CN115689083A

CN115689083A - Predictive performance management method and device, electronic equipment and storage medium

Info

Publication number: CN115689083A
Application number: CN202211425971.1A
Authority: CN
Inventors: 刘小钦; 孙昊; 解明超; 刘畅
Original assignee: Zhejiang Geely Holding Group Co Ltd; Zhejiang Remote Commercial Vehicle R&D Co Ltd; Zhejiang Geely Remote New Energy Commercial Vehicle Group Co Ltd
Current assignee: Zhejiang Geely Holding Group Co Ltd; Zhejiang Remote Commercial Vehicle R&D Co Ltd; Zhejiang Geely Remote New Energy Commercial Vehicle Group Co Ltd
Priority date: 2022-11-14
Filing date: 2022-11-14
Publication date: 2023-02-03

Abstract

The application discloses a prediction performance management method and device, electronic equipment and a storage medium, and relates to the technical field of energy management strategies. In the method, the current position of a vehicle and the target position of a driving destination are obtained; then, screening out at least one candidate driving route comprising the current position and the target position from a preset candidate driving route set; further, determining the route driving cost required by the vehicle on each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the at least one candidate driving route; and finally, when the driving request is received, driving the vehicle to run on the target running route according to the running mode carried by the driving request. In this way, the driving requirements of various types are met.

Description

Predictive performance management method and device, electronic equipment and storage medium

Technical Field

The present application relates to the technical field of energy management policies, and in particular, to a method and an apparatus for predictive performance management, an electronic device, and a storage medium.

Background

In recent years, with the increasing demand for energy conservation and emission reduction, new energy vehicles are developed at a high speed, and compared with traditional fuel vehicles, the new energy vehicles are beneficial to saving energy and reducing the emission of harmful gases, so that the new energy vehicles undoubtedly become an important direction for the development of vehicles in the future under the pressure of energy and environmental protection.

At present, in the research process of new energy vehicles, how to improve the energy utilization rate of vehicles and solve the energy supply of vehicles as far as possible on the premise of ensuring the dynamic property of the vehicles is an important problem that needs to be solved.

Further, in order to effectively solve the above problems, by formulating an energy management strategy, reasonable power distribution among vehicle power components can be effectively realized, and vehicle fuel consumption can be reduced, thereby improving energy utilization of the vehicle and solving energy replenishment of the vehicle.

For example, gradient information of a road information sampling point in front of the vehicle is obtained and matched with road sections, and gradient values of all road sections in front of the vehicle are determined; then, merging the road sections according to the gradient values of the road sections, dividing the road in front of the vehicle into road sections with different road shapes, and determining the road gradients corresponding to the different road sections; further, according to the road section division condition and the road gradient corresponding to each road section, under the conditions of the expected cruising speed and the road speed limit set by the driver, determining a planned speed track which enables the energy consumption of a vehicle power component to be minimum by using a dynamic planning algorithm; and finally, determining the energy distribution rule of the hybrid power component by adopting a rolling optimization algorithm according to the planned speed track and the road shape change of the future road in front of the vehicle.

However, by adopting the above energy management strategy, the rolling optimization algorithm is only used to determine the energy distribution rule of the hybrid component according to the planned vehicle speed trajectory and the road shape change of the future road in front of the vehicle, which may result in a situation that the corresponding driving requirement cannot be met, for example, when the driving situation that the route driving cost is the lowest is met, the driving destination cannot be reached within the set time range, so that the corresponding driving requirement cannot be met.

Therefore, the driving requirements of various types cannot be met by adopting the mode.

Disclosure of Invention

The embodiment of the application provides a method and a device for managing forecast performance, electronic equipment and a storage medium, which are used for meeting driving requirements of various types.

In a first aspect, an embodiment of the present application provides a method for forecasting performance management, where the method includes:

the method comprises the steps of firstly, acquiring the current position of a vehicle and the target position of a driving destination;

screening out at least one candidate driving route comprising a current position and a target position from a preset candidate driving route set;

step three, determining the route driving cost required by the vehicle on each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the at least one candidate driving route;

and step four, when the driving request is received, driving the vehicle to run on the target running route according to the driving mode carried by the driving request.

In a second aspect, an embodiment of the present application further provides a predictive energy management apparatus, where the apparatus includes:

the response module is used for acquiring the current position of the vehicle and the target position of the driving destination;

the screening module is used for screening out at least one candidate driving route comprising a current position and a target position from a preset candidate driving route set;

the determining module is used for determining the route driving cost required by the vehicle on the at least one candidate driving route based on the road condition information of the at least one candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the at least one candidate driving route;

and the driving module is used for driving the vehicle to run on the target running route according to the running mode carried by the running request when the running request is received.

In a possible embodiment, when determining, in step three, the route driving cost required by the vehicle for each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, the determining module is specifically configured to:

for at least one candidate driving route, respectively executing the following operations:

obtaining road section information of each candidate driving road section contained in one candidate driving route from the road condition information of the candidate driving route;

respectively determining the sub-energy consumption amount required by the vehicle on each candidate driving road section based on the road section characteristics contained in each acquired road section information;

determining the energy consumption cost required by the vehicle on a candidate driving route based on the obtained sub energy consumption and the energy supply information of a candidate driving route;

and determining the route running cost of the vehicle on one candidate running route based on the energy consumption cost and the road running cost corresponding to the one candidate running route.

In a possible embodiment, when the sub-energy consumption amount required by the vehicle on each candidate driving section is respectively determined based on the section features respectively contained in the obtained section information, the determining module is specifically configured to:

for each link information, the following operations are respectively performed:

analyzing the road section information to obtain road section characteristics of corresponding candidate driving road sections;

determining the driving power and the driving time of the vehicle on the candidate driving road section based on the characteristic interval to which the road section characteristics belong;

and determining the sub-energy consumption amount required by the vehicle on the candidate driving road section based on the driving power and the driving time.

