to each energy consumption factor is less than zero ;
  • the second diagnosis result generation sub-module 4086 is configured to generate a diagnosis result of energy consumption problem according to the energy consumption factor with the largest change degree of the contribution information and the second preset rule if the change degree of the contribution information corresponding to each energy consumption factor is greater than zero ;
  • the third diagnosis result generation sub-module 4088 is used for otherwise, according to the energy consumption factor with the largest contribution information change degree among the energy consumption factors whose contribution information change degree is greater than zero, and the contribution information change degree among the energy consumption factors whose contribution information change degree is less than zero.
  • the largest energy consumption factor and the third preset rule generate energy consumption problem diagnosis results.
  • the device further includes:
  • the energy consumption statistical change information generation module 410 is configured to generate the corresponding energy consumption statistical information and energy consumption change information in the preset period of the vehicle based on the energy consumption per 100 kilometers of the vehicle in the preset period.
  • energy consumption parameter information affecting vehicle energy consumption in a preset period may be obtained, and then based on the energy consumption parameter information in the preset period, the energy consumption of the vehicle in the preset period is analyzed, and the preset period is determined.
  • Embodiments of the present invention also provide a vehicle including a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors.
  • One or more programs include a method for performing energy consumption analysis of a vehicle as described in any of the embodiments of the present invention.
  • the embodiment of the present invention further provides a readable storage medium, when the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the energy consumption of the vehicle according to any one of the embodiments of the present invention Analytical method.
  • embodiments of the embodiments of the present invention may be provided as a method, an apparatus, or a computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media having computer-usable program code embodied therein, including but not limited to disk storage, CD-ROM, optical storage, and the like.
