WO2024103702A1 - Procédé et appareil de gestion prédictive d'énergie, dispositif électronique et support de stockage - Google Patents

Procédé et appareil de gestion prédictive d'énergie, dispositif électronique et support de stockage Download PDF

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Publication number
WO2024103702A1
WO2024103702A1 PCT/CN2023/100145 CN2023100145W WO2024103702A1 WO 2024103702 A1 WO2024103702 A1 WO 2024103702A1 CN 2023100145 W CN2023100145 W CN 2023100145W WO 2024103702 A1 WO2024103702 A1 WO 2024103702A1
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driving
vehicle
route
candidate
section
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PCT/CN2023/100145
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English (en)
Chinese (zh)
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刘小钦
孙昊
解明超
刘畅
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浙江吉利控股集团有限公司
浙江吉利远程新能源商用车集团有限公司
浙江远程商用车研发有限公司
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Publication of WO2024103702A1 publication Critical patent/WO2024103702A1/fr

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    • 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
    • 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
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/10—Path keeping
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply

Definitions

  • the present disclosure relates to the technical field of energy management strategies, and in particular to a predictive energy management method, device, electronic device and storage medium.
  • the slope information of the road information sampling point in front of the vehicle is obtained and matched with the road section to determine the slope value of each road section in front of the vehicle; then, the road sections are merged according to the road section slope values, the road in front of the vehicle is divided into sections with different road shapes, and the road slopes corresponding to the different sections are determined; further, according to the road section division and the road slopes corresponding to the sections, a dynamic programming algorithm is used to determine the speed limit that makes the vehicle The planned vehicle speed trajectory with the least energy consumption of the power components; finally, according to the planned vehicle speed trajectory and the future road shape changes in front of the vehicle, the rolling optimization algorithm is used to determine the energy distribution rules of the hybrid power components.
  • the above energy management strategy uses a rolling optimization algorithm to determine the energy distribution rules of the hybrid power components only based on the planned vehicle speed trajectory and the future road shape changes in front of the vehicle. This may result in a situation where the corresponding driving needs cannot be met. For example, in the case of driving with the lowest route driving cost, the driving destination cannot be reached within the set time range, thereby failing to meet the corresponding driving needs.
  • the embodiments of the present disclosure provide a predictive energy management method, device, electronic device and storage medium to meet various types of driving needs.
  • an embodiment of the present disclosure provides a predictive energy management method, the method comprising:
  • Step 1 Obtain the current position of the vehicle and the target position of the driving destination;
  • Step 2 Filter out at least one candidate driving route that includes the current location and the target location from a preset set of candidate driving routes;
  • Step 3 determining the route travel cost required for the vehicle on each of the at least one candidate travel route based on the road condition information of each of the at least one candidate travel route, and selecting a target travel route that meets a preset route travel cost condition from the at least one candidate travel route;
  • Step 4 When a driving request is received, the vehicle is driven to travel on the target driving route according to the driving mode carried in the driving request.
  • an embodiment of the present disclosure further provides a predictive energy management device, the device comprising:
  • a response module used to obtain the current position of the vehicle and the target position of the driving destination
  • a screening module used to screen out at least one candidate driving route including the current position and the target position from a preset set of candidate driving routes
  • a determination module configured to determine the route travel cost required for the vehicle on each of the at least one candidate travel route based on the road condition information of each of the at least one candidate travel route, and to select a target travel route that meets a preset route travel cost condition from the at least one candidate travel route;
  • the driving module is used to drive the vehicle to travel on the target driving route according to the driving mode carried in the driving request when a driving request is received.
  • the determination module when determining the route travel cost required for the vehicle on each of the at least one candidate driving routes based on the road condition information of each of the at least one candidate driving routes in step three, is specifically used to:
  • For at least one candidate driving route perform the following operations:
  • the sub-energy consumption required for the vehicle on each candidate driving section is determined respectively;
  • a route driving cost of the vehicle on the candidate driving route is determined.
  • the determination module when determining the sub-energy consumption required for the vehicle on each candidate driving section based on the section characteristics respectively included in each of the obtained section information, the determination module is specifically used to:
  • the driving power and driving time of the vehicle on the candidate driving section are determined;
  • the sub-energy consumption required for the vehicle on the candidate driving section is determined.
