WO2024073939A1 - 增程式车辆的功率控制方法及装置 - Google Patents

增程式车辆的功率控制方法及装置 Download PDF

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WO2024073939A1
WO2024073939A1 PCT/CN2022/137904 CN2022137904W WO2024073939A1 WO 2024073939 A1 WO2024073939 A1 WO 2024073939A1 CN 2022137904 W CN2022137904 W CN 2022137904W WO 2024073939 A1 WO2024073939 A1 WO 2024073939A1
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vehicle
speed
power
target
term
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PCT/CN2022/137904
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English (en)
French (fr)
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徐康
孔彩霞
张宝成
赵瑞
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合众新能源汽车股份有限公司
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Publication of WO2024073939A1 publication Critical patent/WO2024073939A1/zh

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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
    • B60W20/00—Control systems specially adapted for hybrid vehicles
    • B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L50/00—Electric propulsion with power supplied within the vehicle
    • B60L50/50—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells
    • B60L50/60—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using power supplied by batteries
    • B60L50/61—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using power supplied by batteries by batteries charged by engine-driven generators, e.g. series hybrid electric vehicles
    • B60L50/62—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using power supplied by batteries by batteries charged by engine-driven generators, e.g. series hybrid electric vehicles charged by low-power generators primarily intended to support the batteries, e.g. range extenders
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • 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
    • B60W40/02—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 related to ambient conditions
    • B60W40/04—Traffic conditions
    • 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
    • B60W40/08—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 related to drivers or passengers
    • B60W40/09—Driving style or behaviour
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • 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
    • Y02T10/62—Hybrid vehicles

Definitions

  • the present application relates to the field of vehicle technology, and in particular to a power control method and device for an extended-range vehicle.
  • the embodiments of the present application provide a power control method and device for an extended-range vehicle, the main purpose of which is to solve the problem that when the existing power control method relies on road condition matching, the matching degree is low under new road conditions, resulting in low power control accuracy of the extended-range vehicle.
  • the present application provides a power control method for an extended-range vehicle, the method comprising:
  • a vehicle speed change characteristic based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and determine a global predicted vehicle speed of the target vehicle in a target route based on the vehicle speed change characteristic and traffic flow information, wherein the traffic flow information is used to characterize an average vehicle speed of other vehicles in the target route, the vehicle speed change limit is used to characterize a maximum speed allowed by the target vehicle during acceleration or deceleration, and the vehicle driving style is used to characterize a speed change of the target vehicle during acceleration or deceleration;
  • the short-term predicted vehicle speed of the target vehicle based on the first speed information, the second speed information and the traffic flow information of the target vehicle, wherein the first speed information is a set of running speeds of the target vehicle collected in each time unit in the past target period, and the second speed is an average value of all the running speeds in the past target period;
  • the real-time required power of the target vehicle is predicted so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power.
  • the vehicle speed change characteristic includes a speed change correction parameter
  • the determining of the vehicle speed change characteristics based on the vehicle driving style and the vehicle speed change limit of the target vehicle, and determining the global predicted vehicle speed of the target vehicle in the target route based on the vehicle speed change characteristics and traffic flow information includes:
  • the traffic flow information is corrected according to the speed change correction parameter to obtain the global predicted vehicle speed.
  • the preset speed-power relationship includes a vehicle dynamics formula
  • the determining of the global expected power of the target vehicle based on the global predicted vehicle speed and the preset speed-power relationship, and determining the long-term control strategy of the target vehicle based on the global expected power comprises:
  • the equivalent fuel factor of the target vehicle is determined according to the global expected power and the equivalent fuel control strategy, and the long-term control strategy of the target vehicle is determined based on the equivalent fuel factor; wherein the equivalent fuel control strategy is used to control the control rules between fuel and electric energy when the target vehicle is traveling in the most economical way, and the equivalent fuel factor is the oil-to-electricity output ratio that meets the requirements of the target vehicle traveling on the target route.
  • determining the short-term predicted vehicle speed of the target vehicle based on the first speed information, the second speed information and the traffic flow information of the target vehicle includes:
  • the short-term predicted vehicle speed is obtained by performing a prediction operation based on the first speed information, the second speed information and the traffic flow information and by using the preset short-term vehicle speed prediction model, wherein the preset short-term vehicle speed prediction model is a vehicle speed prediction model obtained by training based on a preset neural network algorithm, and the preset neural network algorithm includes a nonlinear autoregressive neural network algorithm and a long short-term memory neural network algorithm.
  • determining the short-term expected power of the target vehicle based on the short-term predicted vehicle speed and the preset speed-power relationship, and generating a range extender start suggestion based on the short-term expected power and a preset power threshold includes:
  • the method before predicting the real-time required power of the target vehicle based on the global expected power, the short-term expected power and the range extender start suggestion in combination with a preset power prediction algorithm, the method further includes:
  • the predicting the real-time required power of the target vehicle based on the global expected power, the short-term expected power and the range extender start suggestion in combination with a preset power prediction algorithm includes:
  • the actual required power of the range extender is determined as the real-time required power.
  • the present application further provides a power control device for an extended-range vehicle, comprising:
  • a first determination unit configured to determine a vehicle speed change characteristic based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and determine a global predicted vehicle speed of the target vehicle in a target route based on the vehicle speed change characteristic and traffic flow information, wherein the traffic flow information is used to characterize an average vehicle speed of other vehicles in the target route, the vehicle speed change limit is used to characterize a maximum speed allowed by the target vehicle during acceleration or deceleration, and the vehicle driving style is used to characterize a speed change of the target vehicle during acceleration or deceleration;
  • a second determination unit configured to determine a global expected power of the target vehicle based on the global predicted vehicle speed and a preset speed-power relationship, and determine a long-term control strategy of the target vehicle based on the global expected power;
  • a third determining unit is used to determine the short-term predicted vehicle speed of the target vehicle based on the first speed information, the second speed information and the traffic flow information of the target vehicle, wherein the first speed information is a set of running speeds of the target vehicle collected in each time unit in a past target period, and the second speed is an average value of all the running speeds in the past target period;
  • a fourth determination unit configured to determine the short-term expected power of the target vehicle based on the short-term predicted vehicle speed and the preset speed-power relationship, and generate a range extender start suggestion based on the short-term expected power and a preset power threshold;
  • a prediction unit is used to predict the real-time power demand of the target vehicle based on the global expected power, the short-term expected power and the range extender start suggestion in combination with a preset power prediction algorithm, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time power demand.
  • the vehicle speed change characteristic includes a speed change correction parameter
  • the first determining unit includes:
  • a determination module configured to obtain historical driving data of the target vehicle and determine the driving style of the vehicle based on the historical driving data
  • An extraction module used for acquiring vehicle information of the target vehicle and extracting the vehicle speed limit value from the vehicle information
  • a first correction module configured to correct the vehicle speed limit value based on the vehicle driving style to obtain the speed correction parameter
  • an acquisition module configured to acquire the current driving information of the target vehicle, and based on the target route, acquire the driving data of other vehicles on the target route, and then determine the average vehicle speed as the traffic flow information based on the driving data, wherein the driving information at least includes the target route;
  • the second correction module is used to correct the traffic flow information according to the speed change correction parameter to obtain the global predicted vehicle speed.
  • the preset speed-power relationship includes a vehicle dynamics formula
  • the second determining unit includes:
  • a calculation module used for calculating the global expected power of the target vehicle by using the vehicle dynamics formula and the global predicted vehicle speed;
  • a determination module is used to determine the equivalent fuel factor of the target vehicle according to the global expected power and the equivalent fuel control strategy, and determine the long-term control strategy of the target vehicle based on the equivalent fuel factor; wherein the equivalent fuel control strategy is used to control the control rules between fuel and electric energy when the target vehicle is traveling in the most economical way, and the equivalent fuel factor is the oil-electricity output ratio that meets the requirements of the target vehicle traveling on the target route.
  • the third determining unit includes:
  • an extraction module configured to obtain the travel data of the target vehicle on the target route, extract the travel speed corresponding to each unit time in the target time period based on the travel data, and determine the multiple travel speeds corresponding to the target time period as the first speed information
  • a calculation module configured to calculate an average value according to all the driving speeds in the first speed information as the second speed information
  • a prediction module is used to perform a prediction operation based on the first speed information, the second speed information and the traffic flow information, and to obtain the short-term predicted vehicle speed by using the preset short-term vehicle speed prediction model, wherein the preset short-term vehicle speed prediction model is a vehicle speed prediction model obtained by training based on a preset neural network algorithm, and the preset neural network algorithm includes a nonlinear autoregressive neural network algorithm and a long short-term memory neural network algorithm.
  • the fourth determining unit includes:
  • a calculation module used for calculating the short-term expected power of the target vehicle by using the vehicle dynamics formula and the short-term predicted vehicle speed;
  • a first execution module configured to determine to start the range extender if it is determined that the short-term expected power exceeds the preset power threshold
  • the second execution module is used to determine to shut down the range extender if it is determined that the short-term expected power does not exceed the preset power threshold.
  • the device further comprises:
  • an acquisition unit used to acquire vehicle status information, and extract range extender status information and battery status information from the vehicle status information
  • the prediction unit is specifically used to determine the actual required power of the range extender as the real-time required power according to the global expected power, the short-term expected power, the range extender startup suggestion, the range extender status information and the battery status information, in combination with the preset power prediction algorithm.
  • an embodiment of the present application provides a storage medium, which includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the power control method for the extended-range vehicle described in any one of the first aspects.
  • an embodiment of the present application provides a power control device for an extended-range vehicle, the device comprising a storage medium; and one or more processors, the storage medium being coupled to the processor, the processor being configured to execute program instructions stored in the storage medium; when the program instructions are executed, the power control method for the extended-range vehicle described in any one of the first aspects is executed.
  • the technical solution provided by this application has at least the following advantages:
  • the present application provides a power control method and device for an extended-range vehicle.
  • the present application first determines a vehicle speed change characteristic based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and determines a global predicted vehicle speed of the target vehicle in a target route based on the vehicle speed change characteristic and traffic flow information. Then, based on the global predicted vehicle speed and a preset speed-power relationship, the global expected power of the target vehicle is determined, and a long-term control strategy of the target vehicle is determined based on the global expected power. Then, based on first speed information, second speed information and traffic flow information of the target vehicle, the short-term predicted vehicle speed of the target vehicle is determined.
  • the short-term expected power of the target vehicle is determined, and a range extender start suggestion is generated based on the short-term expected power and a preset power threshold.
  • the real-time required power of the target vehicle is predicted, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power, thereby realizing the power control function of the extended-range vehicle.
  • the global predicted power determined in the present application is determined based on the global predicted vehicle speed determined based on the vehicle speed change characteristics and traffic flow characteristics, and the traffic flow information is used to characterize the average speed of other vehicles on the target route, that is, the driving conditions of other vehicles are combined when determining the global predicted vehicle speed, and the vehicle speed change characteristics are determined based on the vehicle speed change limit and the vehicle driving style, the vehicle speed change limit is used to characterize the maximum speed allowed by the target vehicle during acceleration or deceleration, and the vehicle driving style is used to characterize the speed change of the target vehicle during acceleration or deceleration.