  • Embodiments of the present invention are described with reference to flowcharts and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the present invention. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing terminal equipment to produce a machine that causes the instructions to be executed by the processor of the computer or other programmable data processing terminal equipment Means are created for implementing the functions specified in the flow or flows of the flowcharts and/or the blocks or blocks of the block diagrams.
  • These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal equipment to operate in a particular manner, such that the instructions stored in the computer readable memory result in an article of manufacture comprising instruction means, the The instruction means implement the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

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Abstract

一种车辆的能耗分析方法、装置和车辆，能耗分析方法包括：获取预设周期内影响车辆能耗的能耗参数信息，然后基于预设周期内能耗参数信息对车辆预设周期内的能耗进行分析，确定预设周期内的能耗分析结果；其中，能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子。

Description

一种车辆的能耗分析方法、装置和车辆
本申请要求在2020年09月23日提交中国专利局、申请号202011013261.9、发明名称为“一种车辆的能耗分析方法、装置和车辆”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及汽车技术领域，特别是涉及一种车辆的能耗分析方法、装置和车辆。
背景技术
全球能源的供应短缺，能源供不应求，使得车辆的运营成本也随之增加。因此对车辆的能耗进行分析，从中找出影响能耗的因素，以便于提示车主更好的降低能耗、节省费用。
目前大多能耗分析的方案，均是针对车本身的部件能耗问题进行分析，如车辆轮胎滚动阻力、电机效率、制动能量回收率等等；然而车辆能耗是多个方面因素综合作用的结果，不仅只由车辆本身引起的。因此采用现有技术的能耗分析方案，无法准确对车辆进行能耗分析。
发明内容
本发明实施例提供一种车辆的能耗分析方法，以提高车辆能耗分析的准确性。
本发明实施例还提供了一种车辆的能耗分析装置和车辆，以保证上述方法的实施。
为了解决上述问题，本发明公开了一种能耗的分析方法，所述的方法包括：
获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子；
基于预设周期内所述能耗参数信息进行能耗分析，确定预设周期内的能耗分析结果。
可选地，所述基于预设周期内所述能耗参数信息进行能耗分析，确定对应的能耗分析结果，包括：
分别确定预设周期内各能耗因子对应对能耗影响的权重；
依据预设周期内各能耗因子对应对能耗影响的权重进行能耗分析，确定对应的能耗分析结果。
可选地，所述分别确定预设周期内各能耗因子对应对能耗影响的权重，包括：
确定预设周期内所述车辆的百公里能耗；
将预设周期内各能耗因子作为自变量和将百公里能耗作为因变量，对自变量和因变量进行回归分析，确定预设周期内各能耗因子对应对能耗影响的权重。
可选地，所述依据预设周期内各能耗因子对应对能耗影响的权重进行能耗分析，确定对应的能耗分析结果，包括：
依据预设周期内各能耗因子对应对能耗影响的权重，确定预设周期内各能耗因子对能耗的贡献信息；
依据预设周期内各能耗因子对能耗的贡献信息，确定预设周期内的能耗分析结果。
可选地，所述能耗参数信息还包括各能耗因子的值，
所述依据预设周期内各能耗因子对应对能耗影响的权重，确定预设周期内各能耗因子对能耗的贡献信息，包括：
依据预设周期内各能耗因子对应对能耗影响的权重和各能耗因子的值进行加权计算，得到加权计算结果；
针对一个能耗因子，计算所述能耗因子的值与所述能耗因子对能耗影响的权重的乘积，得到乘积结果；
依据所述乘积结果和加权计算结果，确定预设周期内所述能耗因子对能耗的贡献信息。
可选地，所述的方法还包括：
获取上一预设周期内各能耗因子对能耗的贡献信息；
依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，生成能耗问题诊断结果。
可选地，所述依据预设周期内各能耗因子对能耗的贡献信息和上一预设 周期内各能耗因子对能耗的贡献信息，生成能耗问题诊断结果，包括：
依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，确定各能耗因子对应的贡献信息变化程度；
若各能耗因子对应的贡献信息变化程度均小于零，则依据贡献信息变化程度最大的能耗因子和第一预设规则，生成能耗问题诊断结果；
若各能耗因子对应的贡献信息变化程度均大于零，则依据贡献信息变化程度最大的能耗因子和第二预设规则，生成能耗问题诊断结果；
否则，依据贡献信息变化程度大于零的能耗因子中贡献信息变化程度最大的能耗因子、贡献信息变化程度小于零的能耗因子中贡献信息变化程度最大的能耗因子和第三预设规则，生成能耗问题诊断结果。
可选地，所述的方法还包括：
基于预设周期内所述车辆的百公里能耗，生成所述车辆预设周期内对应的能耗统计信息和能耗变化信息。
本发明实施例还提供了一种车辆的能耗分析装置，所述的装置包括：
能耗参数信息获取模块，用于获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子；
分析模块，用于基于预设周期内所述能耗参数信息进行能耗分析，确定预设周期内的能耗分析结果。
可选地，所述分析模块包括：
权重确定子模块，用于分别确定预设周期内各能耗因子对应对能耗影响的权重；