  • step 3 at least one candidate driving route is selected.
  • the determination module is specifically used to:
  • a target driving route that meets the energy consumption condition is screened out from at least one candidate driving route.
  • the driving module when the vehicle is driven to drive on the target driving route according to the driving mode carried in the driving request in step 4, the driving module is specifically used to:
  • the vehicle's pure electric range is determined based on the vehicle's remaining battery energy storage capacity and the actual road conditions of the target driving section;
  • the vehicle's range extender is triggered to generate electricity according to the power generation demand of reaching a battery swap station outside the pure electric range, so that the vehicle can travel on the target driving route.
  • the driving module when the vehicle is driven to drive on the target driving route according to the driving mode carried in the driving request in step 4, the driving module is specifically used to:
  • the vehicle's pure electric range is determined based on the vehicle's available driving time and the actual road conditions of the target driving section;
  • the range extender is triggered to generate electricity according to the power generation demand when arriving at the battery swap station, so that the vehicle can travel on the target driving route.
  • the driving module when the vehicle is driven to drive on the target driving route according to the driving mode carried in the driving request in step 4, the driving module is specifically used to:
  • the driving mode is the custom mode
  • the range extender is triggered to generate electricity according to the power generation demand to reach the driving destination, so that the vehicle can travel on the target driving route.
  • the driving module in the process of driving the vehicle to travel on the target driving route according to the driving mode carried by the driving request, is further used to:
  • the vehicle's range extender is turned off
  • the range extender is turned on
  • the range extender is turned on
  • the range extender is turned off.
  • an electronic device comprising a processor and a memory, wherein the memory stores program code, and when the program code is executed by the processor, the processor executes the steps of the predictive energy management method described in the first aspect above.
  • a computer-readable storage medium which includes a program code.
  • the program code When the program code is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the predictive energy management method described in the first aspect.
  • a computer program product is provided.
  • the computer program product is called by a computer, the computer executes the steps of the predictive energy management method as described in the first aspect.
  • the current position of the vehicle and the target position of the driving destination are obtained; then, at least one candidate driving route including the current position and the target position is screened out from a preset set of candidate driving routes; further, based on the road condition information of each of the at least one candidate driving routes, the route driving cost required for the vehicle on each of the at least one candidate driving routes is determined, and a target driving route that meets the preset route driving cost condition is screened out from at least one candidate driving route; finally, when a driving request is received, the vehicle is driven to travel on the target driving route according to the driving mode carried by the driving request.
  • a target driving route that meets the preset route driving cost conditions is screened out from at least one candidate driving route, and when a driving request is received, the vehicle is driven to travel on the target driving route according to the driving mode carried in the driving request, thereby avoiding the technical drawbacks of the prior art that the energy distribution rules of the hybrid power components are determined by the rolling optimization algorithm only based on the planned vehicle speed trajectory and the future road shape changes in front of the vehicle, which may result in situations where the corresponding driving needs cannot be met. Therefore, it is used to meet various types of driving needs.
  • FIG1 exemplarily shows a schematic diagram of an optional application scenario provided by an embodiment of the present disclosure
  • FIG2 exemplarily shows a method flow diagram of a predictive energy management method provided by an embodiment of the present disclosure
  • FIG3 exemplarily shows a flow chart of a method for determining a route travel cost provided by an embodiment of the present disclosure
  • FIG4 exemplarily shows a schematic diagram of a specific application scenario of a road segment division provided by an embodiment of the present disclosure
  • FIG5 exemplarily shows a logic diagram of determining the sub-energy consumption required for a candidate driving section provided by an embodiment of the present disclosure
  • FIG6 exemplarily shows a schematic diagram of a specific application scenario of screening a target driving route provided by an embodiment of the present disclosure
  • FIG7 exemplarily shows a flow chart of a method for a vehicle to travel on a target driving route in a cost priority mode provided by an embodiment of the present disclosure
  • FIG8 exemplarily shows a flow chart of a method for a vehicle to travel on a target driving route in a time priority mode provided by an embodiment of the present disclosure
  • FIG9 exemplarily shows a flow chart of a method for a vehicle to travel on a target driving route in a custom mode provided by an embodiment of the present disclosure
  • FIG. 10 exemplarily shows a specific application scenario based on FIG. 2 provided by an embodiment of the present disclosure. intention
  • FIG11 exemplarily shows a schematic structural diagram of a predictive energy management device provided by an embodiment of the present disclosure
  • FIG. 12 exemplarily shows a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure.