  • the vehicle speed change characteristics can reflect the characteristics of the speed change of the current vehicle during driving, so it can be ensured that the global predicted vehicle speed can take into account the driving characteristics of the current vehicle and the driving conditions of other vehicles on the same route, so that while reflecting the driving characteristics of the current vehicle, the global predicted vehicle speed of the vehicle on the entire route can be determined without the vehicle traveling on the current route, thereby ensuring the accuracy of the global expected power, without considering the matching process of the current road conditions, and improving the accuracy of vehicle power control.
  • the first speed information is a collection of the running speeds collected by the target vehicle in each time unit in the past target period
  • the second speed is the average value of all the running speeds in the past target period, that is, in the process of determining the short-term predicted speed, the driving conditions of the vehicle before the current moment can be taken into account and combined with the possible driving conditions of other vehicles after the current moment to make a short-term predicted speed prediction, thereby ensuring the accuracy of the prediction result, and thus ensuring the accuracy of the short-term expected power, and then laying the foundation for determining the accuracy of the range extender start suggestion based on the comparison between the short-term expected power and the preset power threshold.
  • the real-time required working power of the target vehicle is determined based on the global expected power, the short-term expected power and the range extender start suggestion, which can ensure that in the process of determining the vehicle working condition, both the power demand during long-term operation and the short-term power demand can be taken into account, and on this basis, power management can be performed based on the range extender start suggestion, thereby determining the accuracy of the power control of the range extender vehicle.
  • FIG1 shows a flow chart of a power control method for an extended-range vehicle provided in an embodiment of the present application
  • FIG2 shows a flow chart of another power control method for an extended-range vehicle provided in an embodiment of the present application
  • FIG3 shows a block diagram of a power control device for a range-extended vehicle provided in an embodiment of the present application
  • FIG4 shows a block diagram of another power control device for an extended-range vehicle provided in an embodiment of the present application.
  • the embodiment of the present application provides a power control method for an extended-range vehicle, as shown in FIG1 , the method includes:
  • the traffic flow information is used to characterize the average speed of other vehicles on the target route
  • the vehicle speed limit is used to characterize the maximum speed allowed by the target vehicle during acceleration or deceleration
  • the vehicle driving style is used to characterize the speed change of the target vehicle during acceleration or deceleration.
  • the situation of the vehicle in the speed change process is different.
  • some drivers have more aggressive driving habits, and the speed change per unit time during the acceleration or deceleration process is large, that is, the acceleration and deceleration process is more violent, while some drivers have more gentle driving habits, and the speed change per unit time during the acceleration or deceleration process is small, that is, the acceleration and deceleration process is relatively slow. Therefore, it can be seen that based on different driving habits, each driver's vehicle driving style is different, and different vehicle driving styles will cause the speed change process of the vehicle to be different when driving on the same route, which will then affect the global predicted speed of the vehicle.
  • the vehicle speed change feature can be determined based on the vehicle driving style and the vehicle speed change limit, wherein the vehicle speed change limit is the maximum speed change value required by the vehicle design during the acceleration or deceleration process of the vehicle, and the vehicle must be driven within this vehicle speed change limit in any case.
  • the vehicle driving style can be used to make corrections based on the vehicle speed change limit to obtain the situation that meets the speed change of the target vehicle during driving, that is, the vehicle speed change feature.
  • the changes in the acceleration and deceleration of the target vehicle during driving are actually determined. Since the target route that the current target vehicle is traveling on may be the first time in some cases, in order to determine the global predicted speed of the target vehicle, it is necessary to conduct a comprehensive analysis of the driving conditions of other vehicles, that is, to use traffic flow information as a reference.
  • the traffic flow information can be understood as an average speed that can reflect other vehicles when traveling on the route.
  • the global predicted speed of the target vehicle is carried out with these two, which can not only reflect the driving characteristics of the target vehicle driver, but also refer to the situation of other vehicles traveling on the same route, ensuring that the predicted global predicted speed is more in line with the actual driving conditions and ensuring the accuracy of the prediction results.
  • the corresponding output power can be determined after the vehicle speed is determined. Therefore, in the present embodiment, after the global predicted vehicle speed is determined in the aforementioned steps, the global expected power of the corresponding target vehicle can be determined based on the preset speed working condition relationship, and the global expected power indicates an output power that needs to be maintained globally when the current target vehicle is traveling on the current target route, so that the long-term control strategy of the target vehicle on the route can be determined based on the global expected power.
  • the long-term control strategy is determined based on the global expected power, and the global expected power is determined based on the global predicted vehicle speed, since the global predicted vehicle speed can reflect the driving characteristics of the target vehicle, it is ensured that the global expected power can reflect the driving characteristics of the target vehicle, and then ensures that the long-term control strategy is more in line with the driving characteristics of the target vehicle, making it closer to the actual driving situation, and then ensures the accuracy of controlling the vehicle based on the long-term control strategy.
  • the first speed information is a set of running speeds of the target vehicle collected in each time unit during a past target period
  • the second speed is an average value of all the running speeds during the past target period
  • the short-term speed of a vehicle often changes based on some special circumstances during the actual driving process, for example, if a section of the target route is repaired, causing the road to become narrower and requiring deceleration, the short-term speed of the vehicle when driving to this section may be significantly lower than the speed of the previous section. In other words, if the short-term expected power is to be predicted, the corresponding short-term predicted speed is actually constantly changing.
  • the first speed information can be understood as a set formed by the running speed collected in each time unit in the filtered target time period before the current moment. This shows that the first speed information is actually a set composed of multiple speeds, and the number of running speeds contained in the first speed information can be determined based on the target time period and time unit selected by the user. For example, when the target time period is 1 minute and the time unit is 10 seconds, then the first speed set contains 6 running speeds. When the target time period is 10 minutes and the time unit is 1 minute, the first speed set includes 10 running speeds.
  • the second speed information is actually the average value of all running speeds in the first speed information. For example, when the first speed information contains 6 running speeds of 58, 58, 60, 57, 59, and 56 (unit km/h), then the second speed information is 58 (unit km/h).
  • the prediction in the process of determining the short-term predicted vehicle speed based on the first speed information, the second speed information and the third speed information, the prediction can be combined with the preset neural network prediction model, that is, the above three parameters are used as inputs for prediction, so as to obtain the prediction result, that is, the short-term predicted vehicle speed.
  • the vehicle speed change trend can also be determined based on the first speed information, and then the vehicle speed change of other vehicles in a period of time thereafter can be determined based on the third speed information to determine whether the two are the same. If they are the same, it means that the vehicle speed change trend determined by the first speed information is consistent with the vehicle speed change determined by other vehicles based on traffic flow information.
  • the second speed information can be corrected based on the vehicle speed change trend, so as to predict the vehicle speed in the next short period of time, that is, the short-term predicted vehicle speed.
  • the above two methods can be selected based on the actual needs of the user. The above two methods are only used as exemplary descriptions and are not limited here.
  • the preset speed-power relationship is also used to determine the short-term expected power based on the short-term predicted vehicle speed.
  • the short-term expected power is the output power required to characterize the vehicle's driving in the next short period of time, it can be compared with the preset power threshold based on the short-term expected power.
  • the preset power threshold can be understood as the threshold of the output power required to meet the vehicle's power performance. In this way, it can be compared based on the short-term required power rate of the vehicle and the threshold required to meet the power performance, so as to determine whether it is necessary to turn on the range extender to supplement the power.
  • the real-time required power of the target vehicle is predicted, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power.
  • the power control process of the vehicle in the actual driving process, especially the extended-range vehicle is very complicated, it is necessary to consider not only the global expected power to ensure the overall mileage of the vehicle, but also to ensure the short-term power demand, that is, the short-term expected power. At the same time, it is also necessary to determine whether the range extender needs to be turned on or off based on the current power demand of the vehicle. Therefore, in this embodiment, by combining the global expected power, short-term expected power and range extender startup suggestion, and predicting the actual required power based on the preset power prediction algorithm, it can ensure that during the driving process of the vehicle, the above-mentioned multiple factors are taken into account for control, thereby ensuring the accuracy of the power control of the extended-range vehicle.
  • the present embodiment provides a power control method for an extended-range vehicle.
  • a vehicle speed change characteristic is determined based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and a global predicted speed of the target vehicle in a target route is determined based on the vehicle speed change characteristic and traffic flow information.
  • a global predicted speed of the target vehicle is determined, and a long-term control strategy of the target vehicle is determined based on the global expected power.
  • a short-term predicted speed of the target vehicle is determined based on first speed information, second speed information and traffic flow information of the target vehicle.
  • a short-term expected power of the target vehicle is determined, and a range extender start suggestion is generated based on the short-term expected power and a preset power threshold.
  • a real-time required power of the target vehicle is predicted, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power, thereby realizing a power control function for the extended-range vehicle.
  • the global predicted power determined in the present application is determined based on the global predicted vehicle speed determined based on the vehicle speed change characteristics and traffic flow characteristics, and the traffic flow information is used to characterize the average speed of other vehicles on the target route, that is, the driving conditions of other vehicles are combined when determining the global predicted vehicle speed, and the vehicle speed change characteristics are determined based on the vehicle speed change limit and the vehicle driving style, the vehicle speed change limit is used to characterize the maximum speed allowed by the target vehicle during acceleration or deceleration, and the vehicle driving style is used to characterize the speed change of the target vehicle during acceleration or deceleration.
  • the vehicle speed change characteristics can reflect the characteristics of the speed change of the current vehicle during driving, so it can be ensured that the global predicted vehicle speed can take into account the driving characteristics of the current vehicle and the driving conditions of other vehicles on the same route, so that while reflecting the driving characteristics of the current vehicle, the global predicted vehicle speed of the vehicle on the entire route can be determined without the vehicle traveling on the current route, thereby ensuring the accuracy of the global expected power, without considering the matching process of the current road conditions, and improving the accuracy of vehicle power control.
  • the first speed information is a collection of the running speeds collected by the target vehicle in each time unit during the past target period
  • the second speed is the average value of all the running speeds during the past target period, that is, in the process of determining the short-term predicted speed, the driving conditions of the vehicle before the current moment can be taken into account and combined with the possible driving conditions of other vehicles after the current moment to make a short-term predicted speed prediction, thereby ensuring the accuracy of the prediction result, and thus ensuring the accuracy of the short-term expected power, and then laying the foundation for determining the accuracy of the range extender start suggestion based on the comparison between the short-term expected power and the preset power threshold.
  • the real-time required working power of the target vehicle is determined based on the global expected power, the short-term expected power and the range extender start suggestion, which can ensure that in the process of determining the vehicle working condition, both the power demand during long-term operation and the short-term power demand can be taken into account, and on this basis, power management can be performed based on the range extender start suggestion, thereby determining the accuracy of the power control of the range extender vehicle.
  • the present application embodiment provides another access control method, as shown in FIG2 , the method includes:
  • the traffic flow information is used to characterize the average speed of other vehicles on the target route
  • the vehicle speed limit is used to characterize the maximum speed allowed by the target vehicle during acceleration or deceleration
  • the vehicle driving style is used to characterize the speed change of the target vehicle during acceleration or deceleration.
  • the vehicle speed change feature may include a speed change correction parameter.
  • the speed change correction parameter can be understood as a parameter obtained by adjusting the vehicle speed change limit value based on the driver's driving style during the process of driving the vehicle, which can correct the vehicle speed change (acceleration, deceleration).
  • this step can be executed as follows:
  • the historical driving data of the target vehicle is obtained, and the driving style of the vehicle is determined based on the historical driving data.