权重分析子模块，用于依据预设周期内各能耗因子对应对能耗影响的权重进行能耗分析，确定对应的能耗分析结果。
可选地，所述权重确定子模块包括：
百公里能耗确定单元，用于确定预设周期内所述车辆的百公里能耗；
回归分析单元，用于将预设周期内各能耗因子作为自变量和将百公里能耗作为因变量，对自变量和因变量进行回归分析，确定预设周期内各能耗因子对应对能耗影响的权重。
可选地，所述权重分析子模块包括：
贡献信息确定单元，用于依据预设周期内各能耗因子对应对能耗影响的 权重，确定预设周期内各能耗因子对能耗的贡献信息；
贡献信息分析单元，用于依据预设周期内各能耗因子对能耗的贡献信息，确定预设周期内的能耗分析结果。
可选地，所述能耗参数信息还包括各能耗因子的值，
所述贡献信息确定单元，用于依据预设周期内各能耗因子对应对能耗影响的权重和各能耗因子的值进行加权计算，得到加权计算结果；针对一个能耗因子，计算所述能耗因子的值与所述能耗因子对能耗影响的权重的乘积，得到乘积结果；依据所述乘积结果和加权计算结果，确定预设周期内所述能耗因子对能耗的贡献信息。
可选地，所述的装置还包括：
上一预设周期贡献信息获取模块，用于获取上一预设周期内各能耗因子对能耗的贡献信息；
能耗问题诊断结果生成模块，用于依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，生成能耗问题诊断结果。
可选地，所述能耗问题诊断结果生成模块包括：
变化程度确定子模块，用于依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，确定各能耗因子对应的贡献信息变化程度；
第一诊断结果生成子模块，用于若各能耗因子对应的贡献信息变化程度均小于零，则依据贡献信息变化程度最大的能耗因子和第一预设规则，生成能耗问题诊断结果；
第二诊断结果生成子模块，用于若各能耗因子对应的贡献信息变化程度均大于零，则依据贡献信息变化程度最大的能耗因子和第二预设规则，生成能耗问题诊断结果；
第三诊断结果生成子模块，用于否则，依据贡献信息变化程度大于零的能耗因子中贡献信息变化程度最大的能耗因子、贡献信息变化程度小于零的能耗因子中贡献信息变化程度最大的能耗因子和第三预设规则，生成能耗问题诊断结果。
可选地，所述的装置还包括：
能耗统计变化信息生成模块，用于基于预设周期内所述车辆的百公里能 耗，生成所述车辆预设周期内对应的能耗统计信息和能耗变化信息。
本发明实施例还提供了一种车辆，包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行所述一个或者一个以上程序包含用于执行如本发明实施例任一所述的车辆的能耗分析方法。
本发明实施例还提供了一种可读存储介质，当所述存储介质中的指令由电子设备的处理器执行时，使得电子设备能够执行如本发明实施例任一所述的车辆的能耗分析方法。
与现有技术相比，本发明实施例包括以下优点：
本发明实施例中，可以获取预设周期内影响车辆能耗的能耗参数信息，然后基于预设周期内能耗参数信息对车辆预设周期内的能耗进行分析，确定预设周期内的能耗分析结果；其中，能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子，进而实现通过从人、车、环境等多方面因素综合对车辆能耗进行分析，从而提高车辆能耗分析的准确性。
附图说明
图1是本发明的一种车辆的能耗分析方法实施例的步骤流程图；
图2是本发明的一种车辆的能耗分析方法可选实施例的步骤流程图；
图3是本发明的又一种车辆的能耗分析方法实施例的步骤流程图；
图4本发明的一种车辆的能耗分析装置实施例的结构框图；
图5本发明的一种车辆的能耗分析装置可选实施例的结构框图。
具体实施方式
为使本发明的上述目的、特征和优点能够更加明显易懂，下面结合附图和具体实施方式对本发明作进一步详细的说明。
本发明实施例提供的一种车辆的能耗分析方法，通过综合人、车、环境等多方面因素对车辆能耗的影响，来对车辆能耗进行分析，提高车辆能耗分析的准确性。
参照图1，示出了本发明的一种车辆的能耗分析方法实施例的步骤流程图，具体可以包括如下步骤：
步骤102、获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子。
车辆能耗是多个方面因素综合作用的结果，例如人、车和环境等多个方面因素；但是现有技术中对车辆能耗的分析，大多是针对车辆本身的部件进行的，而忽略了人和环境对车辆能耗的影响。因此，本发明实施例可以从人、车和环境等多个方面因素的综合分析车辆能耗，来提高车辆能耗分析的准确性。
本发明实施例中，当需要对车辆能耗进行分析时，可以获取预设周期内影响车辆能耗的能耗参数信息。其中，能耗参数信息可以是指影响车辆能耗的信息，可以包括影响车辆能耗的能耗因子和能耗因子的值。其中，所述能耗参数信息可以包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子。其中，所述预设周期可以是当前周期，也可以是历史任一周期；所述周期可以按照需求划分，如按照时间划分如1周，又如按照里程划分如车辆行驶500km等，本发明实施例对此不作限制。
其中，驾驶行为能耗因子可以包括在车辆行驶过程中影响车辆能耗的各种驾驶行为对应的因子，例如：加速行为因子、高速驾驶行为因子等。车辆使用行为能耗因子可以包括在车辆行驶过程中影响车辆能耗的各种车辆使用行为的因子，例如：空调温度设置因子等。环境能耗因子可以包括在车辆行驶过程中影响车辆能耗的各种环境对应的因子，例如：路面质量因子等。车辆运行能耗因子可以包括在车辆行驶过程中影响车辆能耗的各种车辆本身运行情况对应的因子，例如：低压电器能耗因子。
在本发明实施例中，所述驾驶行为能耗因子、车辆使用行为能耗因子，可以属于人对车辆能耗影响的因素；所述环境能耗因子，可以属于环境对车辆能耗影响的因素；所述车辆运行能耗因子，可以属于车辆自身对车辆能耗影响的因素。
当然，所述能耗参数信息中还可以包括其他的能耗因子，本发明实施例对此不作限制。
步骤104、基于预设周期内所述能耗参数信息进行能耗分析，确定预设周期内的能耗分析结果。
本发明实施例中，在获取到预设周期内的能耗参数信息后，可以综合能耗参数信息中的驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子，进行能耗分析，确定预设周期内的能耗分析结果。