  • predictive energy management is a solution to the optimal energy management problem of long-distance trunk heavy-duty trucks, especially new energy extended-range battery-swap heavy-duty trucks. It is used to meet users' core needs for vehicle battery swapping and charging, solve pain points such as mileage anxiety, and provide drivers with innovative solutions with the best overall cost.
  • the application scenario includes: a charging and swapping energy station information platform 101, a navigation platform 102, a large vehicle screen 103, a map service platform 104, a global energy management navigation application (Application, APP) 105, and a power domain controller 106.
  • the global energy management navigation APP 105 can receive data or information from the charging and swapping energy station information platform 101, the navigation platform 102, the large vehicle screen 103, the map service platform 104 and the power domain controller 106.
  • the global energy management navigation APP105 is in the vehicle computer and can obtain corresponding energy station information, real-time traffic information and remote maps through various application programming interfaces (Application Programming Interface, API); in addition, the predictive global energy management algorithm software is deployed in the power domain controller 106.
  • API Application Programming Interface
  • the global energy management navigation APP 105 After the driver inputs the destination through the in-vehicle large screen 103, the global energy management navigation APP 105 generates several planned driving routes according to the current location of the vehicle and the location of the destination, and sends the 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 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 vehicle cost corresponding to each route to the global energy management navigation APP105. The driver chooses a route after comprehensively considering factors such as driving time and cost. Finally, the global energy management navigation APP105 sends the route information selected by the driver to the predictive global energy management algorithm module in the power domain controller 106 for subsequent global energy prediction and other related operations.
  • FIG. 2 is a flowchart of a method implementation of a predictive energy management method provided by an embodiment of the present disclosure.
  • the execution subject takes a power domain controller as an example.
  • the specific implementation process of the method is as follows:
  • S201 Acquire the current position of the vehicle and the target position of the driving destination.
  • the power domain controller can obtain the target location of the driving destination through the driving destination input through the on-board large screen, and obtain the current location of the vehicle through the navigation map over-the-air (OTA) technology in the map service platform.
  • OTA navigation map over-the-air
  • S202 Filter out at least one candidate driving route including the current position and the target position from a preset set of candidate driving routes.
  • the power domain controller when executing step S202, after obtaining the current position of the vehicle and the target position of the driving destination, the power domain controller can filter out at least one candidate driving route that includes the current position and the target position from the preset candidate driving route set based on the obtained current position and target position. It should be noted that the preset candidate driving route set includes all candidate routes available for vehicle driving within the set area.
  • the power domain controller may generate several planned driving routes with the current position of the vehicle as the starting point and the target position of the driving destination as the end point, thereby screening out at least one candidate driving route from a preset set of candidate driving routes that satisfies preset route similarity conditions with the generated several planned driving routes.
  • S203 Determine the route driving cost required for the vehicle on each of the at least one candidate driving routes based on the road condition information of each of the at least one candidate driving routes, and select a target driving route that meets a preset route driving cost condition from the at least one candidate driving route.
  • the power domain controller can determine the route driving cost required for 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. For the at least one candidate driving route, referring to FIG. 3, the following steps are respectively performed:
  • S301 Obtaining the road section information of each candidate driving section included in the candidate driving route from the road condition information of the candidate driving route.
  • the power domain controller may divide the obtained candidate driving route into sections according to a predetermined section division threshold, and obtain corresponding candidate driving sections; further, the section information of each candidate driving section may be determined based on the path information of the above candidate driving route obtained from the navigation platform.
  • the obtained candidate driving routes can be segmented every 5-30 meters (i.e., the segment division threshold) to obtain corresponding candidate driving segments, so as to obtain the segment information of each candidate driving segment based on the path information of the candidate driving routes, such as slope, curvature, planned vehicle speed, traffic information and other data information.