  • the historical driving data of the target vehicle is analyzed to determine the characteristics of the speed change (violent, gentle, etc.) of the driver during acceleration and deceleration.
  • the specific calculation process can use an AI classification algorithm (such as K-means algorithm, SVM support vector machine, random forest algorithm, etc.), with the driver's historical driving data as input to obtain the driver's style.
  • the vehicle information of the target vehicle is obtained, and the vehicle speed limit is extracted from the vehicle information.
  • the vehicle speed limit is actually related to the vehicle design, that is, once the vehicle model and type are determined, the vehicle speed limit of the vehicle can be determined. Therefore, in this step, it is necessary to obtain the vehicle information of the target vehicle.
  • the vehicle information can be understood as comprehensive information including the brand, model, type, design, etc. of the vehicle, and the specific vehicle speed limit of the current target vehicle can be determined from the vehicle information.
  • the vehicle speed limit is corrected based on the vehicle driving style to obtain the speed correction parameter.
  • the vehicle driving style can be used to make corrections based on the vehicle speed limit, and the corrected value is the speed correction parameter, that is, a parameter that can reflect the characteristics of the target vehicle when the vehicle speed changes.
  • the current driving information of the target vehicle is obtained, and the driving data of other vehicles on the target route is obtained based on the target route, and then the average vehicle speed is determined as the traffic flow information based on the driving data, and the driving information at least includes the target route.
  • the driving conditions of other vehicles on the current target route need to be used as a reference in the process of predicting the global predicted vehicle speed, it is necessary to determine the target route based on the driving information, and after obtaining the driving data of other vehicles on the target route through the cloud or big data, the average vehicle speed is determined as the traffic flow information based on the driving data.
  • the traffic flow information is corrected according to the speed change correction parameter to obtain the global predicted vehicle speed. Since the speed change correction parameter can reflect the characteristics of the vehicle speed change when the target vehicle is traveling, the traffic flow information is corrected using the speed change correction parameter to obtain the global predicted vehicle speed, which can reflect the driving characteristics of the target vehicle, making the predicted speed closer to the actual driving situation, and ensuring the accuracy of the global predicted vehicle speed.
  • the preset speed-power relationship includes a vehicle dynamics formula.
  • vehicle dynamics formula also called a vehicle dynamics equation, is a formula specifically used to calculate output power using vehicle speed.
  • This step can be specifically performed as follows:
  • the equivalent fuel factor of the target vehicle is determined according to the global expected power and the equivalent fuel control strategy, and the long-term control strategy of the target vehicle is determined based on the equivalent fuel factor; wherein the equivalent fuel control strategy is used to control the control rules between fuel and electric energy when the target vehicle is traveling in the most economical way, and the equivalent fuel factor is the oil-to-electricity output ratio that meets the requirements of the target vehicle traveling on the target route.
  • the equivalent fuel control strategy can be understood as a conventional strategy for determining how to determine the most economical strategy in the process of determining oil-electric output. After determining the equivalent fuel factor in this way, the distribution of output power between electric energy and fuel in the entire target route is actually determined, and the long-term control strategy is determined based on this.
  • the first speed information is a set of running speeds of the target vehicle collected in each time unit during a past target period
  • the second speed is an average value of all the running speeds during the past target period
  • this step may be performed as follows:
  • Step A obtaining the travel data of the target vehicle on the target route, and extracting the travel speed corresponding to each unit time in the target time period based on the travel data, and determining a plurality of the travel speeds corresponding to the target time period as the first speed information;
  • Step B calculating an average value according to all the driving speeds in the first speed information as the second speed information
  • Step C performing a prediction operation based on the first speed information, the second speed information and the traffic flow information and using the preset short-time vehicle speed prediction model to obtain the short-time predicted vehicle speed, wherein the preset short-time vehicle speed prediction model is a vehicle speed prediction model trained based on a preset neural network algorithm, and the preset neural network algorithm includes a nonlinear autoregressive neural network algorithm and a long short-term memory neural network algorithm.
  • the vehicle speed in the future m time can be recorded as For multi-step prediction, i.e., speed prediction after a period of time, m>1. Since the future speed is related to the dynamic changes and average speed of the past period of time, and also needs to refer to the average speed of other vehicles in the future period of time (target period), It is expressed as follows:
  • a dynamic time series prediction algorithm based on AI can be used in advance to solve function f, that is, a vehicle speed prediction model obtained by training based on a neural network algorithm, including a nonlinear autoregressive neural network (NARX) with input and a long short-term memory neural network (LSTM), and sample data.
  • NARX nonlinear autoregressive neural network
  • LSTM long short-term memory neural network
  • this step may be performed as follows:
  • the short-term expected power of the target vehicle is calculated using the vehicle dynamics formula and the short-term predicted vehicle speed.
  • the vehicle dynamics formula is consistent with the description in the previous steps and is a commonly used formula for calculating power, so it will not be repeated here.
  • the preset power threshold is the power threshold set to meet the vehicle power, if it is determined that the short-term expected power exceeds the preset power threshold, it means that the output power is insufficient and the range extender needs to be turned on to supplement the power gap. Otherwise, it means that the output power has been met and the range extender does not need to be turned on.
  • vehicle status information which can be understood as comprehensive information including the status of each component and system of the vehicle as a whole, and then extract the range extender status information and battery status information from the vehicle status information.
  • the vehicle status information can be obtained in real time from the vehicle system, or by issuing instructions to the vehicle system through command control, and then obtaining the corresponding parameters based on the feedback information from various sensors of the vehicle system, for example, data collected from the battery status sensor and the range extender status sensor.
  • various sensors of the vehicle system for example, data collected from the battery status sensor and the range extender status sensor.
  • the acquisition method which shall be based on the actual needs of the user.
  • the real-time required power of the target vehicle is predicted, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power.
  • this step can be performed as follows:
  • the actual required power of the range extender is determined as the real-time required power.
  • the process of determining the real-time power demand ensures that the battery and range extender status are taken into consideration, thereby ensuring that the real-time power demand obtained is more in line with the actual driving situation, thus ensuring the power
  • an embodiment of the present application further provides a storage medium, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the power control method of the extended-range vehicle described above.
  • an embodiment of the present application also provides a power control device for an extended-range vehicle, the device comprising a storage medium; and one or more processors, the storage medium is coupled to the processor, and the processor is configured to execute program instructions stored in the storage medium; when the program instructions are run, the power control method for the extended-range vehicle described above is executed.
  • another embodiment of the present application also provides a power control device for an extended-range vehicle.
  • the power control device embodiment of the extended-range vehicle corresponds to the aforementioned method embodiment.
  • the power control device embodiment of the extended-range vehicle will no longer repeat the details of the aforementioned method embodiment one by one, but it should be clear that the system in this embodiment can correspond to all the contents of the aforementioned method embodiment.
  • the power control device of the extended-range vehicle includes:
  • the first determination unit 31 may be used to determine a vehicle speed change feature based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and determine a global predicted vehicle speed of the target vehicle in a target route based on the vehicle speed change feature and traffic flow information, wherein the traffic flow information may be used to characterize an average vehicle speed of other vehicles in the target route, the vehicle speed change limit may be used to characterize a maximum speed allowed by the target vehicle during acceleration or deceleration, and the vehicle driving style may be used to characterize a speed change of the target vehicle during acceleration or deceleration;
  • a second determination unit 32 may be used to determine a global expected power of the target vehicle based on the global predicted vehicle speed and a preset speed-power relationship, and determine a long-term control strategy of the target vehicle based on the global expected power;
  • the third determining unit 33 may be used to determine the short-term predicted vehicle speed of the target vehicle based on the first speed information, the second speed information and the traffic flow information of the target vehicle, wherein the first speed information is a set of running speeds collected at each time unit of the target vehicle in the past target period, and the second speed is an average value of all the running speeds in the past target period;
  • a fourth determination unit 34 may be configured to determine the short-term expected power of the target vehicle based on the short-term predicted vehicle speed and the preset speed-power relationship, and generate a range extender start suggestion based on the short-term expected power and a preset power threshold;
  • the prediction unit 35 can be used to predict the real-time required power of the target vehicle based on the global expected power, the short-term expected power and the range extender start suggestion, combined with a preset power prediction algorithm, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power.
  • the vehicle speed change characteristic includes a speed change correction parameter
  • the first determining unit 31 includes:
  • the determination module 311 may be used to obtain the historical driving data of the target vehicle and determine the driving style of the vehicle based on the historical driving data;
  • the extraction module 312 may be used to obtain vehicle information of the target vehicle and extract the vehicle speed limit value from the vehicle information;
  • a first correction module 313 may be used to correct the vehicle speed limit value based on the vehicle driving style to obtain the speed correction parameter
  • the acquisition module 314 may be used to acquire the current driving information of the target vehicle, and based on the target route, acquire the driving data of other vehicles on the target route, and then determine the average vehicle speed as the traffic flow information based on the driving data, wherein the driving information at least includes the target route;
  • the second correction module 315 can be used to correct the traffic flow information according to the speed change correction parameter to obtain the global predicted vehicle speed.
  • the preset speed-power relationship includes a vehicle dynamics formula
  • the second determining unit 32 includes:
  • a calculation module 321 may be used to calculate the global expected power of the target vehicle by using the vehicle dynamics formula and the global predicted vehicle speed;
  • the determination module 322 can be used to determine the equivalent fuel factor of the target vehicle according to the global expected power and the equivalent fuel control strategy, and determine the long-term control strategy of the target vehicle based on the equivalent fuel factor; wherein the equivalent fuel control strategy can be used to control the control rules between fuel and electric energy when the target vehicle is traveling in the most economical way, and the equivalent fuel factor is the oil-to-electricity output ratio that meets the requirements of the target vehicle traveling on the target route.
  • the third determining unit 33 includes:
  • the extraction module 331 may be used to obtain the travel data of the target vehicle on the target route, and extract the travel speed corresponding to each unit time in the target time period based on the travel data, and determine the multiple travel speeds corresponding to the target time period as the first speed information;
  • a calculation module 332 may be configured to calculate an average value according to all the driving speeds in the first speed information as the second speed information
  • the prediction module 333 can be used to perform a prediction operation based on the first speed information, the second speed information and the traffic flow information, and use the preset short-time vehicle speed prediction model to obtain the short-time predicted vehicle speed, wherein the preset short-time vehicle speed prediction model is a vehicle speed prediction model obtained by training based on a preset neural network algorithm, and the preset neural network algorithm includes a nonlinear autoregressive neural network algorithm and a long short-term memory neural network algorithm.
  • the fourth determining unit 34 includes:
  • a calculation module 341 may be used to calculate the short-term expected power of the target vehicle by using the vehicle dynamics formula and the short-term predicted vehicle speed;
  • the judging module 342 may be used to judge whether the short-term expected power exceeds the preset power threshold
  • the first execution module 343 may be configured to determine to start the range extender if it is determined that the short-term expected power exceeds the preset power threshold;
  • the second execution module 344 may be configured to determine to shut down the range extender if it is determined that the short-term expected power does not exceed the preset power threshold.
  • the device further includes:
  • An acquisition unit 36 may be used to acquire vehicle status information and extract range extender status information and battery status information from the vehicle status information;
  • the prediction unit 35 can be specifically used to determine the actual required power of the range extender as the real-time required power according to the global expected power, the short-term expected power, the range extender startup suggestion, the range extender status information and the battery status information, in combination with the preset power prediction algorithm.