综上，本发明实施例中，可以获取预设周期内影响车辆能耗的能耗参数信息，然后基于预设周期内能耗参数信息对车辆的预设周期内的能耗进行分析，确定预设周期内的能耗分析结果；其中，能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子，进而实现通过从人、车、环境等多方面因素综合对车辆能耗进行分析，从而提高车辆能耗分析的准确性。
在本发明实施例中，所述基于预设周期内所述能耗参数信息进行能耗分析，确定对应的能耗分析结果的步骤，包括：分别确定预设周期内各能耗因子对应对能耗影响的权重；依据预设周期内各能耗因子对应对能耗影响的权重进行能耗分析，确定对应的能耗分析结果。
其中，不同的能耗因子对于车辆能耗的影响程度不同；例如，驾驶行为能耗因子对车辆能耗的影响程度相对较大，而车辆运行能耗因子对车辆能耗的影响程度相对较小。为了进一步提高能耗分析结果的准确性，本发明实施例可以先分析各能耗因子对车辆能耗影响的权重；然后综合各能耗因子对应对能耗影响的权重进行能耗分析进行计算，确定能耗分析结果。
以下对如何确定能耗分析结果进行说明。
参照图2，示出了本发明的一种车辆的能耗分析方法可选实施例的步骤流程图，具体可以包括如下步骤：
步骤202、获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子；所述能耗参数信息还包括各能耗因子的值。
其中，驾驶行为能耗因子可以包括多个因子，如加速行为因子、减速行为因子、高速驾驶行为因子和低速驾驶行为因子等等，当然，还可以包括其他因子，本发明实施例对此不作限制。
车辆使用行为能耗因子可以包括多个因子，如能量回收模式偏好因子、 能量回收效果因子、空调运行强度因子和空调使用时长因子等等，当然，还可以包括其他因子，本发明实施例对此不作限制。
环境能耗因子可以包括多个因子，如路面质量因子、环境温度因子等等，当然，还可以包括其他因子，本发明实施例对此不作限制。
车辆运行能耗因子可以包括如低压电器能耗因子，当然，还可以包括其他因子，本发明实施例对此不作限制。
在本发明实施例中，能耗因子的值可以是指在能耗因子作用下车辆所行驶的里程或时间，占整个预设周期内总的行驶里程或总的行驶时间的比例。例如：能耗因子为高速行为因子，则可以将预设周期内，高速行驶(行驶速度大于85km/h)的行驶里程，占预设周期内的总里程数的比例的值，作为预设周期内高速行为因子的值。还例如：能耗因子为空调使用时长因子，则可以将预设周期内，车辆开启空调的时间占预设周期内总行驶时间的比例的值，作为预设周期内空调使用时长因子的值。
其中，所述分别确定预设周期内各能耗因子对应对能耗影响的权重，可以参照步骤204～步骤206：
步骤204、确定预设周期内所述车辆的百公里能耗。
其中，百公里能耗可以指车辆行驶100km所消耗的电量。
在本发明实施例中，可以先获取预设周期内每段行程的行驶里程和每段行程所消耗的电量；然后依据每段行程的行驶里程和每段行程所消耗的电量，计算出每段行程的百公里能耗；再依据每段行程的百公里能耗、每段行程的行驶里程和预设周期内车辆行驶的总里程，计算出预设周期内车辆的百公里能耗。
作为一示例，可以通过如下方式计算出所述车辆的百公里能耗：
首先，可以先获取每段行程所消耗的电量，例如：该段行程开始时，车辆剩余电量为40kW·h(千瓦时)，该段行程过程中对车辆充电电量为20kW·h，该段行程结束时，车辆剩余电量为35kW·h，则可以通过如下方式计算：
40kW·h-35kW·h+20kW·h＝25kW·h；
可以得到该段行程所消耗的电量为：25kW·h。
然后，可以根据预设周期内每段行程所消耗的电量和每段行程对应的行驶里程，计算预设周期内车辆每段行程的百公里能耗，例如：预设周期内有 4段行程，每段行程的电量消耗分别为8kW·h、5kW·h、3kW·h和1kW·h，每段行程对应的行驶里程分别为60km、40km、25km和10km，则可以通过如下方式计算：
(8kW·h/60km)*100＝13.3kW·h/百公里；
(5kW·h/40km)*100＝12.5kW·h/百公里；
(3kW·h/25km)*100＝12kW·h/百公里；
(1kW·h/10km)*100＝10kW·h/百公里；
可以得到预设周期内每段行程的百公里能耗分别为：13.3kW·h/百公里、12.5kW·h/百公里、12kW·h/百公里和10kW·h/百公里。
之后，可以根据预设周期内每段行程的百公里能耗、每段行程对应的行驶里程和预设周期内车辆每段行驶里程的总和，计算预设周期内车辆的百公里能耗，例如：预设周期内有4段行程，每段行程的百公里能耗分别为13.3kW·h/百公里、12.5kW·h/百公里、12kW·h/百公里和10kW·h/百公里；每段行程对应的行驶里程分别为60km、40km、25km和10km，则可以通过如下方式计算：
(13.3kW·h/百公里*60km+12.5kW·h/百公里*40km+12kW·h/百公里*25km+10kW·h/百公里*10km)/(60km+40km+25km+10km)＝12.7kW·h/百公里；
可以得到当前时间周期内车辆的百公里能耗为：12.7kW·h/百公里。
作为一示例，当周期按照里程划分时，可以先收集该里程起始时的车辆剩余电量；然后收集该里程内车辆充电电量，以及该里程结束时的车辆剩余电量。然后依据起始时的车辆电量、充电电量、结束时的车辆剩余电量以及预先设置的该里程的里程数，计算得到当前该里程内车辆的百公里能耗。例如：预先设置的该里程为500km，该里程开始时车辆的剩余电量为40kW·h，该里程内对车辆进行了1次充电，充电电量为50kW·h，当车辆行驶500km时，该里程结束，结束时车辆的剩余电量为28kW·h，则可以通过如下方式计算：
(40kW·h-28kW·h+50kW·h)/500km＝12.4kW·h/百公里；
可以得到当前该里程内车辆的百公里能耗为：12.4kW·h/百公里。
步骤206、将预设周期内各能耗因子作为自变量和将百公里能耗作为因变量，对自变量和因变量进行回归分析，确定预设周期内各能耗因子对应对 能耗影响的权重。
在本发明实施例中，可以先将预设周期内各能耗因子作为自变量，将预设周期内的百公里能耗作为因变量，然后对自变量和因变量进行回归分析，从而确定预设周期内各能耗因子对应的对车辆能耗影响的权重，例如：可以进行线性回归分析、非线性回归分析，也可以进行其他回归分析，本发明实施例对此不做限制。
步骤208、依据预设周期内各能耗因子对应对能耗影响的权重，确定预设周期内各能耗因子对能耗的贡献信息。
