An ultra-long endurance mode path quadratic programming method and system and an electric vehicle

Abstract

The application provides an ultra-long endurance mode path quadratic programming method and system and an electric vehicle, and the method is as follows: after the vehicle enters the ultra-long endurance mode, the comfort function of the vehicle is closed, the minimum energy consumption driving path from the current position to the target position is found, and the minimum energy consumption path is taken as the driving path from the current position to the target position. When the endurance mileage of the vehicle is low, according to the insufficient endurance mileage, the ultra-long endurance mode is selected to be started, and in the ultra-long endurance mode, the driving path with the minimum energy consumption between the current position and the terminal position or the charging station is selected, so that the user's trouble for the endurance mileage of the vehicle is relieved as much as possible.

Description

Technical Field

[0001] This invention relates to the field of trajectory prediction technology, and provides a path quadratic planning method, system, and electric vehicle for an extreme range mode. Background Technology

[0002] With the increasing scarcity of natural resources such as oil and the continuous growth of car ownership, environmental pollution caused by vehicle exhaust emissions is becoming increasingly serious. Therefore, new energy vehicles have become a key research focus for various car manufacturers.

[0003] With the development of the power battery industry, electric vehicles have become an important development direction. They are welcomed by a wide range of users because of their advantages such as low operating costs, zero emissions, low noise, and the ability to make full use of off-peak electricity. However, due to the bottleneck of power battery energy density technology, range anxiety of electric vehicles has become the biggest concern for pure electric vehicle users.

[0004] Range anxiety is a major concern for users of pure electric vehicles. Therefore, energy-saving modes have emerged. However, current energy-saving modes on the market only increase driving range by reducing energy consumption in other ECUs, meaning range anxiety remains. Summary of the Invention

[0005] In view of this, this application provides a path quadratic planning method for the extreme range mode, which aims to improve the above-mentioned problems.

[0006] Specifically, the following technical solutions are included:

[0007] On the one hand, this application provides a method for secondary path planning in an extreme battery life mode, the method being as follows:

[0008] After the vehicle enters the ultimate range mode, turn off the vehicle's comfort functions, find the minimum energy consumption driving path from the current location to the target location, and use the minimum energy consumption path as the driving path from the current location to the target location.

[0009] In some embodiments of the present invention, the energy consumption of the driving path consists of the basic energy consumption required for the corresponding driving path, the turning energy consumption, and the gradient energy consumption.

[0010] In some embodiments of the present invention, the basic energy consumption required for the travel route is as follows:

[0011] Determine the distance Li of the driving route, and use the energy consumption required for the straight distance Li as the basic energy consumption required for the corresponding driving route.

[0012] In some embodiments of the present invention, the turning energy consumption required for the driving path is specifically as follows:

[0013] Detect the turning sections on the driving path, and the corresponding turning angles of the turning sections;

[0014] The turning energy consumption of different turning angle ranges corresponding to turning road sections is calibrated.

[0015] Determine the number of turning segments within each turning angle range on the driving path. Multiply the number of turning segments within the corresponding turning angle range by the turning energy consumption of the corresponding turning segment within that turning angle range as the turning energy consumption required for the driving path within the required turning angle range. Sum the turning energy consumption within all turning angle ranges as the turning energy consumption required for the driving path.

[0016] In some embodiments of the present invention, the method for detecting the turning angle corresponding to the turning segment on the driving path is as follows:

[0017] Based on the set sampling interval, the trajectory points of the driving path from the current position to the target position are sampled and put into the sampling point set in sequence. At the same time, the starting position and the target position are put into the starting position and the ending position of the sampling point set, respectively.

[0018] Iterate through all sampling points in the sampling point set and calculate the turning angle from the (i-1)th sampling point, through the ith sampling point, to the (i+1)th sampling point. .

[0019] In some embodiments of the present invention, the turning angle The specific calculation formula is as follows:

[0020]

[0021] in, This represents the Euclidean distance between the (i-1)th sampling point and the ith sampling point. This represents the Euclidean distance between the (i-1)th and (i+1)th sampling points. This represents the Euclidean distance between the (i+1)th sampling point and the ith sampling point, where i ranges from 2 to m-1, and m is the total number of sampling points in the sampling point set.

[0022] In some embodiments of the present invention, the sloping road segments and their gradients on the driving path are detected, and the vehicle's direction of travel is used to determine whether it is going uphill or downhill. If the vehicle is going uphill, the energy consumption required for the corresponding sloping road segment is determined. The specific calculation formula is as follows:

[0023] ;

[0024] If the vehicle is going downhill, the energy consumption required for the slope section is... The specific calculation formula is as follows:

[0025] ;

[0026] in, For the weight of the vehicle. Let be the coefficient of friction for the sloping road section. The slope of the sloping road section. This refers to the length of the sloping road section.