  • the embodiment of the present application provides a power control method and device for an extended-range vehicle.
  • a vehicle speed change characteristic is determined based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and a global predicted speed of the target vehicle in a target route is determined based on the vehicle speed change characteristic and traffic flow information.
  • a global predicted speed of the target vehicle in a target route is determined based on the vehicle speed change characteristic and traffic flow information.
  • a global expected power of the target vehicle is determined, and a long-term control strategy of the target vehicle is determined based on the global expected power.
  • a short-term predicted speed of the target vehicle is determined based on first speed information, second speed information and traffic flow information of the target vehicle.
  • a short-term expected power of the target vehicle is determined, and a range extender start suggestion is generated based on the short-term expected power and a preset power threshold.
  • a real-time required power of the target vehicle is predicted, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power, thereby realizing a power control function for the extended-range vehicle.
  • the global predicted power determined in the present application is determined based on the global predicted vehicle speed determined based on the vehicle speed change characteristics and traffic flow characteristics, and the traffic flow information is used to characterize the average speed of other vehicles on the target route, that is, the driving conditions of other vehicles are combined when determining the global predicted vehicle speed, and the vehicle speed change characteristics are determined based on the vehicle speed change limit and the vehicle driving style, the vehicle speed change limit is used to characterize the maximum speed allowed by the target vehicle during acceleration or deceleration, and the vehicle driving style is used to characterize the speed change of the target vehicle during acceleration or deceleration.
  • the vehicle speed change characteristics can reflect the characteristics of the speed change of the current vehicle during driving, so it can be ensured that the global predicted vehicle speed can take into account the driving characteristics of the current vehicle and the driving conditions of other vehicles on the same route, so that while reflecting the driving characteristics of the current vehicle, the global predicted vehicle speed of the vehicle on the entire route can be determined without the vehicle traveling on the current route, thereby ensuring the accuracy of the global expected power, without considering the matching process of the current road conditions, and improving the accuracy of vehicle power control.
  • the first speed information is a collection of the running speeds collected by the target vehicle in each time unit during the past target period
  • the second speed is the average value of all the running speeds during the past target period, that is, in the process of determining the short-term predicted speed, the driving conditions of the vehicle before the current moment can be taken into account and combined with the possible driving conditions of other vehicles after the current moment to make a short-term predicted speed prediction, thereby ensuring the accuracy of the prediction result, and thus ensuring the accuracy of the short-term expected power, and then laying the foundation for determining the accuracy of the range extender start suggestion based on the comparison between the short-term expected power and the preset power threshold.
  • the real-time required working power of the target vehicle is determined based on the global expected power, the short-term expected power and the range extender start suggestion, which can ensure that in the process of determining the vehicle working condition, both the power demand during long-term operation and the short-term power demand can be taken into account, and on this basis, power management can be performed based on the range extender start suggestion, thereby determining the accuracy of the power control of the range extender vehicle.
  • An embodiment of the present application also provides a power control device for an extended-range vehicle, the device comprising a storage medium; and one or more processors, the storage medium being coupled to the processor, the processor being configured to execute program instructions stored in the storage medium; when the program instructions are executed, the power control method for the extended-range vehicle described above is executed.
  • An embodiment of the present application provides a device, which includes a processor, a memory, and a program stored in the memory and executable on the processor.
  • the processor executes the program, the following steps are implemented: determining a vehicle speed change characteristic based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and determining a global predicted speed of the target vehicle in a target route based on the vehicle speed change characteristic and traffic flow information, wherein the traffic flow information is used to characterize an average speed of other vehicles on the target route, the vehicle speed change limit is used to characterize a maximum speed allowed for the target vehicle during acceleration or deceleration, and the vehicle driving style is used to characterize a speed change of the target vehicle during acceleration or deceleration; determining a global expected power of the target vehicle based on the global predicted speed and a preset speed-power relationship, and determining a global expected power of the target vehicle based on the global predicted speed and a preset speed-power relationship.
  • the global expected power determines the long-term control strategy of the target vehicle; the short-term predicted speed of the target vehicle is determined based on the first speed information, the second speed information and the traffic flow information of the target vehicle, wherein the first speed information is a collection of the running speeds of the target vehicle collected in each time unit in the past target period, and the second speed is the average value of all the running speeds in the past target period; based on the short-term predicted speed and the preset speed-power relationship, the short-term expected power of the target vehicle is determined, and a range extender start suggestion is generated based on the short-term expected power and the preset power threshold; based on the global expected power, the short-term expected power and the range extender start suggestion, combined with a preset power prediction algorithm, the real-time required power of the target vehicle is predicted, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power.
  • vehicle speed change characteristics include a speed change correction parameter
  • the determining of the vehicle speed change characteristics based on the vehicle driving style and the vehicle speed change limit of the target vehicle, and determining the global predicted vehicle speed of the target vehicle in the target route based on the vehicle speed change characteristics and traffic flow information includes:
  • the traffic flow information is corrected according to the speed change correction parameter to obtain the global predicted vehicle speed.
  • the preset speed-power relationship includes a vehicle dynamics formula
  • the determining of the global expected power of the target vehicle based on the global predicted vehicle speed and the preset speed-power relationship, and determining the long-term control strategy of the target vehicle based on the global expected power comprises:
  • the equivalent fuel factor of the target vehicle is determined according to the global expected power and the equivalent fuel control strategy, and the long-term control strategy of the target vehicle is determined based on the equivalent fuel factor; wherein the equivalent fuel control strategy is used to control the control rules between fuel and electric energy when the target vehicle is traveling in the most economical way, and the equivalent fuel factor is the oil-to-electricity output ratio that meets the requirements of the target vehicle traveling on the target route.
  • determining the short-term predicted vehicle speed of the target vehicle based on the first speed information, the second speed information and the traffic flow information of the target vehicle includes:
  • the short-term predicted vehicle speed is obtained by performing a prediction operation based on the first speed information, the second speed information and the traffic flow information and by using the preset short-term vehicle speed prediction model, wherein the preset short-term vehicle speed prediction model is a vehicle speed prediction model obtained by training based on a preset neural network algorithm, and the preset neural network algorithm includes a nonlinear autoregressive neural network algorithm and a long short-term memory neural network algorithm.
  • the determining of the short-term expected power of the target vehicle based on the short-term predicted vehicle speed and the preset speed-power relationship, and generating a range extender start suggestion based on the short-term expected power and a preset power threshold includes:
  • the method further includes:
  • the predicting the real-time required power of the target vehicle based on the global expected power, the short-term expected power and the range extender start suggestion in combination with a preset power prediction algorithm includes:
  • the actual required power of the range extender is determined as the real-time required power.
  • the present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing program code that initializes the following method steps: determining a vehicle speed change characteristic based on a vehicle driving style and a vehicle speed change limit of a target vehicle, and determining a global predicted vehicle speed of the target vehicle in a target route based on the vehicle speed change characteristic and traffic flow information, wherein the traffic flow information is used to characterize the average vehicle speed of other vehicles on the target route, the vehicle speed change limit is used to characterize the maximum speed allowed by the target vehicle during acceleration or deceleration, and the vehicle driving style is used to characterize the speed change of the target vehicle during acceleration or deceleration; determining a global expected power of the target vehicle based on the global predicted vehicle speed and a preset speed-power relationship, and determining a long-term control of the target vehicle based on the global expected power.
  • control strategy determine the short-term predicted speed of the target vehicle based on the first speed information, the second speed information and the traffic flow information of the target vehicle, wherein the first speed information is a set of the running speeds of the target vehicle collected in each time unit in the past target period, and the second speed is the average value of all the running speeds in the past target period; determine the short-term expected power of the target vehicle based on the short-term predicted speed and the preset speed-power relationship, and generate a range extender start suggestion based on the short-term expected power and the preset power threshold; predict the real-time required power of the target vehicle based on the global expected power, the short-term expected power and the range extender start suggestion in combination with a preset power prediction algorithm, so as to control the real-time oil-electric power output ratio of the target vehicle based on the real-time required power.
  • the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.
  • a computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
  • These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
  • a computing device includes one or more processors (CPU), input/output interfaces, network interfaces, and memory.
  • processors CPU
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and/or non-volatile memory in the form of read-only memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
  • RAM random access memory
  • ROM read-only memory
  • flash RAM flash memory
  • Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information.
  • Information can be computer readable instructions, data structures, program modules or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.
  • computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.
  • the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
  • a computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.