本发明实施例中，在确定预设周期内各能耗因子对应的对能耗影响的权重后，可以依据权重，确定预设周期内各能耗因子对能耗的贡献信息；其中，贡献信息可以指在预设周期内，各能耗因子对能耗的贡献程度。
在本发明的实施例中，步骤208可以包括如下子步骤：
子步骤2082、依据预设周期内各能耗因子对应对能耗影响的权重和各能耗因子的值进行加权计算，得到加权计算结果。
在本发明实施例中，在确定各能耗因子对应对能耗影响的权重后，可以依据各能耗因子的权重和各能耗因子的值进行加权计算，从而得到加权计算结果，例如：预设周期内各能耗因子对应对能耗影响的权重分别为25％、25％、30％、20％，各能耗因子的值分别为0.78、0.75、0.54、0.08，则可以通过如下方式计算：
(25％*0.78)+(25％*0.75)+(30％*0.54)+(20％*0.08)＝0.56
可以得到加权计算结果为：0.56。
子步骤2084、针对一个能耗因子，计算所述能耗因子的值与所述能耗因子对能耗影响的权重的乘积，得到乘积结果。
在本发明实施例中，可以针对每一个能耗因子，将每个能耗因子的值与其对应的权重相乘，从而得到乘积结果，例如：预设周期内各能耗因子对应对能耗影响的权重分别为25％、25％、30％、20％，各能耗因子的值分别为0.78、0.75、0.54、0.08，则可以通过如下方式计算：
25％*0.78＝0.195；
25％*0.75＝0.187；
30％*0.54＝0.162；
20％*0.08＝0.016；
可以得到各能耗因子的乘积结果分别为：0.195、0.187、0.162和0.016。
子步骤2086、依据所述乘积结果和加权计算结果，确定预设周期内所述能耗因子对能耗的贡献信息。
在本发明实施例中，在得到乘积结果后，可以针对每个能耗因子，依据每个能耗因子的乘积结果与加权计算结果，确定预设周期内，每个能耗因子对能耗的贡献信息。
作为一示例，可以通过计算每个能耗因子的乘积结果与加权计算结果的比值，得到每个能耗因子对能耗的贡献信息。
在本发明实施例中，为了得到更直观的每个能耗因子对能耗的贡献信息，还可以计算贡献信息与预设周期内车辆的百公里能耗的乘积，得到预设周期内，每个能耗因子对百公里能耗的贡献值，例如：百公里能耗为12.5kW·h/百公里，计算得到加速行为因子的贡献值为1kW·h/百公里，则该贡献值可以指为“车辆行驶百公里所消耗的电量12.5kW·h中，加速行为因子消耗了其中的1kW·h”。
作为本发明的一个示例，如下表1中，
预设周期内的能耗因子包括：加速行为因子、高速驾驶行为因子、低速驾驶行为因子、运动模式偏好因子、能量回收模式偏好因子、能量回收效果因子、空调运行强度因子、空调使用时长因子、低压电器能耗因子和路面质量因子；预设周期内车辆的百公里能耗为12.1kW·h/百公里。
各能耗因子的值分别为：0.78、0.75、0.01、0.54、0.08、0.03、0.9、0.4、0.29和0.98；
各能耗因子对应对能耗影响的分别为：10％、4％、20％、21％、13％、8％、1％、7％、2％和14％；
计算得到加权计算结果为：0.416；
计算针对每个能耗因子的乘积结果分别为：0.078、0.03、0.002、0.113、0.010、0.002、0.009、0.028、0.006和0.137；
依据加权计算结果和乘积结果，计算得到每个能耗因子对能耗的贡献信息分别为：0.187、0.072、0.005、0.272、0.025、0.006、0.022、0.067、0.014和0.330。
计算贡献信息与预设周期内车辆的百公里能耗的乘积，得到每个能耗因子对百公里能耗的贡献值分别为：2.268kW·h/百公里、0.872kW·h/百公 里、0.058kW·h/百公里、3.297kW·h/百公里、0.302kW·h/百公里、0.070kW·h/百公里、0.262kW·h/百公里、0.814kW·h/百公里、0.169kW·h/百公里和3.989kW·h/百公里。
表一：
Figure PCTCN2021118049-appb-000001
Figure PCTCN2021118049-appb-000002
在本发明实施例中，在确定预设周期内能耗因子对能耗的贡献信息后，可以将所得到的能耗因子对能耗的贡献信息存储，以便后续对车辆的历史能耗进行分析。
步骤210、依据预设周期内各能耗因子对能耗的贡献信息，确定预设周期内的能耗分析结果。
在本发明实施例中，在确定预设周期内各能耗因子对能耗的贡献信息后，可以直接将预设周期内各能耗因子对能耗的贡献信息，确定为预设周期内的能耗分析结果。也可以依据预设周期内各能耗因子对能耗的贡献信息，生成图表；将生成的图表，确定为预设周期内的能耗分析结果；本发明实施例对此不作限制。
本发明的一个可选实施例中，可以在车辆显示设备如中控屏中，显示预设周期内的能耗分析结果，以向用户提供更为清楚的能耗分析结果。
在确定预设周期内的能耗分析结果后，还可以将该能耗分析结果存储，以便后续对车辆的历史能耗进行分析时，能够直接依据所存储的能耗分析结果进行分析。
综上，在本发明实施例中，对预设周期内车辆的百公里能耗和各能耗因子进行回归分析，确定预设周期内各能耗因子对应对能耗影响的权重，并基于权重得出能耗分析结果；进而进一步提高了能耗分析结果的准确性。
此外，本发明实施例中，可以依据权重和各能耗因子的值计算出各能耗因子对能耗的贡献信息，以及依据贡献信息生成能耗分析结果，让用户能够依据能耗分析结果知晓预设周期内有哪些能耗因子对车辆的能耗影响较大，以便用户能够有针对性的对车辆的使用作出改进。
参照图3，示出了本发明的又一种车辆的能耗分析方法可选实施例的步骤流程图，具体可以包括如下步骤：
步骤302、获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子；所述能耗参数信息还包括各能耗因子的 值。
步骤304、确定预设周期内所述车辆的百公里能耗。
步骤306、将预设周期内各能耗因子作为自变量和将百公里能耗作为因变量，对自变量和因变量进行回归分析，确定预设周期内各能耗因子对应对能耗影响的权重。
步骤308、依据预设周期内各能耗因子对应对能耗影响的权重，确定预设周期内各能耗因子对能耗的贡献信息。
步骤310、依据预设周期内各能耗因子对能耗的贡献信息，确定预设周期内的能耗分析结果。
步骤302-步骤310与上述步骤202-步骤210类似，在此不再赘述。
在本发明的实施例中，还可以包括如下步骤：
步骤312、获取上一预设周期内各能耗因子对能耗的贡献信息。