  • the power domain controller when executing step S302, after determining the section information of each candidate driving section, the power domain controller can determine the sub-energy consumption required for the vehicle in each candidate driving section based on the section characteristics contained in each section information, the characteristic interval to which each belongs, and the conversion method between the characteristic interval and the sub-energy consumption.
  • Pn the driving power required for the nth candidate driving section
  • Tn the driving time required for the nth candidate driving section
  • Fn driving Fn resistance + Fn acceleration + Fn slope
  • Fnresistance represents the sliding resistance of the nth candidate driving section
  • Fnacceleration represents the acceleration resistance of the nth candidate driving section
  • Fnslope represents the slope resistance of the nth candidate driving section.
  • Vn represents the average speed of the vehicle on the nth candidate driving section
  • a, b and c are the vehicle's sliding resistance coefficients
  • ⁇ represents the vehicle's rotational mass conversion coefficient, which is related to the flywheel, wheel rotational inertia and transmission ratio
  • m represents the mass of the vehicle
  • g represents the acceleration of gravity
  • ⁇ represents the slope value of the nth candidate driving section.
  • the vehicle rotation mass conversion coefficient ⁇ of each type of vehicle will be based on The mass of the vehicle varies. For example, taking a truck as an example, the empirical value of the vehicle rotation mass conversion coefficient ⁇ varies with the mass as shown in Table 1:
  • S303 Based on the obtained energy consumption of each sub-energy and the energy supply information of a candidate driving route, determine the energy consumption cost required for the vehicle on a candidate driving route.
  • the power domain controller when executing step S303, after respectively determining the sub-energy consumption required for the vehicle in each candidate driving section, the power domain controller can determine the energy consumption required for the vehicle in a candidate driving route based on a preset energy consumption calculation formula and the obtained sub-energy consumptions, wherein the energy consumption calculation formula is specifically as follows:
  • Q represents the energy consumption required for the candidate driving route
  • Eff Tol represents the total efficiency of the vehicle system
  • Q n represents the sub-energy consumption required for the nth candidate driving section in the candidate driving route
  • m represents that the candidate driving route is divided into m candidate driving sections.
  • Eff Mot represents the motor efficiency of the vehicle
  • Eff Re represents the range extender efficiency of the vehicle
  • Eff Bat represents the battery efficiency of the vehicle
  • Eff Pt represents the transmission efficiency of the vehicle
  • Eff Eac represents the electric accessory efficiency of the vehicle. It should be noted that the calculation methods of the motor efficiency Eff Mot , the range extender efficiency Eff Re , the battery efficiency Eff Bat , the transmission efficiency Eff Pt and the electric accessory efficiency Eff Eac are as follows:
  • Motor efficiency Eff Mot calculated by interpolation of the motor system efficiency and the motor universal characteristic efficiency MAP diagram;
  • Range extender efficiency Eff Re obtained based on the range extender system universal characteristic efficiency MAP diagram
  • the power domain controller can allocate the total power consumption to fuel replenishment, charging/battery replacement according to a certain proportion based on the energy supply information of gas stations, battery swap stations, charging stations, etc. on the above-mentioned candidate driving routes, and finally calculate the total energy consumption cost (i.e. energy consumption cost) of the above-mentioned candidate driving routes.
  • S304 Determine a route driving cost of the vehicle on a candidate driving route based on the energy consumption cost and the road driving cost corresponding to the candidate driving route.
  • the power domain controller may determine the road driving cost required for the vehicle to travel on the candidate driving route based on the route length of the candidate driving route, and thereby determine the route driving cost required for the vehicle on the candidate driving route based on the obtained energy consumption cost and road driving cost, that is, the sum of the energy consumption cost and the road driving cost.
  • S Y represents the route driving cost of the vehicle
  • S N represents the energy consumption cost of the vehicle
  • S L represents the road driving cost of the vehicle.