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Abstract

本申请公开一种增程式车辆的功率控制方法及装置，涉及车辆技术领域。本申请的方法包括：基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，基于车辆变速特征及交通流信息确定目标车辆在目标线路中的全局预测车速；基于全局预测车速和预设速度功率关系，确定全局预期功率，基于全局预期功率确定目标车辆的长期控制策略；基于目标车辆的第一速度信息、第二速度信息以及交通流信息确定短时预测车速；基于短时预测车速以及预设速度功率关系，确定短时预期功率，并基于短时预期功率与预设功率阈值生成增程器启动建议；基于全局预期功率、短时预期功率以及增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率。

Description

增程式车辆的功率控制方法及装置 技术领域
本申请涉及车辆技术领域，尤其涉及一种增程式车辆的功率控制方法及装置。
背景技术
随着节能、环保理念的深入，新能源车辆也逐步兴起。在新能源车辆的使用过程中，用户的焦虑主要来自续航里程上，因此，如何对车辆进行准确的功率控制就成为了人们关注的焦点。
目前，在进行增程式车辆的功率控制的过程中，常见的是基于道路工况规则进行功率控制，在使用这种方式控制时，往往是预先在不同的道路工况进行测试后，得到不同道路工况下车辆的功率控制策略，然后在实际使用时就需要基于当前道路的工况与道路工况规则中的预设工况相匹配，并以匹配的工况控制策略对车辆进行控制。然而在实际应用中，现有的功率控制方式需要将当前车辆行驶的道路工况与预设工况相匹配，一旦匹配程度较低，就会导致工况控制策略的适配性较差，从而影响功率控制的准确性。
发明内容
本申请实施例提供一种增程式车辆的功率控制方法及装置，主要目的在于解决现有的依赖道路工况匹配方式进行功率控制时，在新路况下匹配程度较低导致增程式车辆的功率控制准确性较低的问题。
为解决上述技术问题，本申请实施例提供如下技术方案：
第一方面，本申请提供了一种增程式车辆的功率控制方法，所述方法，包括：
基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况；
基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略；
基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值；
基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；
基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率 预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例。
可选的，所述车速变速特征包括变速修正参数；
所述基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，包括：
获取所述目标车辆的历史行车数据，并基于所述历史行车数据确定所述车辆驾驶风格；
获取所述目标车辆的车辆信息，并从所述车辆信息中提取所述车辆变速限值；
基于所述车辆驾驶风格对所述车辆变速限值进行修正，得到所述变速修正参数；
获取所述目标车辆当前的行驶信息，并基于所述目标线路获取其他车辆在所述目标线路中的行驶数据，再基于所述行驶数据确定所述平均车速作为所述交通流信息，所述行驶信息至少包括所述目标线路；
根据所述变速修正参数对所述交通流信息进行修正，得到所述全局预测车速。
可选的，所述预设速度功率关系包括车辆动力学公式；
所述基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略，包括：
通过所述车辆动力学公式以及所述全局预测车速，计算所述目标车辆的所述全局预期功率；
根据所述全局预期功率以及等效燃油控制策略确定所述目标车辆的等效燃油因子，并基于所述等效燃油因子确定所述目标车辆的所述长期控制策略；其中，所述等效燃油控制策略用于基于最经济方式控制所述目标车辆行驶时的燃油、电能之间的控制规则，所述等效燃油因子为符合所述目标车辆在所述目标线路中行驶的油电输出比例。
可选的，所述基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，包括：
获取所述目标车辆的在所述目标线路的已行驶数据，并基于所述已行驶数据中提取在所述目标时段内的每个单位时间对应的行驶速度，并将对应所述目标时段的多个所述行驶速度确定为所述第一速度信息；
根据所述第一速度信息中的全部所述行驶速度计算平均值，作为为所述第二速度信息；
根据所述第一速度信息、所述第二速度信息以及交通流信息，并利用所述预设短时车速预测模型执行预测操作，得到所述短时预测车速，其中，所述预设短时车速预测模型是基于预设神经网络算法进行训练得到的车速预测模型，所述预设神经网络算法包括非线性自回归神经网络算法以及长短期记忆神经网络算法。
可选的，所述基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议，包括：
通过所述车辆动力学公式以及所述短时预测车速，计算所述目标车辆的所述短时预期功率；
判断所述短时预期功率是否超过所述预设功率阈值；
若超过，则确定启动所述增程器；
若未超过，则确定关闭所述增程器。
可选的，在所述基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率之前，所述方法还包括：
获取车辆状态信息，并从所述车辆状态信息中提取增程器状态信息以及电池状态信息；
所述基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，包括：
根据所述全局预期功率、所述短时预期功率、所述增程器启动建议、所述增程器状态信息以及所述电池状态信息，结合所述预设功率预测算法，确定所述增程器的实际需求功率，作为所述实时需求功率。
第二方面，本申请还提供一种增程式车辆的功率控制装置，包括：
第一确定单元，用于基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况；
第二确定单元，用于基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略；
第三确定单元，用于基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值；
第四确定单元，用于基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；
预测单元，用于基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例。
可选的，所述车速变速特征包括变速修正参数；
所述第一确定单元，包括：
确定模块，用于获取所述目标车辆的历史行车数据，并基于所述历史行车数据确定所述车辆驾驶风格；
提取模块，用于获取所述目标车辆的车辆信息，并从所述车辆信息中提取所述车辆变速限值；
第一修正模块，用于基于所述车辆驾驶风格对所述车辆变速限值进行修正，得到所述变速修正参数；
获取模块，用于获取所述目标车辆当前的行驶信息，并基于所述目标线路获取其他车 辆在所述目标线路中的行驶数据，再基于所述行驶数据确定所述平均车速作为所述交通流信息，所述行驶信息至少包括所述目标线路；
第二修正模块，用于根据所述变速修正参数对所述交通流信息进行修正，得到所述全局预测车速。
可选的，所述预设速度功率关系包括车辆动力学公式；
所述第二确定单元，包括：
计算模块，用于通过所述车辆动力学公式以及所述全局预测车速，计算所述目标车辆的所述全局预期功率；
确定模块，用于根据所述全局预期功率以及等效燃油控制策略确定所述目标车辆的等效燃油因子，并基于所述等效燃油因子确定所述目标车辆的所述长期控制策略；其中，所述等效燃油控制策略用于基于最经济方式控制所述目标车辆行驶时的燃油、电能之间的控制规则，所述等效燃油因子为符合所述目标车辆在所述目标线路中行驶的油电输出比例。
可选的，所述第三确定单元，包括：
提取模块，用于获取所述目标车辆的在所述目标线路的已行驶数据，并基于所述已行驶数据中提取在所述目标时段内的每个单位时间对应的行驶速度，并将对应所述目标时段的多个所述行驶速度确定为所述第一速度信息；
计算模块，用于根据所述第一速度信息中的全部所述行驶速度计算平均值，作为为所述第二速度信息；
预测模块，用于根据所述第一速度信息、所述第二速度信息以及交通流信息，并利用所述预设短时车速预测模型执行预测操作，得到所述短时预测车速，其中，所述预设短时车速预测模型是基于预设神经网络算法进行训练得到的车速预测模型，所述预设神经网络算法包括非线性自回归神经网络算法以及长短期记忆神经网络算法。
可选的，所述第四确定单元，包括：
计算模块，用于通过所述车辆动力学公式以及所述短时预测车速，计算所述目标车辆的所述短时预期功率；
判断模块，用于判断所述短时预期功率是否超过所述预设功率阈值；
第一执行模块，用于若判断所述短时预期功率超过所述预设功率阈值，则确定启动所述增程器；
第二执行模块，用于若判断所述短时预期功率未超过所述预设功率阈值，则确定关闭所述增程器。
可选的，所述装置还包括：
获取单元，用于获取车辆状态信息，并从所述车辆状态信息中提取增程器状态信息以及电池状态信息；
所述预测单元，具体用于根据所述全局预期功率、所述短时预期功率、所述增程器启动建议、所述增程器状态信息以及所述电池状态信息，结合所述预设功率预测算法，确定所述增程器的实际需求功率，作为所述实时需求功率。
第三方面，本申请的实施例提供了一种存储介质，所述存储介质包括存储的程序，其中，在所述程序运行时控制所述存储介质所在设备执行第一方面中任一项所述的增程式车辆的功率控制方法。
第四方面，本申请的实施例提供了一种增程式车辆的功率控制装置，所述装置包括存储介质；及一个或者多个处理器，所述存储介质与所述处理器耦合，所述处理器被配置为执行所述存储介质中存储的程序指令；所述程序指令运行时执行第一方面中任一项所述的增程式车辆的功率控制方法。
借由上述技术方案，本申请提供的技术方案至少具有下列优点：
本申请提供一种增程式车辆的功率控制方法及装置，本申请首先基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，然后，基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略，之后基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，之后基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；最后基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例，从而实现对增程式车辆的功率控制功能。与现有技术相比，本申请确定的全局预测功率是基于车辆变速特征和交通流特征确定的全局预测车速确定的，且所述交通流信息用于表征其他车辆在所述目标线路的平均车速，也就是说在确定全局预测车速时结合了其他车辆行驶情况，同时车辆变速特征又是基于车辆变速限值和车辆驾驶风格确定的，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况，因此车辆变速特征能够体现当前车辆在行驶过程中车速变化的特点，因此可以确保全局预测车速能够兼顾当前车辆的行驶特点和其他车辆在同样线路上的行驶情况，从而在体现了当前车辆的行驶特点的同时无需该车辆在当前线路上行驶也能够确定车辆在整个线路上的全局预测车速的确定，继而保证了全局预期功率的准确性，无需考虑当前道路车况进行匹配的过程，提高了车辆功率控制的准确性。另外，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值，也就是说能够在确定短时预测车速的过程中兼顾本车辆在当前时刻之前的行驶情况结合其他车辆在当前时刻之后可能的行驶情况进行短时预测车速预测，确保了预测结果的准确性，也就确保了短时预期功率的准确性，继而为基于短时预期功率与预设功率阈值对比来确定增程器启动建议的准确性奠定了基础。这样，基于全局预期功率、短时预期功率以及增程器启动建议进行目标车辆的实时需求工功率的确定，能够确保在确定车辆工况的过程中，既能顾及长期运行时的功率需求，还能考虑到短时功率需求，并在此基础上可以基于增程器启动建议进行功率管理， 确定了对增程式车辆的功率控制的准确性。
附图说明
通过参考附图阅读下文的详细描述，本申请示例性实施方式的上述以及其他目的、特征和优点将变得易于理解。在附图中，以示例性而非限制性的方式示出了本申请的若干实施方式，相同或对应的标号表示相同或对应的部分，其中：
图1示出了本申请实施例提供的一种增程式车辆的功率控制方法流程图；
图2示出了本申请实施例提供的另一种增程式车辆的功率控制方法流程图；
图3示出了本申请实施例提供的一种增程式车辆的功率控制装置的组成框图；
图4示出了本申请实施例提供的另一种增程式车辆的功率控制装置的组成框图。
具体实施方式
下面将参照附图更详细地描述本申请的示例性实施方式。虽然附图中显示了本申请的示例性实施方式，然而应当理解，可以以各种形式实现本申请而不应被这里阐述的实施方式所限制。相反，提供这些实施方式是为了能够更透彻地理解本申请，并且能够将本申请的范围完整的传达给本领域的技术人员。
需要注意的是，除非另有说明，本申请使用的技术术语或者科学术语应当为本申请所属领域技术人员所理解的通常意义。
本申请实施例提供一种增程式车辆的功率控制方法，具体如图1所示，该方法包括：
101、基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于车辆变速特征及交通流信息确定目标车辆在目标线路中的全局预测车速。