步骤314、依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，生成能耗问题诊断结果。
在本发明实施例中，还可以获取当前车辆的上一预设周期内各能耗因子对能耗的贡献信息；然后可以通过比对预设周期内各能耗因子对能耗的贡献信息，和上一预设周期内各能耗因子对能耗的贡献信息，确定预设周期内各能耗因子对能耗的贡献信息，相较于上一预设周期内各能耗因子对能耗的贡献信息的变化程度；再依据变化程度，对车辆的能耗问题进行分析诊断，并依据分析诊断的结果生成一能耗问题诊断结果。
本发明的一个示例中，可以通过如下方式计算各能耗因子对应的贡献信息变化程度：
贡献信息变化程度＝预设周期的能耗因子对能耗的贡献信息-上一预设周期的能耗因子对能耗因子对能耗的贡献信息。
作为一示例，若各能耗因子对应的贡献信息变化程度均小于零，则依据贡献信息变化程度最大的能耗因子和第一预设规则，生成能耗问题诊断结果。
其中，可以预先设置第一预设规则，第一预设规则可以是指针对预设周期中各能耗因子的贡献信息相对于上一预设周期各耗能因子的贡献信息降低的能耗问题诊断结果；可以包括第一预设能耗问题诊断结果模板，所述第一预设能耗问题诊断结果模板中包括贡献信息变化程度最大的能耗因子。所 述第一预设能耗问题诊断结果模板如“太棒了！本期监控的能耗因子全面改善，其中**因子(即贡献信息变化程度最大的能耗因子)下降尤其明显，请继续保持”。
如果各能耗因子对应的贡献信息变化程度均小于零，则可以认为预设周期的能耗比上一预设周期的能耗相对来说有所降低；此时，可以确定预设周期对比上一预设周期中，贡献信息变化程度最大的能耗因子；然后再依据贡献信息变化程度最大的能耗因子和第一预设能耗问题诊断结果模板，生成一能耗问题诊断结果。例如：贡献信息变化程度最大的能耗因子为“加速行为因子”，则可以生成如下能耗问题诊断结果“太棒了！本期监控的能耗因子全面改善，其中加速行为因子下降尤其明显，请继续保持”。然后可以在车辆的显示设备中显示该能耗问题诊断结果。
作为又一示例，若各能耗因子对应的贡献信息变化程度均大于零，则依据贡献信息变化程度最大的能耗因子和第二预设规则，生成能耗问题诊断结果。
其中，可以预先设置第二预设规则，第二预设规则可以是针对预设周期中各能耗因子的贡献信息相对于上一预设周期各能耗因子的贡献信息升高的能耗问题诊断结果；可以包括第二预设能耗问题诊断结果模板，所述第二预设能耗问题诊断结果模板中包括贡献信息变化程度最大的能耗因子。所述第二预设能耗问题诊断结果模板如“很糟糕！本期监控的能耗因子全面不佳，其中**因子(即贡献信息变化程度最大的能耗因子)增加尤其明显，请留意”。
如果各能耗因子对应的贡献信息变化程度均大于零，则可以认为预设周期的能耗比上一预设周期的能耗相对来说有所升高；此时，可以确定预设周期对比上一预设周期中，贡献信息变化程度最大的能耗因子；然后再依据贡献信息变化程度最大的能耗因子和第二预设能耗问题诊断结果模板，生成一能耗问题诊断结果。例如：贡献信息变化程度最大的能耗因子为“路面质量因子”，则可以生成如下能耗问题诊断结果“很糟糕！本期监控的能耗因子全面不佳，其中路面质量因子增加尤其明显，请留意”。然后可以在车辆的显示设备中显示该能耗问题诊断结果。
作为再一示例，否则，依据贡献信息变化程度大于零的能耗因子中贡献信息变化程度最大的能耗因子、贡献信息变化程度小于零的能耗因子中贡献信息变化程度最大的能耗因子和第三预设规则，生成能耗问题诊断结果。
其中，可以预先设置第三预设规则，第三预设规则可以是针对预设周期中部分能耗因子的贡献信息相对于上一预设周期对应的能耗因子的贡献信息降低，和另一部分能耗因子的贡献信息相对于上一预设周期对应的能耗因子的贡献信息升高的能耗问题诊断结果；可以包括第三预设能耗问题诊断结果模板，所述第三预设能耗问题诊断结果模板中包括降低部分的能耗因子中贡献信息变化程度最大的能耗因子，和升高部分的能耗因子中贡献信息变化程度最大的能耗因子。所述第三预设能耗问题诊断结果模板如“本期**因子(即降低部分的能耗因子中贡献信息变化程度最大的能耗因子)改善明显，请继续保持；本期**因子(即升高部分的能耗因子中贡献信息变化程度最大的能耗因子)表现不佳，请留意”。
如果部分能耗因子对应的贡献信息变化程度大于零，另一部分能耗因子对应的贡献信息变化程度小于零，则可以认为预设周期的部分能耗因子对能耗的影响有所降低，另一部分能耗因子对能耗的影响有所升高；此时，可以确定预设周期对比上一预设周期中，贡献信息变化程度大于零的能耗因子中贡献信息变化程度最大的能耗因子，和贡献信息变化程度小于零的能耗因子中贡献信息变化程度最大的能耗因子；然后再依据贡献信息变化程度大于零的能耗因子中贡献信息变化程度最大的能耗因子、贡献信息变化程度小于零的能耗因子中贡献信息变化程度最大的能耗因子，以及第三预设能耗问题诊断结果模板，生成一能耗诊断问题诊断结果。例如：贡献信息变化程度小于零的能耗因子中贡献信息变化信息最大的能耗因子为“运动模式偏好因子”，贡献信息变化程度大于零的能耗因子中贡献信息变化程度最大的能耗因子为“低压电器能耗因子”，则可以生成如下能耗问题诊断结果“本期运动模式偏好因子改善明显，请继续保持；本期低压电器能耗因子表现不佳，请留意”。然后可以在车辆的显示设备中显示该能耗问题诊断结果。
在本发明实施例中，在确定预设周期内所述车辆的百公里能耗后，还可以进行如下步骤：
基于预设周期内所述车辆的百公里能耗，生成所述车辆预设周期内对应的能耗统计信息和能耗变化信息。
在本发明实施例中，在确定预设周期内车辆的百公里能耗后，可以采用车辆的百公里能耗，生成能耗统计信息；然后在车辆的显示设备中显示该能 耗统计信息，以告知用户预设周期内车辆的能耗使用情况；还可以将该能耗统计信息存储，以便后续对车辆的能耗使用情况进行分析。
作为一示例，统计信息中还可以包括：本次周期内车辆行驶的里程数、能耗成本等，本发明实施例对此不作限制。
在本发明实施例中，还可以基于预设周期内车辆的百公里能耗，生成该车辆预设周期内对应的能耗变化信息。
在本发明实施例中，可以确定预设周期内中，每个时间段内的车辆的百公里能耗，例如，预设周期为一周，预设周期内的每个时间段可以为一天；然后采用预设周期内中，每个时间段内的车辆的百公里能耗，生成能耗变化信息。然后在车辆的显示设备中显示该能耗变化信息，以便于用户知晓车辆能耗的变化情况。
作为一示例，能耗变化信息还可以包括：上一预设周期内中，每个时间段内的车辆的百公里能耗；本周期的百公里能耗相比上一周期的百公里能耗升高(或降低)的程度等，本发明实施例对此不作限制。