  • the power domain controller After the power domain controller obtains the route driving cost required for the vehicle on each of the above-mentioned at least one candidate driving routes based on the above-mentioned method steps, it can determine the driving cost arrangement order of each of the above-mentioned at least one candidate driving routes based on the route driving cost required for the vehicle on each of the above-mentioned at least one candidate driving routes, thereby screening out a target driving route that meets the driving cost conditions from the above-mentioned at least one candidate driving route based on the obtained arrangement order of each driving cost.
  • FIG. 6 is a schematic diagram of a specific application scenario for screening target driving routes provided by an embodiment of the present disclosure
  • the power domain controller can obtain the driving cost ranking order corresponding to each of the at least one candidate driving routes based on the at least one route driving cost (i.e., 1025, 981, 1127), which is in order: 2, 3, 1; then, based on the obtained at least one driving cost ranking order (i.e., 2, 3, 1), from at least one candidate driving route (i.e., Cda.Dr.Route1, Cda.Dr.Route2, and Cda.Dr.Route3), screen out the target driving route that meets the preset driving cost condition Dri.Cost
  • the power domain controller may comprehensively consider factors such as driving time and driving cost when screening out the target driving route from at least one candidate driving route; in addition, the power domain controller may also return the target driving route number and route driving cost to the navigation APP, which will be displayed on the vehicle interface by the navigation APP.
  • the power domain controller can drive on the target driving route based on the driving mode carried by the driving request sent by the target terminal.
  • the driving mode (also referred to as the driving mode) can be divided into the following three situations:
  • Scenario 1 Cost priority mode.
  • the vehicle's pure electric range is determined based on the vehicle's battery's remaining energy storage capacity and the actual road conditions of the target driving section; further, when it is determined that there is no battery swap station within the pure electric range, the vehicle's range extender is triggered to generate electricity according to the power generation demand of reaching a battery swap station outside the pure electric range, so that the vehicle can travel on the target driving route.
  • the power domain controller may drive the vehicle to travel on the target driving route in a cost priority mode according to the following method:
  • S701 Calculate the route planning and power generation demand according to the driving mode setting and the high-definition map.
  • S702 Calculate the vehicle's current remaining pure electric range based on the vehicle's current remaining available power and real-time route status.
  • S703 Search for available battery swap stations within the pure electric range along the route and push them to the driver.
  • S705 During operation, a real-time closed-loop detection is performed to determine whether the pure electric range supports reaching the recommended battery swap station.
  • S706 Pure electric range ⁇ distance to battery swap station. If so, proceed to S707; if not, proceed to S705.
  • S707 Is there any other available battery swap station within the pure electric range? If so, proceed to S708; if not, proceed to S709 and further to S705.
  • S708 Calculate the power generation requirement to reach the nearest battery swap station, and send the range extender power generation requirement to the vehicle power control module.
  • S710 Controls the generator controller GCU and the engine to generate electricity according to the power demand and provide real-time feedback on the working status.
  • S711 monitor the working status and power of the range extender fed back by the vehicle power control module in real time, calculate the power generation under the current demand condition, and transfer the obtained results to S705.
  • the vehicle's pure electric range is determined based on the vehicle's available driving time and the actual road conditions of the target driving section; further, when it is determined that the pure electric range meets the preset first pure electric range condition, the range extender is triggered to generate electricity according to the power generation demand to arrive at the battery swap station, so that the vehicle can travel on the target driving route.
  • the power domain controller may drive the vehicle to travel on the target driving route in the time priority mode according to the following method:
  • S801 Calculate the route planning and power generation demand according to the driving mode setting and the high-definition map.
  • S802 Calculate the drivable mileage of the current driving condition based on the current available driving time of the vehicle and the real-time status of the route.
  • S803 Search for available battery swap stations within the drivable mileage limit along the route and push them to the driver.
  • S804 During operation, a real-time closed-loop detection is performed to determine whether the pure electric range supports reaching the recommended battery swap station.
  • S806 Calculate the power generation demand to reach the recommended battery swap station, and send the range extender power generation demand to the vehicle power control module.
  • S807 Control the GCU and the engine to generate electricity according to the power demand and provide real-time feedback on the working status.
  • S808 Monitor the working status and power of the range extender fed back by the vehicle power control module in real time, calculate the power generation under the current demand condition, and transfer the obtained results to S803.