其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况。
在车辆实际行驶过程中，基于驾驶员的操作习惯的不同，车辆在速度变化过程中的情况是不同的，例如某些驾驶员驾驶习惯比较激进，加速或减速的过程中单位时间内的速度变化较大，即加速和减速的过程比较猛烈，而有的驾驶员驾驶习惯比较平缓，加速或减速过程中单位时间内的速度变化较小，也就是说加速和减速过程比较缓慢，因此，可以看出基于不同的驾驶习惯，每个驾驶员的车辆驾驶风格是不同的，而不同的车辆驾驶风格会导致车辆在行驶同一个线路时速度变化过程也存在区别，继而会影响车辆的全局预测车速。基于此，在本实施例中，就可以基于该车辆驾驶风格和车辆变速限值来确定车辆变速特征，其中车辆变速限值就是该车辆在加速或减速过程中基于车辆设计所要求的最大的速度变化值，无论如何驾驶车辆都要再这个车辆变速限值之内。这样就可以基于车辆变速限值的基础上利用车辆驾驶风格进行修正，得到符合该目标车辆在行驶过程中的速度变化的情况，即车辆变速特征。
在确定了车辆变速特征后，实际上就确定了该目标车辆在行驶时加速和减速时变化的 情况，而由于某些情况下当前的目标车辆行驶的目标线路可能是第一次行驶，为了确定该目标车辆行驶时的全局预测速度，就需要从其他车辆行驶的情况进行综合分析，也就是说将交通流信息作为参考，该交通流信息就可以理解为一种能够体现出其他车辆在行驶在该线路时的平均车。这样在车辆变速特征作为当前目标车辆行驶特征的基础上，结合其他车辆行驶该线路的平均速度，即交通流信息，以此二者来进行该目标车辆的全局预测车速，这既能体现出目标车辆驾驶人员驾驶的特点，还能参考其他车辆行驶同一个线路的情况，确保了预测出的全局预测车速的更为符合实际行驶情况，保证了预测结果的准确性。
102、基于全局预测车速和预设速度功率关系，确定目标车辆的全局预期功率，并基于全局预期功率确定目标车辆的长期控制策略。
由于车速、输出功率、和动力之间存在一定关系，即预设速度功率关系，而动力可以基于车辆的进行采集，因此，当确定了车速后就能够确定对应的输出功率。因此在本实施例中，当前述步骤中确定了全局预测车速后，就可以基于预设速度工况关系，确定对应目标车辆的全局预期功率，该全局预期功率表明了在当前目标车辆行驶在当前目标线路时全局需要保持的一个输出功率，这样就可以基于该全局预期功率来确定目标车辆在该线路上的长期控制策略。由于该长期控制策略是基于全局预期功率确定的，而全局预期功率是基于全局预测车速确定的，由于全局预测车速能够体现出目标车辆驾驶特点的，因此就确保了该全局预期功率能够体现出目标车辆的驾驶特点，继而确保了长期控制策略更为符合目标车辆的驾驶特点，使其更趋近实际的驾驶情况，继而确保了基于该长期控制策略对车辆进行控制时的准确性。
103、基于目标车辆的第一速度信息、第二速度信息以及交通流信息确定目标车辆的短时预测车速。
其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值。
由于车辆在在实际行驶的过程中，短时车速往往会基于一些特殊情况进行变化，例如，目标线路中某段线路出现修路的情况导致道路变窄且需要减速，那么车辆在行驶到这部分路段时的短时车速可能会明显低于此前路段的车速。也就是说，若要预测短时预期功率时，对应的短时预测车速实际上是不断变化的。同时，由于短时预测车速的预测过程中，不仅需要考虑其他车辆在目标路段中当前时刻之后一段时间内的车速，还需要兼顾此前该目标车辆行驶过程中的车速，因此在本步骤中就需要结合目标车辆的第一速度信息、第二速度信息以及交通流信息进行预测。其中，第一速度信息可以理解为当前时刻之前的过滤目标时段内中每个时间单位采集的运行速度所形成的集合。这就说明，第一速度信息实际上是多个速度组成的集合，其中第一速度信息中包含的运行速度的数量可以基于用户选取的目标时段与时间单位进行确定。例如当目标时段为1分钟，时间单位10秒，那么该第一速度集合中就包含6个运行速度。而当目标时段为10分钟，时间单位为1分钟，那么该第一速度集合中就包含10个运行速度。
对于第二速度信息而言，该第二速度信息实际上就是第一速度信息中全部运行速度的 平均值，例如当第一速度信息中包含6个运行速度分别为58、58、60、57、59、56(单位km/h)时，那么第二速度信息就为58(单位km/h)。
另外，在本发明实施例中，基于第一速度信息、第二速度信息以及第三速度信息确定短期预测车速的过程中，可以结合预设神经网络预测模型进行预测，也就是说讲上述三种参数作为输入端进行预测，从而得到预测结果，即短时预测车速。还可以基于第一速度信息来确定车速变化趋势，然后基于第三速度信息来其他车辆在此后一段时间内的车速变化情况，确定二者之间是否相同，如果相同那么说明第一速度信息确定的车速变化趋势与其他车辆基于交通流信息确定的车速变化情况相符，那么就可以基于车速变化趋势对第二速度信息进行修正，从而预测接下来短时间内车速的情况，即短时预测车速。需要说明的是，在本实施例中上述两种方式可以基于用户的实际需要进行选取，上述两种仅仅作为示例性的描述，在此不做限定。
104、基于短时预测车速以及预设速度功率关系，确定目标车辆的短时预期功率，并基于短时预期功率与预设功率阈值生成增程器启动建议。
当确定了短时预测车速后，基于前述步骤中的描述可知，车速和输出功率之间存在对应关系，因此在本实施例中同样利用该预设速度功率关系，基于该短时预测车速来确定短时预期功率。当确定了短时预期功率后，由于该短时预期功率是表征接下来较短时间内车辆的行驶所需的输出功率，那么就可以基于短时预期功率与预设功率阈值进行对比，该预设功率阈值可以理解为满足车辆动力性能所需的输出功率的门槛，这样就可以基于车辆短时所需的工率和满足动力性能所需的门槛进行对比，从而确定是否需要额外再开启增程器来补充功率。
105、基于全局预期功率、短时预期功率以及增程器启动建议，结合预设功率预测算法，预测目标车辆的实时需求功率，以便基于实时需求功率控制目标车辆的实时的油电功率输出比例。
由于车辆在实际的驾驶过程中，尤其是增程式车辆，功率控制过程中是非常复杂的，不仅需要考虑全局预期功率，以保证车辆整体运行里程，还需要保证短时动力需求，即短时预期功率，同时还需要基于当前车辆的动力需求确定增程器是否需要开启或关闭，因此在本实施例中，通过结合全局预期功率、短时预期功率以及增程器启动建议，并基于预设功率预测算法来预测实际需求功率，能够确保在车辆行驶过程中，兼顾上述多种因素进行控制，从而确保了增程式车辆的功率控制的准确性。
本实施例提供了一种增程式车辆的功率控制方法，在本申请实施例中，首先基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，然后，基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略，之后基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，之后基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设 功率阈值生成增程器启动建议；最后基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例，从而实现对增程式车辆的功率控制功能。与现有技术相比，本申请确定的全局预测功率是基于车辆变速特征和交通流特征确定的全局预测车速确定的，且所述交通流信息用于表征其他车辆在所述目标线路的平均车速，也就是说在确定全局预测车速时结合了其他车辆行驶情况，同时车辆变速特征又是基于车辆变速限值和车辆驾驶风格确定的，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况，因此车辆变速特征能够体现当前车辆在行驶过程中车速变化的特点，因此可以确保全局预测车速能够兼顾当前车辆的行驶特点和其他车辆在同样线路上的行驶情况，从而在体现了当前车辆的行驶特点的同时无需该车辆在当前线路上行驶也能够确定车辆在整个线路上的全局预测车速的确定，继而保证了全局预期功率的准确性，无需考虑当前道路车况进行匹配的过程，提高了车辆功率控制的准确性。另外，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值，也就是说能够在确定短时预测车速的过程中兼顾本车辆在当前时刻之前的行驶情况结合其他车辆在当前时刻之后可能的行驶情况进行短时预测车速预测，确保了预测结果的准确性，也就确保了短时预期功率的准确性，继而为基于短时预期功率与预设功率阈值对比来确定增程器启动建议的准确性奠定了基础。这样，基于全局预期功率、短时预期功率以及增程器启动建议进行目标车辆的实时需求工功率的确定，能够确保在确定车辆工况的过程中，既能顾及长期运行时的功率需求，还能考虑到短时功率需求，并在此基础上可以基于增程器启动建议进行功率管理，确定了对增程式车辆的功率控制的准确性。
以下为了更加详细地说明，本申请实施例提供了另一种访问控制方法，具体如图2所示，该方法包括：
201、基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于车辆变速特征及交通流信息确定目标车辆在目标线路中的全局预测车速。
其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况。
具体的，所述车速变速特征具体可为包括变速修正参数。该变速修正参数可以理解为驾驶员驾驶车辆过程中，基于其驾驶风格对车辆变速限值进行调整后得到的参数，能够对车速变化(加速、减速)进行修正。
基于此，本步骤在执行时可以为：
首先，获取所述目标车辆的历史行车数据，并基于所述历史行车数据确定所述车辆驾驶风格。在本步骤中可以理解为通过对目标车辆的历史行车数据进行分析，从而确定出驾驶员在加速、减速过程中的速度变化的特点(猛烈、平缓等)，具体的计算过程可以使用 AI分类算法(例如K-means算法，SVM支持向量机，随机森林算法等)，以驾驶员历史行车数据作为输入，获得驾驶员风格。
然后，获取所述目标车辆的车辆信息，并从所述车辆信息中提取所述车辆变速限值。在本步骤中，基于前述实施例描述可知车辆变速限值实际上跟车辆设计有关，也就是说一旦车型、种类确定的，该车辆的车辆变速限值就可以确定了，因此在本步骤中就需要获取目标车辆的车辆信息，该车辆信息可以理解为包含车辆的品牌、型号、种类、设计等综合信息，能够从该车辆信息中确定当前的目标车辆具体的车辆变速限值是多少。
之后，基于所述车辆驾驶风格对所述车辆变速限值进行修正，得到所述变速修正参数。在本步骤中，当基于前述步骤的描述确定了车辆驾驶风格和车辆变速限值后，就可以在车辆变速限值的基础上，利用车辆驾驶风格进行修正，得到修正后的值就是该变速修正参数，即能够体现目标车辆在车速变化时的特点的参数。
再之后，获取所述目标车辆当前的行驶信息，并基于所述目标线路获取其他车辆在所述目标线路中的行驶数据，再基于所述行驶数据确定所述平均车速作为所述交通流信息，所述行驶信息至少包括所述目标线路。在本步骤中，由于预测全局预测车速的过程中需要结合其他车辆的在当前的目标线路的行驶情况作为参考，因此就需要基于行驶信息确定出目标线路，并通过云端或大数据获取到其他车辆在该目标线路中行驶数据后，基于该行驶数据确定出平均车速作为交通流信息。
最后，根据所述变速修正参数对所述交通流信息进行修正，得到所述全局预测车速。由于变速修正参数能够体现目标车辆行驶时的车辆速度变化的特点，因此利用变速修正参数对交通流信息进行修正，得到全局预测车速就能够体现出目标车辆的行驶特点，使预测出的速度更为贴近实际的驾驶情况，确保了全局预测车速的准确性。
202、基于全局预测车速和预设速度功率关系，确定目标车辆的全局预期功率，并基于全局预期功率确定目标车辆的长期控制策略。
具体的，所述预设速度功率关系包括车辆动力学公式。该车辆动力学公式，又叫车辆动力学方程，是一种专用于利用车速计算输出功率的公式。
本步骤在执行时具体可以为：
通过所述车辆动力学公式以及所述全局预测车速，计算所述目标车辆的所述全局预期功率；
根据所述全局预期功率以及等效燃油控制策略确定所述目标车辆的等效燃油因子，并基于所述等效燃油因子确定所述目标车辆的所述长期控制策略；其中，所述等效燃油控制策略用于基于最经济方式控制所述目标车辆行驶时的燃油、电能之间的控制规则，所述等效燃油因子为符合所述目标车辆在所述目标线路中行驶的油电输出比例。
在本实施例中，在基于车辆动力学公式，计算出对应全局预测车速的全局预期功率之后，还需要确定当前目标车辆的长期控制策略。在这个过程中，对于新能源车辆，尤其是增程式车辆而言，实际上就是确定在目标车辆在整个目标线路行驶过程中的燃油输出的功率和电能输出的功率之间的比例关系，即等效燃油因子。因此，在本步骤中就需要基于全 局预期功率以及等效燃油控制策略来确定整个目标线路行驶过程中电能和燃油之间功率输出的分配情况。其中该等效燃油控制策略可以理解为一种常规的确定油电输出过程中如何确定最经济的策略。这样确定出等效燃油因子后，实际上就确定了接下啦整个目标线路中电能和燃油之间输出功率的分配情况，从而基于此确定长期控制策略。
203、基于目标车辆的第一速度信息、第二速度信息以及交通流信息确定目标车辆的短时预测车速。
其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值。
具体的，本步骤在执行时可以为：
步骤A、获取所述目标车辆的在所述目标线路的已行驶数据，并基于所述已行驶数据中提取在所述目标时段内的每个单位时间对应的行驶速度，并将对应所述目标时段的多个所述行驶速度确定为所述第一速度信息；
步骤B、根据所述第一速度信息中的全部所述行驶速度计算平均值，作为为所述第二速度信息；
步骤C、根据所述第一速度信息、所述第二速度信息以及交通流信息，并利用所述预设短时车速预测模型执行预测操作，得到所述短时预测车速，其中，所述预设短时车速预测模型是基于预设神经网络算法进行训练得到的车速预测模型，所述预设神经网络算法包括非线性自回归神经网络算法以及长短期记忆神经网络算法。