In a possible embodiment, when a target driving route satisfying a preset route driving cost condition is selected from the at least one candidate driving route in step three, the determining module is specifically configured to:

determining a running cost ranking sequence of each of the at least one candidate running route based on a route running cost required by the vehicle on each of the at least one candidate running route;

and screening out a target driving route meeting the energy consumption condition from at least one candidate driving route based on the obtained arrangement sequence of the driving costs.

In a possible embodiment, in step four, when the vehicle is driven to travel on the target travel route according to the travel mode carried by the travel request, the driving module is specifically configured to:

if the driving mode is the cost priority mode, determining the pure electric driving mileage of the vehicle based on the residual energy storage capacity of the battery of the vehicle and the actual road condition of the target driving road section;

and when the pure electric endurance mileage is determined and the power conversion station does not exist, triggering a range extender of the vehicle, and generating power according to the power generation requirement of the power conversion station outside the pure electric endurance mileage so as to enable the vehicle to run on the target running route.

In a possible embodiment, in step four, the driving module is specifically configured to, when the vehicle is driven on the target driving route according to the driving mode carried by the driving request:

if the driving mode is the time priority mode, determining the pure electric endurance mileage of the vehicle based on the available driving time of the vehicle and the actual road condition of the target driving road section;

and when the pure electric endurance mileage is determined to meet the preset first pure electric endurance mileage condition, triggering the range extender to generate power according to the power generation requirement reaching the power conversion station, so that the vehicle runs on the target running route.

if the driving mode is the self-defined mode, when a second pure electric endurance mileage condition preset by the pure electric endurance mileage is determined, the range extender is triggered to generate electricity according to the electricity generation requirement of reaching the driving destination, so that the vehicle runs on the target driving route.

In a possible embodiment, during driving on the target driving route according to the driving mode carried by the driving request, the driving module is further configured to:

if the vehicle is currently located in a crowded road section in the target driving route, closing the range extender of the vehicle;

if the vehicle is currently in a smooth road section in the target driving route, starting a range extender;

if an uphill road section meeting the preset uphill road section condition exists in the set distance range in front of the vehicle and the battery discharge power of the vehicle does not meet the requirement of the whole vehicle, starting a range extender;

and if the downhill road section meeting the preset downhill road section condition exists in the set distance range in front of the vehicle, and the residual energy storage capacity of the battery of the vehicle is not more than the total energy recovery amount of the downhill road section, closing the range extender.

In a third aspect, an electronic device is proposed, which comprises a processor and a memory, wherein the memory stores program code, which, when executed by the processor, causes the processor to perform the steps of the predictive performance management method of the first aspect.

In a fourth aspect, a computer-readable storage medium is proposed, which comprises program code for causing an electronic device to perform the steps of the predictive performance management method of the first aspect when the program code runs on the electronic device.

In a fifth aspect, there is provided a computer program product which, when invoked by a computer, causes the computer to perform the steps of the predictive performance management method of the first aspect.

The beneficial effect of this application is as follows:

in the forecast performance management method provided by the embodiment of the application, the current position of a vehicle and the target position of a driving destination are obtained; then, screening out at least one candidate driving route comprising the current position and the target position from a preset candidate driving route set; further, determining the route driving cost required by the vehicle on each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the at least one candidate driving route; and finally, when the driving request is received, driving the vehicle to run on the target running route according to the running mode carried by the driving request.

By adopting the method, the target driving route meeting the preset route driving cost condition is screened out from at least one candidate driving route, and when the driving request is received, the vehicle is driven to drive on the target driving route according to the driving mode carried by the driving request, so that the technical defect that the energy distribution rule of the hybrid power component can not meet the corresponding driving requirement by adopting a rolling optimization algorithm only according to the planned speed track and the road shape change of a future road in front of the vehicle in the prior art can be avoided, and the driving requirements of various types can be met.

Furthermore, other features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. In the drawings:

fig. 1 schematically illustrates an alternative application scenario provided by an embodiment of the present application;

FIG. 2 is a schematic diagram illustrating a method flow of a predictive energy management method according to an embodiment of the present application;

FIG. 3 is a flow chart illustrating a method for determining a route driving cost according to an embodiment of the present application;

fig. 4 is a schematic diagram illustrating a specific application scenario of road segment division provided by an embodiment of the present application;

FIG. 5 is a logic diagram for illustrating an example of sub-energy consumption amount required for determining a candidate driving section according to an embodiment of the application;

fig. 6 is a schematic diagram illustrating a specific application scenario of screening a target driving route according to an embodiment of the present application;

FIG. 7 is a flowchart illustrating a method for a vehicle to travel on a target travel route in a cost-first mode according to an embodiment of the present application;

FIG. 8 is a flowchart illustrating a method for a vehicle to travel on a target travel route in a time-first mode according to an embodiment of the present application;

FIG. 9 is a flowchart illustrating a method for a vehicle to travel on a target travel route in a customized mode according to an embodiment of the present application;

fig. 10 is a schematic diagram illustrating a specific application scenario based on fig. 2 according to an embodiment of the present application;

fig. 11 is a schematic structural diagram illustrating a predictive energy management device provided in an embodiment of the present application;

fig. 12 schematically illustrates a structural diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments, but not all embodiments, of the technical solutions of the present application. All other embodiments obtained by a person skilled in the art without any inventive step based on the embodiments described in the present application are within the scope of the protection of the present application.