  • the range extender is triggered to generate electricity according to the power generation demand to reach the driving destination, so that the vehicle can travel on the target driving route.
  • the power domain controller may drive the vehicle to travel on the target driving route in a custom mode according to the following method:
  • S901 Calculate the route and power generation requirements based on the driving mode settings and high-definition maps.
  • S902 Calculate the distance to the destination based on the battery swap station or destination selected by the user.
  • S903 During operation, a real-time closed-loop detection is performed to determine whether the pure electric range supports reaching the destination.
  • S904 Pure electric range ⁇ distance to destination. If so, proceed to S905; if not, proceed to S903.
  • S905 Calculate the power generation demand to reach the destination and send the extended range information to the vehicle power control module The power generation demand of the device.
  • S906 Control the GCU and the engine to generate electricity according to the power generation demand and provide real-time feedback on the working status.
  • S907 Monitor the working status and power of the range extender fed back by the vehicle power control module in real time, calculate the power generation under the current demand conditions, and transfer the obtained results to S903.
  • the vehicle's range extender when the power domain controller drives the vehicle to travel on the target driving route in accordance with the driving mode carried by the driving request, if the vehicle is currently in a congested section of the target driving route, the vehicle's range extender is turned off; if the vehicle is currently in a smooth section of the target driving route, the range extender is turned on to enable the range extender to generate electricity according to preset power generation and power supply conditions; if there is an uphill section that meets the preset uphill section conditions within the set distance range in front of the vehicle, and the battery discharge power of the vehicle does not meet the vehicle's requirements, the range extender is turned on to enable the range extender to generate electricity according to the preset power generation power conditions; if there is a downhill section that meets the preset downhill section conditions within the set distance range in front of the vehicle, and the remaining energy storage capacity of the vehicle's battery is not greater than the total energy recovery of the downhill section, the range extender is turned off.
  • the start-stop control based on the above-mentioned range extender not only takes into account the vehicle's noise, vibration and sound roughness (NVH), that is, smoothness, but also, to a certain extent, provides the generated electricity to the vehicle for driving consumption to achieve energy-saving control and reduce energy conversion loss; in addition, when the map prompts that there is a large uphill road ahead and the battery discharge power does not meet the needs of the whole vehicle, the range extender is started in advance to complete the engine warm-up condition, and then power generation assistance is performed according to the optimal power generation point of the range extender; at the same time, when a long downhill slope is detected ahead, it is predicted whether the total energy recovered from the long downhill slope ahead and the current battery state of charge (SOC) can be fully recovered.
  • NSH vehicle's noise, vibration and sound roughness
  • the range extender is turned off in advance for pure electric driving to ensure the energy recovery demand for the long downhill slope, avoid energy loss of the whole vehicle due to no energy recovery when going up and down long slopes, and the risk of component failure caused by overheating of mechanical components of the braking system due to long-term operation.
  • the power domain controller obtains the current location Cur.Location of the vehicle and the target location Tar.Location of the driving destination; then, from the preset candidate driving route set Can.Tra.Path.Set, a route containing the current location Cur.Location and the target location Tar.Location is selected.
  • At least one candidate driving route at location Tar.Location for example, Cda.Dr.Route1, Cda.Dr.Route2 and Cda.Dr.Route3; further, based on the traffic condition information of at least one candidate driving route (in order: Traffic.Infor1, Traffic.Infor2 and Traffic.Infor3), determine the route travel cost required for the vehicle on at least one candidate driving route (in order: Route.Tra.Cost1, Route.Tra.Cost2 and Route.Tra.Cost3), and screen out a target driving route that meets the preset route travel cost condition Route.Tra.Cost.Cond from at least one candidate driving route, such as Cda.Dr.Route2; finally, when a driving request Dri.Request sent by the target terminal is received, drive the vehicle to travel on the target driving route Cda.Dr.Route2 according to the driving mode (for example, time priority mode) carried by the driving request Dri.Request.