在本实施例中，为了精准预测未来短时间内的车速，即短时预测车速，可以以当前时刻为起点，将未来m时间内的车速记作
Figure PCTCN2022137904-appb-000001
对于多步预测，即一段时间以后的速度预测时，也就是m>1。由于未来的车速与过去一段时间的动态变化和平均车速存在关联，同时还要参考其他车辆在未来一段时间(目标时段)内的平均车速，因此可将
Figure PCTCN2022137904-appb-000002
用如下公式表示：
Figure PCTCN2022137904-appb-000003
在公式1中，
Figure PCTCN2022137904-appb-000004
表示从当前时刻t到过去d′秒的车速序列，即第一速度信息中多个运行车速形成的集合，而
Figure PCTCN2022137904-appb-000005
表示当前时刻t之前过去d′秒的平均速度。
Figure PCTCN2022137904-appb-000006
表示从当前时刻t开始之后m′秒内的平均速度值，也就是交通流信息所确定的其他车辆行驶情况。
基于公式1可知，为了实现对未来车速的预测，关键是求得函数f的实际算法。在本实施例中可以预先使用基于AI的动态时间序列预测算法来求解函数f，也就是说，基于神经网络算法，其中包括带输入的非线性自回归神经网络(NARX)和长短期记忆神经网络(LSTM)，以及样本数据进行训练得到的车速预测模型。之后再将第一速度信息、所述第二速度信息以及交通流信息作为输入，就能够基于预测得到对应的预测结果，作为短时预预测车速。
204、基于短时预测车速以及预设速度功率关系，确定目标车辆的短时预期功率，并基于短时预期功率与预设功率阈值生成增程器启动建议。
具体的，本步骤在执行时可以为：
首先，通过所述车辆动力学公式以及所述短时预测车速，计算所述目标车辆的所述短时预期功率，在本步骤中，所述车辆动力学公式与前述步骤中的描述一致，作为常用的计算功率的公式，在此不做赘述。
然后，判断所述短时预期功率是否超过所述预设功率阈值；
其中，若超过，则确定启动所述增程器；反之，若未超过，则确定关闭所述增程器。
由于短时预期功率表征了目标车辆在接下来短时间内所需的功率，而预设功率阈值则为满足车辆动力所设置的功率门槛，因此在确定短时预期功率超过预设功率阈值说明输出功率不足，需要开启增程器补充功率缺口，反之则说明输出功率已满足，不需要开启增程器。
205、获取车辆状态信息，并从车辆状态信息中提取增程器状态信息以及电池状态信息。
由于在实际应用中，增程器的状态和电池的状态也同样会对增程式车辆的输出功率造成影响，因此在进行功率控制的过程中也需要考虑到上述两个因素，基于此在本实施例中就需要获取车辆状态信息，该车辆状态信息可以理解为包含车辆整体各个部件和系统状态的综合信息，然后从该车辆状态信息中提取增程器状态信息和电池状态信息。
需要说明的是，该车辆状态信息可以是基于车机系统中实时获取的，也可以通过指令控制的方式向车机系统下达指令，然后基于车机系统从各个传感器的反馈信息对相应参数进行获取，例如，从电池状态传感器和增程器状态传感器采集到的数据进行获取。在此，对于获取方式不做限定，以用户实际需求的方式为准。
206、基于全局预期功率、短时预期功率以及增程器启动建议，结合预设功率预测算法，预测目标车辆的实时需求功率，以便基于实时需求功率控制目标车辆的实时的油电功率输出比例。
基于前述步骤的的描述可知，由于在实际应用中增程器状态和电池状态也会对功率控制过程造成影响，因此，本步骤在执行时可以为：
根据所述全局预期功率、所述短时预期功率、所述增程器启动建议、所述增程器状态信息以及所述电池状态信息，结合所述预设功率预测算法，确定所述增程器的实际需求功率，作为所述实时需求功率。
这样确定实时需求功率的过程中就确保了兼顾对电池、增程器状态的兼顾，从而确保了得到的实时需求功率更为符合实际驾驶情况，从而确保了功率
为了实现上述目的，根据本申请的另一方面，本申请实施例还提供了一种存储介质，所述存储介质包括存储的程序，其中，在所述程序运行时控制所述存储介质所在设备执行上述所述的增程式车辆的功率控制方法。
为了实现上述目的，根据本申请的另一方面，本申请实施例还提供了一种增程式车辆的功率控制装置，所述装置包括存储介质；及一个或者多个处理器，所述存储介质与所述处理器耦合，所述处理器被配置为执行所述存储介质中存储的程序指令；所述程序指令运 行时执行上述所述的增程式车辆的功率控制方法。
进一步的，作为对上述图1及图2所示方法的实现，本申请另一实施例还提供了一种增程式车辆的功率控制装置。该增程式车辆的功率控制装置实施例与前述方法实施例对应，为便于阅读，本增程式车辆的功率控制装置实施例不再对前述方法实施例中的细节内容进行逐一赘述，但应当明确，本实施例中的系统能够对应实现前述方法实施例中的全部内容。具体如图3所示，该增程式车辆的功率控制装置包括：
第一确定单元31，可以用于基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，其中，所述交通流信息可以用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值可以用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格可以用于表征所述目标车辆在加速或减速过程中速度变化情况；
第二确定单元32，可以用于基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略；
第三确定单元33，可以用于基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值；
第四确定单元34，可以用于基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；
预测单元35，可以用于基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例。
进一步的，如图4所示，所述车速变速特征包括变速修正参数；
所述第一确定单元31，包括：
确定模块311，可以用于获取所述目标车辆的历史行车数据，并基于所述历史行车数据确定所述车辆驾驶风格；
提取模块312，可以用于获取所述目标车辆的车辆信息，并从所述车辆信息中提取所述车辆变速限值；
第一修正模块313，可以用于基于所述车辆驾驶风格对所述车辆变速限值进行修正，得到所述变速修正参数；
获取模块314，可以用于获取所述目标车辆当前的行驶信息，并基于所述目标线路获取其他车辆在所述目标线路中的行驶数据，再基于所述行驶数据确定所述平均车速作为所述交通流信息，所述行驶信息至少包括所述目标线路；
第二修正模块315，可以用于根据所述变速修正参数对所述交通流信息进行修正，得到所述全局预测车速。
进一步的，如图4所示，所述预设速度功率关系包括车辆动力学公式；
所述第二确定单元32，包括：
计算模块321，可以用于通过所述车辆动力学公式以及所述全局预测车速，计算所述目标车辆的所述全局预期功率；
确定模块322，可以用于根据所述全局预期功率以及等效燃油控制策略确定所述目标车辆的等效燃油因子，并基于所述等效燃油因子确定所述目标车辆的所述长期控制策略；其中，所述等效燃油控制策略可以用于基于最经济方式控制所述目标车辆行驶时的燃油、电能之间的控制规则，所述等效燃油因子为符合所述目标车辆在所述目标线路中行驶的油电输出比例。
进一步的，如图4所示，所述第三确定单元33，包括：
提取模块331，可以用于获取所述目标车辆的在所述目标线路的已行驶数据，并基于所述已行驶数据中提取在所述目标时段内的每个单位时间对应的行驶速度，并将对应所述目标时段的多个所述行驶速度确定为所述第一速度信息；
计算模块332，可以用于根据所述第一速度信息中的全部所述行驶速度计算平均值，作为为所述第二速度信息；
预测模块333，可以用于根据所述第一速度信息、所述第二速度信息以及交通流信息，并利用所述预设短时车速预测模型执行预测操作，得到所述短时预测车速，其中，所述预设短时车速预测模型是基于预设神经网络算法进行训练得到的车速预测模型，所述预设神经网络算法包括非线性自回归神经网络算法以及长短期记忆神经网络算法。
进一步的，如图4所示，所述第四确定单元34，包括：
计算模块341，可以用于通过所述车辆动力学公式以及所述短时预测车速，计算所述目标车辆的所述短时预期功率；
判断模块342，可以用于判断所述短时预期功率是否超过所述预设功率阈值；
第一执行模块343，可以用于若判断所述短时预期功率超过所述预设功率阈值，则确定启动所述增程器；
第二执行模块344，可以用于若判断所述短时预期功率未超过所述预设功率阈值，则确定关闭所述增程器。
进一步的，如图4所示，所述装置还包括：
获取单元36，可以用于获取车辆状态信息，并从所述车辆状态信息中提取增程器状态信息以及电池状态信息；
所述预测单元35，具体可以用于根据所述全局预期功率、所述短时预期功率、所述增程器启动建议、所述增程器状态信息以及所述电池状态信息，结合所述预设功率预测算法，确定所述增程器的实际需求功率，作为所述实时需求功率。
本申请实施例提供一种增程式车辆的功率控制方法及装置，在本申请实施例中，首先基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，然后，基于所述全局 预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略，之后基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，之后基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；最后基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例，从而实现对增程式车辆的功率控制功能。与现有技术相比，本申请确定的全局预测功率是基于车辆变速特征和交通流特征确定的全局预测车速确定的，且所述交通流信息用于表征其他车辆在所述目标线路的平均车速，也就是说在确定全局预测车速时结合了其他车辆行驶情况，同时车辆变速特征又是基于车辆变速限值和车辆驾驶风格确定的，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况，因此车辆变速特征能够体现当前车辆在行驶过程中车速变化的特点，因此可以确保全局预测车速能够兼顾当前车辆的行驶特点和其他车辆在同样线路上的行驶情况，从而在体现了当前车辆的行驶特点的同时无需该车辆在当前线路上行驶也能够确定车辆在整个线路上的全局预测车速的确定，继而保证了全局预期功率的准确性，无需考虑当前道路车况进行匹配的过程，提高了车辆功率控制的准确性。另外，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值，也就是说能够在确定短时预测车速的过程中兼顾本车辆在当前时刻之前的行驶情况结合其他车辆在当前时刻之后可能的行驶情况进行短时预测车速预测，确保了预测结果的准确性，也就确保了短时预期功率的准确性，继而为基于短时预期功率与预设功率阈值对比来确定增程器启动建议的准确性奠定了基础。这样，基于全局预期功率、短时预期功率以及增程器启动建议进行目标车辆的实时需求工功率的确定，能够确保在确定车辆工况的过程中，既能顾及长期运行时的功率需求，还能考虑到短时功率需求，并在此基础上可以基于增程器启动建议进行功率管理，确定了对增程式车辆的功率控制的准确性。本申请实施例还提供了一种增程式车辆的功率控制装置，所述装置包括存储介质；及一个或者多个处理器，所述存储介质与所述处理器耦合，所述处理器被配置为执行所述存储介质中存储的程序指令；所述程序指令运行时执行上述所述的增程式车辆的功率控制方法。
本申请实施例提供了一种设备，设备包括处理器、存储器及存储在存储器上并可在处理器上运行的程序，处理器执行程序时实现以下步骤：基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况；基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于 所述全局预期功率确定所述目标车辆的长期控制策略；基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值；基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例。
进一步的，所述车速变速特征包括变速修正参数；
所述基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，包括：
获取所述目标车辆的历史行车数据，并基于所述历史行车数据确定所述车辆驾驶风格；
获取所述目标车辆的车辆信息，并从所述车辆信息中提取所述车辆变速限值；
基于所述车辆驾驶风格对所述车辆变速限值进行修正，得到所述变速修正参数；
获取所述目标车辆当前的行驶信息，并基于所述目标线路获取其他车辆在所述目标线路中的行驶数据，再基于所述行驶数据确定所述平均车速作为所述交通流信息，所述行驶信息至少包括所述目标线路；
根据所述变速修正参数对所述交通流信息进行修正，得到所述全局预测车速。
进一步的，所述预设速度功率关系包括车辆动力学公式；
所述基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略，包括：
通过所述车辆动力学公式以及所述全局预测车速，计算所述目标车辆的所述全局预期功率；
根据所述全局预期功率以及等效燃油控制策略确定所述目标车辆的等效燃油因子，并基于所述等效燃油因子确定所述目标车辆的所述长期控制策略；其中，所述等效燃油控制策略用于基于最经济方式控制所述目标车辆行驶时的燃油、电能之间的控制规则，所述等效燃油因子为符合所述目标车辆在所述目标线路中行驶的油电输出比例。
进一步的，所述基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，包括：