[0027] In some embodiments of the present invention, after triggering the ultimate range mode, it is detected whether the vehicle currently meets the entry conditions for the ultimate range mode. If the result is yes, the ultimate range mode is entered. The entry conditions for the ultimate range mode are as follows:

[0028] Condition 1: The vehicle is not currently in ADAS intelligent driving mode;

[0029] Condition 2: The current state of charge (SOC) of the power battery is lower than the set threshold;

[0030] Condition 3: The vehicle's remaining driving range is less than the remaining distance from the vehicle's current location to the destination location.

[0031] On the other hand, embodiments of this application provide a path secondary planning system for an extreme battery life mode, the system comprising:

[0032] Navigation device; Vehicle control unit (VCU) connected to the navigation device; Vehicle control unit (VCU) connected to the input unit.

[0033] The input unit is used to receive the destination location entered by the user and send it to the vehicle control unit (VCU).

[0034] The navigation device is used to locate the vehicle's current position and send it to the vehicle control unit (VCU);

[0035] After detecting that the vehicle is in the ultimate range mode, the vehicle control unit (VCU) turns off the vehicle's comfort functions and plans the driving path with the minimum energy consumption from the current position to the target position based on the path quadratic planning method in the ultimate range mode.

[0036] On the other hand, this application provides an electric vehicle that integrates the aforementioned extreme range mode path secondary planning system.

[0037] When the vehicle's range is low, this invention selects to activate the ultimate range mode based on the insufficient range. In the ultimate range mode, it selects the driving route with the least energy consumption between the current location and the destination or charging station, so as to alleviate the user's concerns about the vehicle's range as much as possible. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart of the path secondary planning method for the extreme battery life mode provided in an embodiment of the present invention;

[0040] Figure 2 A schematic diagram of the path secondary planning system in extreme battery life mode provided in an embodiment of the present invention;

[0041] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0042] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0043] Unless otherwise defined, all technical terms used in the embodiments of this application have the same meaning as commonly understood by one of ordinary skill in the art.

[0044] When the vehicle's range is low, this invention selects and activates an "Extreme Range Mode" based on the insufficient range. In Extreme Range Mode, it chooses the route with the lowest energy consumption between the current location and the destination or charging station, thus alleviating the user's concerns about the vehicle's range as much as possible. Figure 1 The flowchart below shows the path quadratic planning method for the extreme battery life mode provided in this embodiment of the invention. The method is as follows:

[0045] After the vehicle enters the ultimate range mode, the vehicle's comfort functions are turned off, and the path with the lowest energy consumption from the current location to the target location is found and used as the driving path from the current location to the target location.

[0046] In this embodiment of the invention, after triggering the ultimate range mode, it is detected whether the vehicle currently meets the entry conditions for the ultimate range mode. If the result is yes, the ultimate range mode is entered. The entry conditions for the ultimate range mode are as follows:

[0047] Condition 1: The vehicle is not currently in ADAS intelligent driving mode;

[0048] Condition 2: The current state of charge (SOC) of the power battery is lower than the set threshold (20%).

[0049] Condition 3: The vehicle's remaining driving range is less than the remaining distance from the vehicle's current location to the destination location.

[0050] After the vehicle enters the ultimate range mode, it turns off comfort functions such as actively turning off the air conditioning, seat heating, ambient lighting, DMS fatigue detection, and multimedia music, and calculates the energy consumption of each path from the current location to the target location, and outputs the path with the lowest energy consumption.

[0051] In this embodiment of the invention, when the distance from the current location to the nearest charging station is greater than or equal to the distance from the current location to the destination location, the target location is the input destination location; when the distance from the current location to the nearest charging station is less than the distance from the current location to the destination location, the target location is the charging station closest to the vehicle's current location.

[0052] In this embodiment of the invention, there may be multiple travel paths R from the current location to the target location. The energy consumption required for each travel path is estimated. The energy consumption of the travel path consists of the base energy consumption, turning energy consumption, and gradient energy consumption of the road segment between the current location and the target location. The above three energy consumptions are explained below for the travel path Ri from the current location to the target location:

[0053] (1) Basic energy consumption required for the driving route;

[0054] Determine the distance Li of the travel path Ri, and calculate the energy consumption required for the straight distance Li. That is, the product of the energy consumption of the straight section per unit distance and the distance Li is the basic energy consumption from the current position to the target position.