  • the driving mode for example, time priority mode
  • the current position of the vehicle and the target position of the driving destination are obtained; then, at least one candidate driving route including the current position and the target position is screened out from a preset set of candidate driving routes; further, based on the road condition information of each of the at least one candidate driving routes, the route driving cost required for the vehicle on each of the at least one candidate driving routes is determined, and a target driving route that meets the preset route driving cost condition is screened out from at least one candidate driving route; finally, when a driving request is received, the vehicle is driven to travel on the target driving route according to the driving mode carried by the driving request.
  • a target driving route that meets the preset route driving cost conditions is screened out from at least one candidate driving route, and when a driving request is received, the vehicle is driven to travel on the target driving route according to the driving mode carried in the driving request, thereby avoiding the technical drawbacks of the prior art that the energy distribution rules of the hybrid power components are determined by the rolling optimization algorithm only based on the planned vehicle speed trajectory and the future road shape changes in front of the vehicle, which may result in the situation where the corresponding driving needs cannot be met. Therefore, it is used to meet various types of driving needs.
  • the embodiment of the present disclosure also provides a predictive energy management device, which is used to implement the above-mentioned predictive energy management method process of the embodiment of the present disclosure.
  • the predictive energy management device includes: a response module 1101, a screening module 1102, a determination module 1103 and a driving module 1104, wherein:
  • a response module 1101 is used to obtain the current position of the vehicle and the target position of the driving destination;
  • a screening module 1102 is used to screen out at least one candidate driving route including a current location and a target location from a preset set of candidate driving routes;
  • the determination module 1103 is used to determine the route travel cost required for the vehicle on each of the at least one candidate travel route based on the road condition information of each of the at least one candidate travel route, and select a target travel route that meets a preset route travel cost condition from the at least one candidate travel route;
  • the driving module 1104 is used to drive the vehicle to travel on the target driving route according to the driving mode carried in the driving request when a driving request is received.
  • the determination module 1103 when determining the route travel cost required for the vehicle on each of the at least one candidate travel route based on the road condition information of each of the at least one candidate travel route in step three, is specifically used to:
  • For at least one candidate driving route perform the following operations:
  • the sub-energy consumption required for the vehicle on each candidate driving section is determined respectively;
  • a route driving cost of the vehicle on the candidate driving route is determined.
  • the determination module 1103 when determining the sub-energy consumption required for the vehicle on each candidate driving section based on the section characteristics respectively included in each of the obtained section information, the determination module 1103 is specifically used to:
  • the driving power and driving time of the vehicle on the candidate driving section are determined;
  • the determining module 1103 is specifically configured to:
  • a target driving route that meets the energy consumption condition is screened out from at least one candidate driving route.
  • the driving module 1104 when the vehicle is driven to drive on the target driving route according to the driving mode carried in the driving request in step 4, the driving module 1104 is specifically used to:
  • the vehicle's pure electric range is determined based on the vehicle's remaining battery energy storage capacity and the actual road conditions of the target driving section;
  • the vehicle's range extender is triggered to generate electricity according to the power generation demand of reaching a battery swap station outside the pure electric range, so that the vehicle can travel on the target driving route.
  • the driving module when the vehicle is driven to drive on the target driving route according to the driving mode carried in the driving request in step 4, the driving module is specifically used to:
  • the vehicle's pure electric range is determined based on the vehicle's available driving time and the actual road conditions of the target driving section;
  • the range extender is triggered to generate electricity according to the power generation demand when arriving at the battery swap station, so that the vehicle can travel on the target driving route.
  • the driving module when the vehicle is driven to drive on the target driving route according to the driving mode carried in the driving request in step 4, the driving module is specifically used to:
  • the driving mode is the custom mode
  • the range extender is triggered to generate electricity according to the power generation demand to reach the driving destination, so that the vehicle can travel on the target driving route.
  • the driving module 1104 when driving the vehicle according to the driving mode carried by the driving request, During the driving process on the target driving route, the driving module 1104 is further used to:
  • the vehicle's range extender is turned off
  • the range extender is turned on
  • the range extender is turned on
  • the range extender is turned off.
  • the embodiment of the present disclosure also provides an electronic device, which can implement the predictive energy management method process provided by the above embodiment of the present disclosure.
  • the electronic device can be a server, or a terminal device or other electronic device. As shown in FIG. 12, the electronic device may include:
  • FIG. 12 takes the connection between the processor 1201 and the memory 1202 via the bus 1200 as an example.