It should be noted that "a plurality" is understood as "at least two" in the description of the present application. "and/or" describes the association relationship of the associated object, indicating that there may be three relationships, for example, a and/or B, which may indicate: a exists alone, A and B exist simultaneously, and B exists alone. A is connected with B and can represent: a and B are directly connected and A and B are connected through C. In addition, in the description of the present application, the terms "first," "second," and the like are used for descriptive purposes only and are not intended to indicate or imply relative importance nor order to be construed.

First, the following briefly introduces the design ideas of the embodiments of the present application:

with the advance of double-carbon emission reduction and the rapid development of new energy technology, the sales volume of new energy vehicles is greatly increased, so that the new energy vehicles are more easily concerned by all parties in terms of energy supply and energy utilization efficiency different from the problems of the traditional fuel vehicles.

The predictive energy management is an innovative solution for solving the optimal energy management problem of long-distance trunk heavy truck vehicles, particularly new-energy range-increasing battery-replacing heavy truck vehicles, meeting the battery-replacing and charging core requirements of users, solving the pain points of mileage anxiety and the like and providing optimal whole-process cost for drivers.

The method can be easily seen how to plan the optimal route selection of the journey according to the requirements of the driver aiming at the new energy vehicle for increasing the journey and changing the electricity; how to rationally control the work electricity generation of range extender according to the road type in front of the vehicle to make the vehicle energy consumption reach the optimum state to and according to the economic and timely effect demand of the driver, rationally plan and trade the power station and supply, avoid the battery to appear overcharging simultaneously, just so become the problem that needs to solve.

In view of this, in order to meet the driving requirements of various types under the condition of low energy consumption, the embodiment of the present application provides a method for managing predictive performance, which specifically includes: acquiring the current position of a vehicle and the target position of a driving destination; then, screening out at least one candidate driving route comprising a current position and a target position from a preset candidate driving route set; further, determining the route driving cost required by the vehicle on each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the at least one candidate driving route; and finally, when the driving request is received, driving the vehicle to run on the target running route according to the running mode carried by the driving request.

In particular, preferred embodiments of the present application will be described below with reference to the accompanying drawings of the specification, it being understood that the preferred embodiments described herein are merely for illustrating and explaining the present application, and are not intended to limit the present application, and that the features of the embodiments and examples of the present application may be combined with each other without conflict.

Referring to fig. 1, a schematic diagram of an optional application scenario provided in an embodiment of the present application is shown, where the application scenario includes: the energy management system comprises a charging and replacing energy station information platform 101, a navigation platform 102, a vehicle-mounted large screen 103, a map service platform 104, a global energy management navigation Application (APP) 105 and a power domain controller 106, wherein the global energy management navigation APP105 can receive data or information from the charging and replacing energy station information platform 101, the navigation platform 102, the vehicle-mounted large screen 103, the map service platform 104 and the power domain controller 106.

It should be noted that, the global energy management navigation APP105 is in a vehicle, and can obtain corresponding energy station information, traffic real-time information and a remote map through each Application Programming Interface (API); further, predictive global energy management algorithm software is deployed in power domain controller 106.

For example, after the driver inputs a destination through the vehicle-mounted large screen 103, the global energy management navigation APP105 generates a plurality of planned driving routes according to the current position and the destination position of the vehicle, and sends information of each driving route to the predictive global energy management algorithm software module of the power domain controller 106; then, the predictive global energy management module calculates the energy consumption and the vehicle cost of each route according to the received information of each driving route; further, after the calculation is completed, the power domain controller 106 sends the energy consumption and the vehicle cost corresponding to each route to the global energy management navigation APP105, and the driver selects one route to drive after comprehensively considering the driving time, the cost and other factors; finally, the global energy management navigation APP105 sends the route information selected by the driver to a predictive global energy management algorithm module in the power domain controller 106, and performs subsequent related operations such as global energy prediction.

In the following, the predictive performance management method provided by the exemplary embodiment of the present application is described in conjunction with the application scenario described above and with reference to the drawings, it should be noted that the above system architecture is only shown for the convenience of understanding the spirit and principle of the present application, and the embodiment of the present application is not limited in any way in this respect.

Referring to fig. 2, which is a flowchart illustrating an implementation of a method for forecasting performance management according to an embodiment of the present application, an implementation of the method is as follows:

s201: a current position of the vehicle and a target position of a driving destination are acquired.

Specifically, in step S201, after the automatic navigation of the vehicle is started, the power domain controller may acquire a target position of the driving destination through the driving destination input by the on-board large screen, and acquire a current position of the vehicle through an Over-the-Air (OTA) technique of a navigation map in a map service platform.

It should be noted that the above is only an example, and in the embodiment of the present application, the implementation of the method is not limited, that is, the method may be navigation of a vehicle itself, or may be a mobile phone application program.

S202: screening out at least one candidate driving route comprising the current position and the target position from a preset candidate driving route set.

Specifically, in step S202, after obtaining the current position of the vehicle and the target position of the driving destination, the power domain controller may screen out at least one candidate driving route including the current position and the target position from a preset candidate driving route set based on the obtained current position and target position, where the preset candidate driving route set includes candidate routes for the vehicle to travel in a set area.

Optionally, the power domain controller may generate the plurality of planned driving routes by using a current position of the vehicle as a starting point and a target position of the driving destination as an end point, so as to screen out at least one candidate driving route that meets a preset route similarity condition with the generated plurality of planned driving routes from a preset candidate driving route set.

S203: and determining the route driving cost required by the vehicle on the at least one candidate driving route based on the road condition information of the at least one candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the at least one candidate driving route.

Specifically, in step 203, after screening out at least one candidate driving route, the power domain controller may determine a route driving cost required by the vehicle on the at least one candidate driving route based on road condition information of the at least one candidate driving route, and for the at least one candidate driving route, referring to fig. 3, the following steps are respectively performed:

s301: and obtaining the road section information of each candidate driving road section contained in one candidate driving route from the road condition information of the candidate driving route.