[0055] Since the vehicle's battery utilization is highest in the speed range of [80km / h, 100 km / h], after the vehicle enters the ultimate range mode, the vehicle speed is constrained between 80km / h and 100km / h, and the energy consumption per unit distance on a straight road within this speed range is calibrated using real vehicles.

[0056] (2) Turning energy consumption required for the driving path Ri;

[0057] Identify the turning segments on the driving path Ri and the corresponding turning angles. Calculate the turning energy consumption for turning segments corresponding to different turning angle intervals. The larger the turning angle of a turning segment, the more turning energy is required. Determine the number of turning segments within each turning angle interval. Multiply the number of turning segments within a given turning angle interval by the turning energy consumption of the corresponding turning segment within that interval as the turning energy consumption required for driving path Ri within that turning angle interval. Sum the turning energy consumption across all turning angle intervals as the total turning energy consumption required for driving path Ri.

[0058] In this embodiment of the invention, the turning angle on the turning section is... Located in the turning angle range At that time, the turning energy consumption corresponding to the turning section is The turning angle on the curve section Located in the turning angle range At that time, the turning energy consumption corresponding to the turning section is The turning angle on the curve section Located in the turning angle range At that time, the turning energy consumption corresponding to the turning section is zero, at the turning angle When, it indicates that the vehicle is making a U-turn on the corresponding road section, at the turning angle When, it indicates that the vehicle is traveling in a straight line on the corresponding road segment.

[0059] In this embodiment of the invention, the method for detecting the turning segments and the corresponding turning angles on the driving path Ri is as follows:

[0060] Based on the set sampling interval, trajectory points are sampled along the driving path Ri from the current position to the target position and sequentially added to the sampling point set. The starting position and target position are also added to the starting and ending positions of the sampling point set, respectively. All sampling points in the sampling point set are traversed, and the turning angle from the (i-1)th sampling point, passing through the ith sampling point, to the (i+1)th sampling point is calculated. Turning angle The specific calculation formula is as follows:

[0061] (1)

[0062] in, This represents the Euclidean distance between the (i-1)th sampling point and the ith sampling point. This represents the Euclidean distance between the (i-1)th and (i+1)th sampling points. This represents the Euclidean distance between the (i+1)th sampling point and the ith sampling point, where i ranges from 2 to m-1, and m is the total number of sampling points in the sampling point set.

[0063] If the driving path Ri has only three turning sections, namely two turning sections with a 120-degree turning angle and one turning section with a 180-degree turning angle, then the turning energy consumption required for the driving path Ri is 2*E+5E=9E.

[0064] (3) Energy consumption due to gradient required for the driving path Ri;

[0065] In this embodiment of the invention, the sloping road segments and their gradients on the driving path Ri are detected. Based on the vehicle's driving direction, it is determined whether the vehicle is going uphill or downhill. If the vehicle is going uphill, the gradient of the sloping road segment is used to determine whether the vehicle is going uphill or downhill. and ramp length To calculate the required slope energy consumption for the corresponding sloping road section. The specific calculation formula is as follows:

[0066] (2)

[0067] in, For the weight of the vehicle. is the friction coefficient of the slope, and is a set constant.

[0068] If the vehicle is going downhill, the gradient of the slope section will be used as a reference. and ramp length To calculate the required slope energy consumption for the corresponding sloping road section. The specific calculation formula is as follows:

[0069] (3)

[0070] This invention defines the energy consumption required for the driving path Ri as the sum of the gradient energy consumption required for all sloping road sections. The energy consumption required for the driving path Ri is the sum of the base energy consumption, the turning energy consumption, and the gradient energy consumption. By estimating the energy consumption required for each driving path, the driving path with the lowest energy consumption is selected as the optimal driving path from the current location to the target location and recommended to the user.

[0071] To maximize the vehicle's range, the energy recovery level is set to the highest level after the vehicle enters the ultimate range mode. This maximizes the energy recovery to extend the vehicle's range and ensure that the vehicle can reach the target location as far as possible.

[0072] Figure 2 This is a schematic diagram of the path quadratic planning system in extreme range mode provided by an embodiment of the present invention. For ease of explanation, only the parts related to the embodiment of the present invention are shown. The system includes:

[0073] Navigation device; Vehicle control unit (VCU) connected to the navigation device; Vehicle control unit (VCU) connected to the input unit.