作为一示例，还可以获取其他同系列车辆的百公里能耗，采用本车辆与其他同系列车辆的百公里能耗的比对结果，生成能耗变化信息，以告知用户自己的车辆与其他同系列车辆的百公里能耗的差别，判断当前能耗的变化情况是否为个例。
在本发明实施例中，可以预先设置多个能耗变化特征规则，当预设周期相对于上一预设周期的百公里能耗发生变化时，可以基于能耗变化匹配其所符合的能耗变化特征规则，然后依据所匹配的能耗变化特征规则生成一能耗变化信息。
作为一示例，预先设置的多个能耗变化特征规则可以包括：规则一：能耗拨动，近几个周期内能耗波动大；规则二：能耗突变，本周期能耗增加或下降较大；规则三：排名突变，在同系列车辆的能耗排位中，本周期能耗排位变化较大；规则四：能耗维持，近几周期能耗保持在一定区间内；规则五：能耗新低或新高，本周期能耗处于历史最低或最高，本发明实施例对此不作限制。
在本发明实施例中，在确定依据何种规则生成一能耗变化信息时，可以按照所符合的能耗变化特征规则出现的时间顺序，优先选择最近符合的一条能耗变化特征规则来生成能耗变化信息，本发明实施例对此不作限制。
综上，本发明实施例中，可以获取上一预设周期内各能耗因子对能耗的贡献信息，然后将其与预设周期内各能耗因子对能耗的贡献信息进行比较，然后依据比较结果生成能耗问题诊断结果，从而告知用户车辆当前所存在的能耗问题，以便用户能够依据诊断结果对车辆的使用进行优化。
此外，依据车辆的百公里能耗，生成能耗统计信息和能耗变化信息，使得用户能够了解车辆能耗的使用情况，以及车辆能耗的变化情况。
需要说明的是，对于方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明实施例并不受所描述的动作顺序的限制，因为依据本发明实施例，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作并不一定是本发明实施例所必须的。
参照图4，示出了本发明一种车辆的能耗分析装置实施例的结构框图，具体可以包括如下模块：
能耗参数信息获取模块402，用于获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子；
分析模块404，用于基于预设周期内所述能耗参数信息进行能耗分析，确定预设周期内的能耗分析结果。
参照图5，示出了本发明一种车辆的能耗分析装置可选实施例的结构框图，具体可以包括如下模块：
本发明的一个可选实施例中，所述分析模块404包括：
权重确定子模块4042，用于分别确定预设周期内各能耗因子对应对能耗影响的权重；
权重分析子模块4044，用于依据预设周期内各能耗因子对应对能耗影响的权重进行能耗分析，确定对应的能耗分析结果。
本发明的一个可选实施例中，所述权重确定子模块4042包括：
百公里能耗确定单元40422，用于确定预设周期内所述车辆的百公里能耗；
回归分析单元40424，用于将预设周期内各能耗因子作为自变量和将百 公里能耗作为因变量，对自变量和因变量进行回归分析，确定预设周期内各能耗因子对应对能耗影响的权重。
本发明的一个可选实施例中，所述权重分析子模块4044包括：
贡献信息确定单元40442，用于依据预设周期内各能耗因子对应对能耗影响的权重，确定预设周期内各能耗因子对能耗的贡献信息；
贡献信息分析单元40444，用于依据预设周期内各能耗因子对能耗的贡献信息，确定预设周期内的能耗分析结果。
本发明的一个可选实施例中，所述能耗参数信息还包括各能耗因子的值，
所述贡献信息确定单元40442，用于依据预设周期内各能耗因子对应对能耗影响的权重和各能耗因子的值进行加权计算，得到加权计算结果；针对一个能耗因子，计算所述能耗因子的值与所述能耗因子对能耗影响的权重的乘积，得到乘积结果；依据所述乘积结果和加权计算结果，确定预设周期内所述能耗因子对能耗的贡献信息。
本发明的一个可选实施例中，所述的装置还包括：
上一预设周期贡献信息获取模块406，用于获取上一预设周期内各能耗因子对能耗的贡献信息；
能耗问题诊断结果生成模块408，用于依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，生成能耗问题诊断结果。
本发明的一个可选实施例中，所述能耗问题诊断结果生成模块408包括：
变化程度确定子模块4082，用于依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，确定各能耗因子对应的贡献信息变化程度；
第一诊断结果生成子模块4084，用于若各能耗因子对应的贡献信息变化程度均小于零，则依据贡献信息变化程度最大的能耗因子和第一预设规则，生成能耗问题诊断结果；
第二诊断结果生成子模块4086，用于若各能耗因子对应的贡献信息变化程度均大于零，则依据贡献信息变化程度最大的能耗因子和第二预设规则，生成能耗问题诊断结果；
第三诊断结果生成子模块4088，用于否则，依据贡献信息变化程度大于 零的能耗因子中贡献信息变化程度最大的能耗因子、贡献信息变化程度小于零的能耗因子中贡献信息变化程度最大的能耗因子和第三预设规则，生成能耗问题诊断结果。
本发明的一个可选实施例中，所述的装置还包括：
能耗统计变化信息生成模块410，用于基于预设周期内所述车辆的百公里能耗，生成所述车辆预设周期内对应的能耗统计信息和能耗变化信息。
综上，本发明实施例中，可以获取预设周期内影响车辆能耗的能耗参数信息，然后基于预设周期内能耗参数信息对车辆预设周期内的能耗进行分析，确定预设周期内的能耗分析结果；其中，能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子，进而实现通过从人、车、环境等多方面因素综合对车辆能耗进行分析，从而提高车辆能耗分析的准确性。
对于装置实施例而言，由于其与方法实施例基本相似，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
本发明实施例还提供了一种车辆，包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行所述一个或者一个以上程序包含用于执行如本发明实施例任一所述的车辆的能耗分析方法。
本发明实施例还提供了一种可读存储介质，当所述存储介质中的指令由电子设备的处理器执行时，使得电子设备能够执行如本发明实施例任一所述的车辆的能耗分析方法。
本说明书中的各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似的部分互相参见即可。