获取所述目标车辆的在所述目标线路的已行驶数据，并基于所述已行驶数据中提取在所述目标时段内的每个单位时间对应的行驶速度，并将对应所述目标时段的多个所述行驶速度确定为所述第一速度信息；
根据所述第一速度信息中的全部所述行驶速度计算平均值，作为为所述第二速度信息；
根据所述第一速度信息、所述第二速度信息以及交通流信息，并利用所述预设短时车速预测模型执行预测操作，得到所述短时预测车速，其中，所述预设短时车速预测模型是基于预设神经网络算法进行训练得到的车速预测模型，所述预设神经网络算法包括非线性 自回归神经网络算法以及长短期记忆神经网络算法。
进一步的，所述基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议，包括：
通过所述车辆动力学公式以及所述短时预测车速，计算所述目标车辆的所述短时预期功率；
判断所述短时预期功率是否超过所述预设功率阈值；
若超过，则确定启动所述增程器；
若未超过，则确定关闭所述增程器。
进一步的，在所述基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率之前，所述方法还包括：
获取车辆状态信息，并从所述车辆状态信息中提取增程器状态信息以及电池状态信息；
所述基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，包括：
根据所述全局预期功率、所述短时预期功率、所述增程器启动建议、所述增程器状态信息以及所述电池状态信息，结合所述预设功率预测算法，确定所述增程器的实际需求功率，作为所述实时需求功率。
本申请还提供了一种计算机程序产品，当在数据处理设备上执行时，适于执行初始化有如下方法步骤的程序代码：基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况；基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略；基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值；基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例。
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请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，本申请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。
本申请是参照根据本申请实施例的方法、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设备上，使得在计算机或其他可编程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。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
存储器可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。存储器是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，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、商品或者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、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括要素的过程、方法、商品或者设备中还存在另外的相同要素。
本领域技术人员应明白，本申请的实施例可提供为方法、系统或计算机程序产品。因此，本申请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，本申请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。
以上仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。

Claims (14)

  1. 一种增程式车辆的功率控制方法，其特征在于，所述方法包括：
    基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况；
    基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略；
    基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值；
    基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；
    基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例。
  2. 根据权利要求1所述的方法，其特征在于，所述车速变速特征包括变速修正参数；
    所述基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，包括：
    获取所述目标车辆的历史行车数据，并基于所述历史行车数据确定所述车辆驾驶风格；
    获取所述目标车辆的车辆信息，并从所述车辆信息中提取所述车辆变速限值；
    基于所述车辆驾驶风格对所述车辆变速限值进行修正，得到所述变速修正参数；
    获取所述目标车辆当前的行驶信息，并基于所述目标线路获取其他车辆在所述目标线路中的行驶数据，再基于所述行驶数据确定所述平均车速作为所述交通流信息，所述行驶信息至少包括所述目标线路；
    根据所述变速修正参数对所述交通流信息进行修正，得到所述全局预测车速。
  3. 根据权利要求1所述的方法，其特征在于，所述预设速度功率关系包括车辆动力学公式；
    所述基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略，包括：
    通过所述车辆动力学公式以及所述全局预测车速，计算所述目标车辆的所述全局预期功率；
    根据所述全局预期功率以及等效燃油控制策略确定所述目标车辆的等效燃油因子，并 基于所述等效燃油因子确定所述目标车辆的所述长期控制策略；其中，所述等效燃油控制策略用于基于最经济方式控制所述目标车辆行驶时的燃油、电能之间的控制规则，所述等效燃油因子为符合所述目标车辆在所述目标线路中行驶的油电输出比例。
  4. 根据权利要求1所述的方法，其特征在于，所述基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，包括：
    获取所述目标车辆的在所述目标线路的已行驶数据，并基于所述已行驶数据中提取在所述目标时段内的每个单位时间对应的行驶速度，并将对应所述目标时段的多个所述行驶速度确定为所述第一速度信息；
    根据所述第一速度信息中的全部所述行驶速度计算平均值，作为为所述第二速度信息；
    根据所述第一速度信息、所述第二速度信息以及交通流信息，并利用所述预设短时车速预测模型执行预测操作，得到所述短时预测车速，其中，所述预设短时车速预测模型是基于预设神经网络算法进行训练得到的车速预测模型，所述预设神经网络算法包括非线性自回归神经网络算法以及长短期记忆神经网络算法。
  5. 根据权利要求1所述的方法，其特征在于，所述基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议，包括：
    通过所述车辆动力学公式以及所述短时预测车速，计算所述目标车辆的所述短时预期功率；
    判断所述短时预期功率是否超过所述预设功率阈值；
    若超过，则确定启动所述增程器；
    若未超过，则确定关闭所述增程器。
  6. 根据权利要求1-5中任一项所述的方法，其特征在于，在所述基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率之前，所述方法还包括：
    获取车辆状态信息，并从所述车辆状态信息中提取增程器状态信息以及电池状态信息；
    所述基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，包括：
    根据所述全局预期功率、所述短时预期功率、所述增程器启动建议、所述增程器状态信息以及所述电池状态信息，结合所述预设功率预测算法，确定所述增程器的实际需求功率，作为所述实时需求功率。
  7. 一种增程式车辆的功率控制装置，其特征在于，所述装置包括：
    第一确定单元，用于基于目标车辆的车辆驾驶风格以及车辆变速限值确定车辆变速特征，并基于所述车辆变速特征及交通流信息确定所述目标车辆在目标线路中的全局预测车速，其中，所述交通流信息用于表征其他车辆在所述目标线路的平均车速，所述车辆变速限值用于表征所述目标车辆在加速或减速过程中车辆允许的最大速度，所述车辆驾驶风格用于表征所述目标车辆在加速或减速过程中速度变化情况；
    第二确定单元，用于基于所述全局预测车速和预设速度功率关系，确定所述目标车辆的全局预期功率，并基于所述全局预期功率确定所述目标车辆的长期控制策略；
    第三确定单元，用于基于所述目标车辆的第一速度信息、第二速度信息以及交通流信息确定所述目标车辆的短时预测车速，其中，所述第一速度信息为所述目标车辆在过去目标时段内的在每个时间单位采集的运行速度的集合，所述第二速度为所述过去目标时段内全部所述运行速度的平均值；
    第四确定单元，用于基于所述短时预测车速以及所述预设速度功率关系，确定所述目标车辆的短时预期功率，并基于所述短时预期功率与预设功率阈值生成增程器启动建议；
    预测单元，用于基于所述全局预期功率、所述短时预期功率以及所述增程器启动建议，结合预设功率预测算法，预测所述目标车辆的实时需求功率，以便基于所述实时需求功率控制所述目标车辆的实时的油电功率输出比例。
  8. 根据权利要求7所述的装置，其特征在于，所述车速变速特征包括变速修正参数；
    所述第一确定单元，包括：
    确定模块，用于获取所述目标车辆的历史行车数据，并基于所述历史行车数据确定所述车辆驾驶风格；
    提取模块，用于获取所述目标车辆的车辆信息，并从所述车辆信息中提取所述车辆变速限值；
    第一修正模块，用于基于所述车辆驾驶风格对所述车辆变速限值进行修正，得到所述变速修正参数；
    获取模块，用于获取所述目标车辆当前的行驶信息，并基于所述目标线路获取其他车辆在所述目标线路中的行驶数据，再基于所述行驶数据确定所述平均车速作为所述交通流信息，所述行驶信息至少包括所述目标线路；
    第二修正模块，用于根据所述变速修正参数对所述交通流信息进行修正，得到所述全局预测车速。
  9. 根据权利要求7所述的装置，其特征在于，所述预设速度功率关系包括车辆动力学公式；
    所述第二确定单元，包括：
    计算模块，用于通过所述车辆动力学公式以及所述全局预测车速，计算所述目标车辆的所述全局预期功率；
    确定模块，用于根据所述全局预期功率以及等效燃油控制策略确定所述目标车辆的等效燃油因子，并基于所述等效燃油因子确定所述目标车辆的所述长期控制策略；其中，所述等效燃油控制策略用于基于最经济方式控制所述目标车辆行驶时的燃油、电能之间的控制规则，所述等效燃油因子为符合所述目标车辆在所述目标线路中行驶的油电输出比例。
  10. 根据权利要求7所述的装置，其特征在于，所述第三确定单元，包括：
    提取模块，用于获取所述目标车辆的在所述目标线路的已行驶数据，并基于所述已行驶数据中提取在所述目标时段内的每个单位时间对应的行驶速度，并将对应所述目标时段 的多个所述行驶速度确定为所述第一速度信息；
    计算模块，用于根据所述第一速度信息中的全部所述行驶速度计算平均值，作为为所述第二速度信息；
    预测模块，用于根据所述第一速度信息、所述第二速度信息以及交通流信息，并利用所述预设短时车速预测模型执行预测操作，得到所述短时预测车速，其中，所述预设短时车速预测模型是基于预设神经网络算法进行训练得到的车速预测模型，所述预设神经网络算法包括非线性自回归神经网络算法以及长短期记忆神经网络算法。
  11. 根据权利要求7所述的装置，其特征在于，所述第四确定单元，包括：
    计算模块，用于通过所述车辆动力学公式以及所述短时预测车速，计算所述目标车辆的所述短时预期功率；
    判断模块，用于判断所述短时预期功率是否超过所述预设功率阈值；
    第一执行模块，用于若判断所述短时预期功率超过所述预设功率阈值，则确定启动所述增程器；
    第二执行模块，用于若判断所述短时预期功率未超过所述预设功率阈值，则确定关闭所述增程器。
  12. 根据权利要求7-11中任一项所述的装置，其特征在于，所述装置还包括：
    获取单元，用于获取车辆状态信息，并从所述车辆状态信息中提取增程器状态信息以及电池状态信息；
    所述预测单元，具体用于根据所述全局预期功率、所述短时预期功率、所述增程器启动建议、所述增程器状态信息以及所述电池状态信息，结合所述预设功率预测算法，确定所述增程器的实际需求功率，作为所述实时需求功率。
  13. 一种存储介质，其特征在于，所述存储介质包括存储的程序，其中，在所述程序运行时控制所述存储介质所在设备执行权利要求1至6中任一项所述的增程式车辆的功率控制方法。
  14. 一种增程式车辆的功率控制装置，其特征在于，所述装置包括存储介质；及一个或者多个处理器，所述存储介质与所述处理器耦合，所述处理器被配置为执行所述存储介质中存储的程序指令；所述程序指令运行时执行权利要求1至6中任一项所述的增程式车辆的功率控制方法。
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