  • the bus 1200 is represented by a bold line in FIG. 12, and the connection between other components is only for schematic illustration and is not intended to be limiting.
  • the bus 1200 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one bold line is used in FIG. 12, but it does not mean that there is only one bus or one type of bus.
  • the processor 1201 can also be called a controller, and there is no restriction on the name.
  • the memory 1202 stores instructions that can be executed by at least one processor 1201.
  • the at least one processor 1201 can execute a predictive energy management method discussed above by executing the instructions stored in the memory 1202.
  • the processor 1201 can implement the functions of each module in the device shown in FIG11.
  • the processor 1201 is the control center of the device, and can use various interfaces and lines to connect the various parts of the entire control device.
  • the processor 1201 By running or executing instructions stored in the memory 1202 and calling the data stored in the memory 1202, the various functions of the device and process data, the device can be monitored as a whole.
  • the processor 1201 may include one or more processing units. 1201 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor 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, and in some embodiments, they may also be implemented separately on separate chips.
  • the processor 1201 may be a general-purpose processor, such as a CPU, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present disclosure.
  • a general-purpose processor may be a microprocessor or any conventional processor, etc.
  • the steps of a predictive energy management method disclosed in conjunction with the embodiments of the present disclosure may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.
  • the memory 1202 is a non-volatile computer-readable storage medium that can 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, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmable Read Only Memory, PROM), a read-only memory (Read Only Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, and the like.
  • a flash memory such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static
  • the memory 1202 is any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto.
  • the memory 1202 in the embodiment of the present disclosure may also be a circuit or any other device that can realize a storage function, and is used to store program instructions and/or data.
  • the code corresponding to a predictive energy management method introduced in the above embodiment can be fixed into the chip, so that the chip can execute the steps of a predictive energy management method of the embodiment shown in Figure 2 when running.
  • How to design and program the processor 1201 is a technology known to those skilled in the art and will not be described here.
  • the present disclosure also provides a storage medium.
  • Computer instructions are stored, and when the computer instructions are executed on a computer, the computer is caused to execute a predictive energy management method discussed above.
  • various aspects of a predictive energy management method provided by the present disclosure may also be implemented in the form of a program product, which includes program code.
  • the program product When the program product is run on an apparatus, the program code is used to enable the control device to execute the steps of a predictive energy management method according to various exemplary embodiments of the present disclosure described above in this specification.
  • the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, compact disk read only memory (CD-ROM), optical storage, etc.) containing computer-usable program code.
  • CD-ROM compact disk read only memory
  • optical storage etc.
  • 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.

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Abstract

L'invention concerne un procédé et un appareil de gestion prédictive d'énergie, un dispositif électronique et un support de stockage, se rapportant au domaine technique des stratégies de gestion de l'énergie. Le procédé consiste à : acquérir l'emplacement actuel d'un véhicule et un emplacement cible d'une destination de conduite ; à partir d'un ensemble d'itinéraires de déplacement candidats prédéfini, rechercher par criblage au moins un itinéraire de déplacement candidat contenant l'emplacement actuel et l'emplacement cible ; sur la base d'informations de condition de route respectives du ou des itinéraires de déplacement candidats, déterminer des coûts de déplacement sur itinéraire requis par le véhicule sur le ou les itinéraires de déplacement candidats et, à partir du ou des itinéraires de déplacement candidats, rechercher par criblage un itinéraire de déplacement cible satisfaisant à une condition de coût de déplacement sur itinéraire prédéfinie ; et, lorsqu'une demande de déplacement est reçue, amener le véhicule à se déplacer sur l'itinéraire de déplacement cible conformément à un mode de déplacement proposé par la demande de déplacement. Grâce à ce procédé, diverses exigences de déplacement peuvent être satisfaites.
PCT/CN2023/100145 2022-11-14 2023-06-14 Procédé et appareil de gestion prédictive d'énergie, dispositif électronique et support de stockage WO2024103702A1 (fr)

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CN118144764A (zh) * 2024-03-29 2024-06-07 重庆赛力斯凤凰智创科技有限公司 增程器控制方法、装置、设备及介质

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