本领域内的技术人员应明白，本发明实施例的实施例可提供为方法、装置、或计算机程序产品。因此，本发明实施例可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明实施例是参照根据本发明实施例的方法、终端设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理终端设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理终端设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理终端设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理终端设备上，使得在计算机或其他可编程终端设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程终端设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本发明实施例的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例做出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明实施例范围的所有变更和修改。
最后，还需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者终端设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者终端设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者终端设备中还存在另外的相同要素。
以上对本发明所提供的一种车辆的能耗分析方法和一种车辆的能耗分 析装置，进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (11)

  1. 一种车辆的能耗分析方法，其特征在于，所述的方法包括：
    获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用行为能耗因子、环境能耗因子和车辆运行能耗因子；
    基于预设周期内所述能耗参数信息进行能耗分析，确定预设周期内的能耗分析结果。
  2. 根据权利要求1所述的方法，其特征在于，所述基于预设周期内所述能耗参数信息进行能耗分析，确定对应的能耗分析结果，包括：
    分别确定预设周期内各能耗因子对应对能耗影响的权重；
    依据预设周期内各能耗因子对应对能耗影响的权重进行能耗分析，确定对应的能耗分析结果。
  3. 根据权利要求2所述的方法，其特征在于，所述分别确定预设周期内各能耗因子对应对能耗影响的权重，包括：
    确定预设周期内所述车辆的百公里能耗；
    将预设周期内各能耗因子作为自变量和将百公里能耗作为因变量，对自变量和因变量进行回归分析，确定预设周期内各能耗因子对应对能耗影响的权重。
  4. 根据权利要求2所述的方法，其特征在于，所述依据预设周期内各能耗因子对应对能耗影响的权重进行能耗分析，确定对应的能耗分析结果，包括：
    依据预设周期内各能耗因子对应对能耗影响的权重，确定预设周期内各能耗因子对能耗的贡献信息；
    依据预设周期内各能耗因子对能耗的贡献信息，确定预设周期内的能耗分析结果。
  5. 根据权利要求4所述的方法，其特征在于，所述能耗参数信息还包括各能耗因子的值，
    所述依据预设周期内各能耗因子对应对能耗影响的权重，确定预设周期内各能耗因子对能耗的贡献信息，包括：
    依据预设周期内各能耗因子对应对能耗影响的权重和各能耗因子的值进行加权计算，得到加权计算结果；
    针对一个能耗因子，计算所述能耗因子的值与所述能耗因子对能耗影响的权重的乘积，得到乘积结果；
    依据所述乘积结果和加权计算结果，确定预设周期内所述能耗因子对能耗的贡献信息。
  6. 根据权利要求5所述的方法，其特征在于，所述的方法还包括：
    获取上一预设周期内各能耗因子对能耗的贡献信息；
    依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，生成能耗问题诊断结果。
  7. 根据权利要求6所述的方法，其特征在于，所述依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，生成能耗问题诊断结果，包括：
    依据预设周期内各能耗因子对能耗的贡献信息和上一预设周期内各能耗因子对能耗的贡献信息，确定各能耗因子对应的贡献信息变化程度；
    若各能耗因子对应的贡献信息变化程度均小于零，则依据贡献信息变化程度最大的能耗因子和第一预设规则，生成能耗问题诊断结果；
    若各能耗因子对应的贡献信息变化程度均大于零，则依据贡献信息变化程度最大的能耗因子和第二预设规则，生成能耗问题诊断结果；
    否则，依据贡献信息变化程度大于零的能耗因子中贡献信息变化程度最大的能耗因子、贡献信息变化程度小于零的能耗因子中贡献信息变化程度最大的能耗因子和第三预设规则，生成能耗问题诊断结果。
  8. 根据权利要求3所述的方法，其特征在于，所述的方法还包括：
    基于预设周期内所述车辆的百公里能耗，生成所述车辆预设周期内对应的能耗统计信息和能耗变化信息。
  9. 一种车辆的能耗分析装置，其特征在于，所述的装置包括：
    能耗参数信息获取模块，用于获取预设周期内影响车辆能耗的能耗参数信息，所述能耗参数信息包括以下能耗因子：驾驶行为能耗因子、车辆使用 行为能耗因子、环境能耗因子和车辆运行能耗因子；
    分析模块，用于基于预设周期内所述能耗参数信息进行能耗分析，确定预设周期内的能耗分析结果。
  10. 一种车辆，其特征在于，包括有存储器，以及一个或者一个以上的程序，其中一个或者一个以上程序存储于存储器中，且经配置以由一个或者一个以上处理器执行所述一个或者一个以上程序包含用于执行如方法权利要求1-8任一所述的车辆的能耗分析方法。
  11. 一种可读存储介质，其特征在于，当所述存储介质中的指令由电子设备的处理器执行时，使得电子设备能够执行如方法权利要求1-8任一所述的车辆的能耗分析方法。
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