Alternatively, referring to fig. 4, after obtaining a candidate driving route, the power domain controller may divide the candidate driving route into road segments according to a predetermined road segment division threshold value, and obtain corresponding candidate driving road segments, according to the road segment division threshold value, when performing step S301; further, the link information of each candidate driving link may be determined based on the path information of the one candidate driving route acquired by the navigation platform.

For example, the obtained candidate driving routes may be segmented at intervals of 5-30 meters (i.e., the route segment division threshold) to obtain corresponding candidate driving routes, so as to obtain respective route information of the candidate driving routes, such as data information of a slope, a curvature, a planned vehicle speed, traffic information, and the like, according to the route information of the candidate driving routes.

S302: and respectively determining the sub-energy consumption amount required by the vehicle on each candidate driving road section based on the road section characteristics respectively contained in the obtained road section information.

Specifically, after determining the link information of each candidate travel link, the power domain controller may determine the sub-energy consumption amount required by the vehicle on each candidate travel link based on the link characteristics included in each link information, the feature interval to which each link belongs, and the conversion manner between the feature interval and the sub-energy consumption amount when performing step S302.

Optionally, referring to fig. 5, for each obtained link information, the following operations are respectively performed: the power domain controller analyzes the road section information through a predictive global energy management module to obtain the road section characteristics of corresponding candidate driving road sections; secondly, determining the driving power and the driving time of the vehicle on the candidate driving road section based on the characteristic section to which the road section characteristic belongs; finally, determining the sub-energy consumption required by the vehicle on the candidate driving section based on the driving power and the driving time, wherein the prediction formula of the sub-energy consumption is as follows:

Q _n ＝P _n ×T _n

wherein, P _n Represents the driving power, T, required by the nth candidate driving road section _n The driving time required by the nth candidate driving road section is shown, wherein the driving time T is _n Driving power P _n The prediction formula of (c) is specifically as follows:

P _n ＝F _{n running} ×V _n

Wherein S is _n Length of link, V, representing the nth candidate driving link _n Representing the average speed of the vehicle on the nth candidate route segment, F _{n running} The total running resistance of the nth candidate running section is shown, and it should be noted that the total running resistance F _{n running} The calculation formula of (a) is specifically as follows:

F _{n running} ＝F _{n resistance} +F _{n acceleration} +F _{n slope}

Wherein, F _{n resistance} Representing the glide resistance, F, of the n-th candidate driving route section _{n acceleration} Representing the acceleration resistance of the n-th candidate travel section, F _{n slope} The slope resistance of the nth candidate road segment is shown, and it should be noted that the sliding resistance F _{n resistance} Acceleration resistance F _{n acceleration} And slope resistance F _{n slope} The calculation formula of (a) is specifically as follows:

F _{n slope} ＝mg×sinθ

Wherein, V _n Representing the average speed of the vehicle on the nth candidate driving road section, wherein a, b and c are all the sliding resistance coefficients of the vehicle; delta represents a conversion coefficient of the rotating mass of the vehicle, and is related to a flywheel, the rotational inertia of the wheel and the transmission ratio; m represents the mass of the vehicle, g represents the gravitational acceleration, and θ represents the gradient value of the nth-segment candidate travel segment.

It should be noted that the vehicle rotating mass conversion coefficient δ of each vehicle type changes according to the mass of the vehicle, and for example, in the case of a truck, the empirical value of the vehicle rotating mass conversion coefficient δ varies with the mass as shown in table 1:

TABLE 1

Quality of	49T	10T
			δ	1.285	1.05

As can be seen from the above table, the vehicle rotational mass conversion coefficient δ decreases as the mass of the vehicle increases within a certain range.

S303: and determining the energy consumption cost required by the vehicle on a candidate driving route based on the obtained sub-energy consumption amount and the energy supply information of the candidate driving route.

Specifically, in step S303, after determining the sub-energy consumption amounts required by the vehicle on the candidate driving routes respectively, the power domain controller may determine the energy consumption amount required by the vehicle on one candidate driving route based on a preset energy consumption amount calculation formula and the obtained sub-energy consumption amounts, wherein the energy consumption amount calculation formula is specifically as follows:

wherein Q represents the amount of energy consumption required for the candidate travel route, eff _Tol Representing the overall efficiency, Q, of the vehicle system _n Representing the sub-energy consumption amount required by the nth candidate driving section in the candidate driving route, m representing the candidate driving route divided into m candidate driving sections, and it is required to say that the total efficiency Eff of the vehicle system _Tol The calculation formula of (a) is specifically as follows:

Eff _Tol ＝Eff _Mot ×Eff _Re ×Eff _Bat ×Eff _Pt ×Eff _Eac

wherein, eff _Mot Indicating the motor efficiency, eff, of the vehicle _Re Indicating range extender efficiency, eff, of the vehicle _Bat Indicating the battery efficiency, eff, of the vehicle _Pt Representing the driveline efficiency, eff, of the vehicle _Eac The efficiency of the electric accessory of the vehicle is shown, and the efficiency Eff of the motor is explained _Mot Efficiency Eff of range extender _Re Battery efficiency Eff _Bat And drive train efficiency Eff _Pt And electrical accessory efficiency Eff _Eac The calculation methods of (a) are respectively as follows:

efficiency Eff of the motor _Mot : according to the efficiency of the motor system, the motor universal characteristic efficiency MAP graph is obtained through interpolation calculation;

efficiency Eff of range extender _Re : obtaining the characteristic efficiency MAP according to the range extender system;

battery with a battery cellEfficiency Eff _Bat : obtaining the battery charging and discharging efficiency according to a MAP graph;

driveline efficiency Eff _Pt : including transmission efficiency Eff _Tras And rear axle efficiency Eff _Rear I.e. Eff _Pt ＝Eff _Tras ×Eff _Rear ；

Efficiency Eff of electrical accessory _Eac : efficiency Eff of ACCM of air conditioner _Ac DC/DC converter DCDC efficiency Eff _DCDC Steering efficiency Eff of motor _SDCAC Heater efficiency Eff _PTC And motor air compressor efficiency Eff _BDCAC I.e. Eff _Eac ＝Eff _Ac ×Eff _DCDC ×Eff _SDCAC ×Eff _PTC ×Eff _BDCAC 。

Then, after determining the energy consumption amount required by the vehicle on the candidate driving route, the power domain controller may allocate the total power consumption to fuel replenishment and charging/replacement according to a certain proportion according to energy replenishment information such as a gas station, a replacement station, a charging station and the like on the candidate driving route, and finally calculate the total energy consumption cost (i.e., energy consumption cost) of the candidate driving route.

S304: and determining the route running cost of the vehicle on one candidate running route based on the energy consumption cost and the road running cost corresponding to the one candidate running route.

For example, in executing step S304, the power domain controller may determine the road running cost required by the vehicle to run on the candidate running route based on the route length of the candidate running route, so as to determine the route running cost required by the vehicle on the candidate running route based on the obtained energy consumption cost and road running cost, that is, the sum of the energy consumption cost and the road running cost, where the calculation formula of the route running cost is specifically as follows:

S _Y ＝S _N +S _L

wherein S is _Y Indicating the cost of the vehicle to travel on the route, S _N Representing the energy consumption cost of the vehicle, S _L Representing the road travel cost of the vehicle.

Further, after obtaining the route running cost required by the vehicle for each of the at least one candidate running route based on the above method steps, the power domain controller may determine the running cost ranking of each of the at least one candidate running route based on the route running cost required by the vehicle for each of the at least one candidate running route, so as to screen out a target running route satisfying the running cost condition from the at least one candidate running route based on each obtained running cost ranking.

For example, referring to fig. 6, which is a schematic diagram of a specific application scenario for screening target driving routes provided by an embodiment of the present application, after obtaining route driving costs (1025, 981, 1127, unit: yuan) respectively required by at least one candidate driving route (for example, cda.dr.route1, cda.dr.route2, and cda.dr.route 3), the power domain controller may obtain a driving cost ranking order corresponding to each of the at least one candidate driving route based on the at least one route driving cost (1025, 981, 1127), sequentially: 2. 3, 1; next, based on the obtained at least one running cost ranking (i.e., 2, 3, 1), a target running route satisfying a preset running cost condition dri.cost.condition, i.e., a candidate running route cda.dr.route2 having the lowest running cost ranking, is screened out from at least one candidate running route (i.e., cda.dr.route1, cda.dr.route2, and cda.dr.route 3) as the target running route.

Optionally, when the power domain controller screens out a target driving route from the at least one candidate driving route, factors such as driving time and driving cost can be comprehensively considered; in addition, the power domain controller can also return the number of the target running route and the route running cost to the navigation APP, and the navigation APP displays the number on the vehicle-mounted machine interface.

S204: and when the driving request is received, driving the vehicle to run on the target running route according to the driving mode carried by the driving request.

Alternatively, in step S204, after determining the target driving route satisfying the route driving cost condition, the power domain controller may drive on the target driving route based on the driving mode carried by the driving request sent by the target terminal.

For example, the driving mode (also called as driving mode) can be divided into the following 3 cases:

case 1: a cost first mode.

If the driving mode of the vehicle is the cost priority mode, determining the pure electric driving range of the vehicle based on the residual energy storage capacity of the battery of the vehicle and the actual road condition of the target driving road section; further, when the pure electric endurance mileage is determined and the power change station does not exist, the range extender of the vehicle is triggered, and power generation is performed according to the power generation requirement of the power change station outside the pure electric endurance mileage, so that the vehicle runs on the target running route.

In one possible implementation, referring to fig. 7, the power domain controller may drive the vehicle to travel on the target travel route in the cost-priority mode according to the following:

s701: and carrying out path planning and calculation of the power generation amount demand according to the running mode setting and the high-definition map.

S702: and calculating the current pure electric remaining endurance mileage of the vehicle according to the current remaining available electric quantity of the vehicle and the real-time path condition.

S703: and searching available power change stations in the pure electric endurance mileage boundary along the way and pushing the available power change stations to the driver.

S704: in the running process, the vehicle runs purely electrically without sending the enabling and power requirements of the range extender.

S705: and in the operation process, whether the pure electric endurance mileage supports reaching the recommended battery replacement station or not is detected in a closed loop manner in real time.

S706: and if the pure electric endurance mileage is less than the power station swapping distance, the step S707 is executed, and if not, the step S705 is executed.

S707: and if no other available power change stations exist in the pure electric endurance mileage, the process goes to S708, if not, the process goes to S709, and the process further goes to S705.

S708: and calculating the generated energy requirement reaching the nearest battery replacement station, and sending the generated power requirement of the range extender to the whole vehicle power control module.

S709: and recommending other available power change stations within the remaining pure electric endurance mileage.

S710: and controlling a generator controller GCU and an engine, generating power according to the power generation power demand, and feeding back the working state in real time.

S711: and monitoring the working state and power of the range extender fed back by the whole vehicle power control module in real time, calculating the generated energy of the current required working condition, and transferring the obtained result to S705.

Case 2: time-first mode.

If the driving mode of the vehicle is the time priority mode, determining the pure electric driving mileage of the vehicle based on the available driving time of the vehicle and the actual road condition of the target driving road section; further, when the pure electric endurance mileage is determined to meet the preset first pure electric endurance mileage condition, the range extender is triggered to generate electricity according to the electricity generation requirement reaching the electricity conversion station, and therefore the vehicle can run on the target running route.

In a possible implementation manner, assuming that the preset first pure electric mileage condition is that the pure electric mileage is less than the distance from the vehicle to the power change station with the preset distance condition, referring to fig. 8, the power domain controller may drive the vehicle to run on the target driving route in the time-first mode according to the following manner:

s801: and carrying out path planning and calculation of the power generation amount demand according to the running mode setting and the high-definition map.

S802: and calculating the driving range of the current driving working condition according to the current available driving time and the real-time path condition of the vehicle.

S803: and searching available power change stations in the feasible driving range boundary along the way and pushing the available power change stations to the driver.

S804: and in the operation process, whether the pure electric endurance mileage supports reaching the recommended battery replacement station or not is detected in a closed loop manner in real time.

S805: and if not, turning to S804, and if so, turning to S806.

S806: and calculating the generated energy requirement reaching the recommended battery replacement station, and sending the power generation requirement of the range extender to the vehicle power control module.

S807: and controlling the GCU and the engine, generating power according to the power generation power demand, and feeding back the working state in real time.

S808: and monitoring the working state and power of the range extender fed back by the whole vehicle power control module in real time, calculating the generated energy of the current required working condition, and transferring the obtained result to S803.

Case 3: and (5) self-defining a mode.

If the driving mode of the vehicle is the user-defined mode, when the pure electric endurance mileage is determined to meet the preset second pure electric endurance mileage condition, the range extender is triggered to generate electricity according to the electricity generation requirement of the driving destination, so that the vehicle runs on the target driving route.

In a possible implementation manner, assuming that the preset second pure electric mileage continuation condition is that the pure electric mileage continuation is smaller than the distance between the vehicle and the driving destination, referring to fig. 9, the power domain controller may drive the vehicle to run on the target running route in the customized mode according to the following manner:

s901: and carrying out path planning and calculation of the power generation amount demand according to the running mode setting and the high-definition map.

S902: and calculating the distance to the destination according to the power exchange station or the destination selected by the user.

S903: and in the operation process, whether the pure electric endurance mileage supports the arrival at the destination or not is detected in a closed loop manner in real time.

S904: and if the pure electric endurance mileage is less than the destination driving distance, the step is shifted to S905, and if not, the step is shifted to S903.

S905: and calculating the power generation amount demand of the destination, and sending the power generation demand of the range extender to the vehicle power control module.

S906: and controlling the GCU and the engine, generating power according to the power generation requirement and feeding back the working state in real time.

S907: and monitoring the working state and power of the range extender fed back by the whole vehicle power control module in real time, calculating the generated energy of the current required working condition, and transferring the obtained result to S903.

Optionally, the power domain controller closes the range extender of the vehicle if the vehicle is currently located in a crowded road section in the target running route in the process of driving the vehicle on the target running route according to the running mode carried by the vehicle according to the running request; if the vehicle is currently in a smooth road section in the target driving route, starting the range extender to enable the range extender to generate power according to preset power generation and supply conditions; if an ascending road section meeting the preset ascending road section condition exists in the set distance range in front of the vehicle and the battery discharge power of the vehicle does not meet the requirement of the whole vehicle, starting the range extender to enable the range extender to generate power according to the preset power generation condition; and if the downhill road section meeting the preset downhill road section condition exists in the set distance range in front of the vehicle, and the residual energy storage capacity of the battery of the vehicle is not more than the total energy recovery amount of the downhill road section, closing the range extender.

Therefore, based on the start-stop control of the range extender, not only Noise, vibration and Harshness (NVH), namely smoothness, of the vehicle are considered, but also the generated power is provided for the driving consumption of the vehicle to a certain extent so as to achieve energy-saving control and reduce energy conversion loss; in addition, when the map prompts that the road ahead has a large uphill and the battery discharge power does not meet the requirement of the whole vehicle, the range extender is started in advance to finish the warming working condition of the engine, and then the power generation assistance is carried out according to the optimal power generation power point of the range extender; meanwhile, when a long downhill slope is detected in the front, whether all energy recovery can be carried out under the total energy recovery energy Of the long downhill slope and the current battery State Of Charge (SOC) is predicted, if not, the range extender is closed in advance to carry out pure electric driving, the energy recovery requirement Of the long downhill slope is guaranteed, and the risks that energy consumption loss Of the whole vehicle is caused due to the fact that no energy recovery exists when a long downhill slope is lifted and a long-time working overheating Of mechanical parts Of a braking system is caused are avoided.

Based on the above method steps, referring to fig. 10, which is a specific application scenario diagram of the predictive performance management method provided in the embodiment of the present application, the power domain controller obtains a current position cur.location of the vehicle and a target position tar.location of the driving destination; then, screening at least one candidate driving route (such as cda.dr.route1, cda.dr.route2 and cda.dr.route 3) including the current position cur.location and the target position tar.location from a preset candidate driving route set can.tra.path.set; further, based on the road condition information (in sequence: traffic. Inforr 1, traffic. Inforr 2 and traffic. Inforr 3) of each candidate driving route, determining the driving cost (in sequence: route. Tra. Cost1, route. Tra. Cost2 and route. Tra. Cost3) of the vehicle on each candidate driving route, and screening out a target driving route, such as Cda. Dr. Route2, which meets the preset route driving cost condition route.Tra. Cost. Cond, from the candidate driving routes; finally, when the driving request dri.request sent by the target terminal is received, the vehicle is driven to run on the target running route cda.dr.route2 according to the driving mode (for example, time priority mode) carried by the driving request dri.request.

In summary, in the predictive performance management method provided in the embodiment of the present application, the current position of the vehicle and the target position of the driving destination are obtained; then, screening out at least one candidate driving route comprising the current position and the target position from a preset candidate driving route set; further, determining the route driving cost required by the vehicle on each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the at least one candidate driving route; and finally, when the driving request is received, driving the vehicle to run on the target running route according to the running mode carried by the driving request.

Further, based on the same technical concept, the embodiment of the present application further provides a predictive energy management device, which is configured to implement the flow of the predictive energy management method of the embodiment of the present application. Referring to fig. 11, the predictive energy management apparatus includes: a response module 1101, a screening module 1102, a determination module 1103, and an actuation module 1104, wherein:

a response module 1101 for acquiring a current position of the vehicle and a target position of a driving destination;

the screening module 1102 is configured to screen out at least one candidate driving route including a current position and a target position from a preset candidate driving route set;

a determining module 1103, configured to determine, based on road condition information of each of the at least one candidate driving route, a route driving cost required by the vehicle on each of the at least one candidate driving route, and screen out, from the at least one candidate driving route, a target driving route that meets a preset route driving cost condition;

and the driving module 1104 is configured to drive the vehicle to run on the target running route according to the running mode carried by the running request when the running request is received.

In a possible embodiment, when determining, in step three, a route driving cost required by the vehicle for each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, the determining module 1103 is specifically configured to:

In a possible embodiment, when determining the sub-energy consumption amount required by the vehicle on each candidate driving section respectively based on the section features respectively contained in the obtained section information, the determining module 1103 is specifically configured to:

for each link information, the following operations are respectively performed:

In a possible embodiment, when the target driving route meeting the preset route driving cost condition is screened out from at least one candidate driving route in step three, the determining module 1103 is specifically configured to:

In a possible embodiment, in step four, when the vehicle is driven to travel on the target travel route according to the travel mode carried by the travel request, the driving module 1104 is specifically configured to:

In a possible embodiment, in the driving mode carried by the vehicle according to the driving request, during the driving on the target driving route, the driving module 1104 is further configured to:

if the downhill road section meeting the preset downhill road section condition exists in the set distance range in front of the vehicle, and the residual energy storage capacity of the battery of the vehicle is not larger than the total energy recovery amount of the downhill road section, the range extender is closed.

Based on the same technical concept, the embodiment of the present application further provides an electronic device, and the electronic device can implement the flow of the predictive performance management method provided by the above embodiment of the present application. In one embodiment, the electronic device may be a server, a terminal device, or other electronic device. As shown in fig. 12, the electronic device may include:

at least one processor 1201 and a memory 1202 connected to the at least one processor 1201, in this embodiment, a specific connection medium between the processor 1201 and the memory 1202 is not limited, and fig. 12 illustrates an example in which the processor 1201 and the memory 1202 are connected by a bus 1200. The bus 1200 is shown by a thick line in fig. 12, and the connection manner between other components is merely illustrative and not limited thereto. The bus 1200 may be divided into an address bus, a data bus, a control bus, etc., and is shown in fig. 12 with only one thick line for ease of illustration, but does not represent only one bus or type of bus. Alternatively, the processor 1201 may also be referred to as a controller, without limitation to name a few.

In the embodiment of the present application, the memory 1202 stores instructions executable by the at least one processor 1201, and the at least one processor 1201 can execute the instructions stored in the memory 1202 to perform a predictive performance management method as discussed above. The processor 1201 may implement the functions of the respective modules in the apparatus shown in fig. 11.

The processor 1201 is a control center of the apparatus, and may connect various parts of the entire control device by using various interfaces and lines, and perform various functions and process data of the apparatus by operating or executing instructions stored in the memory 1202 and calling data stored in the memory 1202, thereby performing overall monitoring of the apparatus.

In one possible design, the processor 1201 may include one or more processing units, and the processor 1201 may integrate an application processor, which primarily handles operating systems, user interfaces, application programs, and the like, and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 1201. In some embodiments, the processor 1201 and the memory 1202 may be implemented on the same chip, or in some embodiments, they may be implemented separately on separate chips.

The processor 1201 may be a general-purpose processor, such as a CPU, digital signal processor, application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like, that may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present application. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of a method for predicting performance management disclosed in embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

Memory 1202, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The Memory 1202 may include at least one type of storage medium, and may include, for example, a flash Memory, a hard disk, a multimedia card, a card-type Memory, a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Programmable Read Only Memory (PROM), a Read Only Memory (ROM), a charged Erasable Programmable Read Only Memory (EEPROM), a magnetic Memory, a magnetic disk, an optical disk, and the like. The memory 1202 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 1202 in the embodiments of the subject application may also be circuitry or any other device capable of performing a memory function for storing program instructions and/or data.

The processor 1201 is programmed to solidify the code corresponding to the predictive performance amount management method described in the foregoing embodiment into the chip, so that the chip can execute the steps of the predictive performance amount management method of the embodiment shown in fig. 2 when running. How the processor 1201 is programmed is well known to those skilled in the art and will not be described in detail herein.

Based on the same inventive concept, the present application also provides a storage medium storing computer instructions, which when executed on a computer, cause the computer to execute a predictive performance management method as discussed above.

In some possible embodiments, the present application provides that the various aspects of a predictive energy management method may also be implemented in the form of a program product comprising program code for causing a control apparatus to perform the steps of a predictive energy management method according to various exemplary embodiments of the present application described above in this specification, when the program product is run on a device.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.

Claims

1. A method for predictive performance management, comprising:

screening out at least one candidate driving route comprising the current position and the target position from a preset candidate driving route set;

step three, determining the route driving cost required by the vehicle on each candidate driving route based on the road condition information of each candidate driving route, and screening out a target driving route meeting the preset route driving cost condition from the candidate driving routes;

and fourthly, when a driving request is received, driving the vehicle to drive on the target driving route according to the driving mode carried by the driving request.

2. The method according to claim 1, wherein the determining the route driving cost required by the vehicle for each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route in the third step comprises:

for the at least one candidate driving route, respectively performing the following operations:

obtaining the road section information of each candidate driving road section contained in one candidate driving route from the road condition information of the candidate driving route;

determining energy consumption cost required by the vehicle on the candidate driving route based on the obtained sub-energy consumption amount and the energy replenishment information of the candidate driving route;

and determining the route running cost of the vehicle on the candidate running route based on the energy consumption cost and the road running cost corresponding to the candidate running route.

3. The method according to claim 2, wherein the determining sub-energy consumption amounts required by the vehicle on the candidate travel sections based on the section features included in the obtained section information respectively comprises:

for each piece of road section information, respectively executing the following operations:

determining the driving power and the driving time of the vehicle on the candidate driving road section based on the characteristic interval to which the road section characteristic belongs;

and determining the sub-energy consumption amount required by the vehicle on the candidate driving section based on the driving power and the driving time.

4. The method of claim 1, wherein the step three of screening out a target driving route from the at least one candidate driving route, which satisfies a predetermined route driving cost condition, comprises:

determining a running cost ranking order of each of the at least one candidate running route based on a route running cost required for each of the at least one candidate running route by the vehicle;

and screening out a target driving route meeting the driving cost condition from the at least one candidate driving route based on the obtained arrangement sequence of the driving costs.

5. The method according to any one of claims 1 to 4, wherein the step four of driving the vehicle to travel on the target travel route according to the travel pattern carried by the travel request comprises:

if the driving mode is the cost priority mode, determining the pure electric endurance mileage of the vehicle based on the battery residual energy storage capacity of the vehicle and the actual road condition of the target driving road section;

and when the pure electric endurance mileage is determined and the power change station does not exist, triggering a range extender of the vehicle, and generating power according to the power generation requirement of the power change station outside the pure electric endurance mileage so as to enable the vehicle to run on the target running route.

6. The method according to any one of claims 1 to 4, wherein the step four of driving the vehicle on the target driving route according to the driving mode carried by the driving request comprises:

if the driving mode is the time priority mode, determining the pure electric driving mileage of the vehicle based on the available driving time of the vehicle and the actual road condition of the target driving road section;

and when the pure electric endurance mileage is determined to meet a preset first pure electric endurance mileage condition, triggering the range extender to generate power according to a power generation requirement reaching the power conversion station, so that the vehicle runs on the target running route.

7. The method according to any one of claims 1 to 4, wherein the step four of driving the vehicle on the target driving route according to the driving mode carried by the driving request comprises:

if the driving mode is the user-defined mode, when the pure electric endurance mileage is determined to meet a preset second pure electric endurance mileage condition, the range extender is triggered to generate power according to the power generation requirement of the driving destination, and therefore the vehicle can drive on the target driving route.

8. The method according to any one of claims 1-4, wherein the driving the vehicle to travel on the target travel route according to the travel pattern carried by the travel request further comprises:

if the vehicle is currently located in the crowded road section in the target driving route, closing a range extender of the vehicle;

if the vehicle is currently in a smooth road section in the target driving route, starting the range extender;

if an uphill road section meeting preset uphill road section conditions exists in the set distance range in front of the vehicle and the battery discharge power of the vehicle does not meet the requirements of the whole vehicle, starting the range extender;

9. A predictive performance management apparatus, comprising:

the screening module is used for screening out at least one candidate driving route comprising the current position and the target position from a preset candidate driving route set;

the determining module is used for determining route driving cost required by the vehicle on the at least one candidate driving route based on the road condition information of the at least one candidate driving route, and screening out a target driving route meeting a preset route driving cost condition from the at least one candidate driving route;

10. The apparatus according to claim 9, wherein, when determining the route driving cost required for the vehicle to travel on each of the at least one candidate driving route based on the road condition information of each of the at least one candidate driving route, the determining module is specifically configured to:

11. The apparatus according to claim 10, wherein when the sub-energy consumption amounts required by the vehicle for the respective candidate travel segments are respectively determined based on the segment features included in the obtained respective segment information, the determining module is specifically configured to:

12. The apparatus according to claim 9, wherein, in said screening out a target driving route satisfying a preset route driving cost condition from the at least one candidate driving route, the determining module is specifically configured to:

13. The apparatus according to any one of claims 9 to 12, wherein when the vehicle is driven on the target driving route according to the driving mode carried by the driving request, the driving module is specifically configured to:

14. The apparatus according to any one of claims 9 to 12, wherein, when the vehicle is driven on the target driving route according to the driving mode carried by the driving request, the driving module is specifically configured to:

15. The apparatus according to any one of claims 9 to 12, wherein, when the vehicle is driven on the target driving route according to the driving mode carried by the driving request, the driving module is specifically configured to:

if the driving mode is the user-defined mode, when the pure electric mileage is determined to meet a preset second pure electric mileage condition, the range extender is triggered to generate power according to the power generation requirement of the driving destination, so that the vehicle runs on the target driving route.

16. The apparatus according to any one of claims 9-12, wherein during the driving of the vehicle on the target driving route according to the driving mode carried by the driving request, the driving module is further configured to:

if the vehicle is currently located in a smooth road section in the target driving route, starting the range extender;

17. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-8 when executing the computer program.

18. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.