[0074] The input unit receives the destination location entered by the user and sends it to the vehicle controller (VCU). The navigation device locates the vehicle's current location and sends it to the VCU. After detecting that the vehicle is in the ultimate range mode, the VCU disables the vehicle's comfort functions and plans the energy-efficient driving path from the current location to the destination location based on the path quadratic planning method in the ultimate range mode. In the ultimate range mode, the VCU selects the driving path with the lowest energy consumption between the current location and the destination location or the charging station, thereby alleviating the user's concerns about the vehicle's range as much as possible.

[0075] When the distance from the current location to the nearest charging station is greater than or equal to the distance from the current location to the destination location, the target location is the input destination location. When the distance from the current location to the nearest charging station is less than the distance from the current location to the destination location, the target location is the charging station closest to the vehicle's current location.

[0076] To maximize the vehicle's range, once the vehicle enters the ultimate range mode, the vehicle control unit (VCU) adjusts the energy recovery level to the highest level. By recovering as much energy as possible, the vehicle's range is increased, ensuring that the vehicle can reach the target location as far as possible.

[0077] The present invention also provides an electric vehicle that integrates the above-mentioned path secondary planning system in the extreme range mode. When the vehicle enters the power battery with low power and insufficient range, it can choose to activate the extreme range mode. In the extreme range mode, the vehicle selects the driving path with the least energy consumption between the current location and the destination or charging station, so as to alleviate the user's concerns about the vehicle's range as much as possible.

[0078] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only.

[0079] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A path quadratic programming method for ultra- endurance mode, characterized by, The method is as follows: After the vehicle enters the ultimate range mode, turn off the vehicle's comfort functions, find the minimum energy consumption driving path from the current location to the target location, and use the minimum energy consumption path as the driving path from the current location to the target location. The energy consumption of a driving route consists of the basic energy consumption required for the corresponding driving route, the energy consumption for turning, and the energy consumption for gradient. The specific energy consumption required for turning along the driving route is as follows: Detect the turning sections on the driving path, and the corresponding turning angles of the turning sections; The turning energy consumption of different turning angle ranges corresponding to turning road sections is calibrated. Determine the number of turning segments within each turning angle range on the driving path. Multiply the number of turning segments within the corresponding turning angle range by the turning energy consumption of the corresponding turning segment within that turning angle range as the turning energy consumption required for the driving path within the required turning angle range. Sum the turning energy consumption within all turning angle ranges as the turning energy consumption required for the driving path. The basic energy consumption required for the driving route is as follows: Determine the distance Li of the driving route, and use the energy consumption required for the straight distance Li as the basic energy consumption required for the corresponding driving route.

2. The path quadratic planning method for the extreme battery life mode as described in claim 1, characterized in that, The specific method for detecting the turning angle of the turning section on the driving path is as follows: Based on the set sampling interval, the trajectory points of the driving path from the current position to the target position are sampled and put into the sampling point set in sequence. At the same time, the starting position and the target position are put into the starting position and the ending position of the sampling point set, respectively. Iterate through all sampling points in the sampling point set and calculate the turning angle from the (i-1)th sampling point, through the ith sampling point, to the (i+1)th sampling point. .

3. The path quadratic planning method for the extreme battery life mode as described in claim 1, characterized in that, Turning angle The specific calculation formula is as follows: ； in, This represents the Euclidean distance between the (i-1)th sampling point and the ith sampling point. This represents the Euclidean distance between the (i-1)th and (i+1)th sampling points. This represents the Euclidean distance between the (i+1)th sampling point and the ith sampling point, where i ranges from 2 to m-1, and m is the total number of sampling points in the sampling point set.

4. The path quadratic planning method for the extreme battery life mode as described in claim 1, characterized in that, The system detects the sloping road sections and their gradients along the driving path. Based on the vehicle's direction of travel, it determines whether the vehicle is going uphill or downhill. If the vehicle is going uphill, it calculates the energy consumption required for the corresponding slope section. The specific calculation formula is as follows: ； If the vehicle is going downhill, the energy consumption required for the slope section is... The specific calculation formula is as follows: ； in, For the weight of the vehicle. Let be the coefficient of friction for the sloping road section. The slope of the sloping road section. This refers to the length of the sloping road section.

5. The path quadratic planning method for the extreme battery life mode as described in claim 1, characterized in that, After triggering the Ultimate Range Mode, the system checks whether the vehicle currently meets the entry conditions for Ultimate Range Mode. If the result is yes, the vehicle enters Ultimate Range Mode. The entry conditions for Ultimate Range Mode are as follows: Condition 1: The vehicle is not currently in ADAS intelligent driving mode; Condition 2: The current state of charge (SOC) of the power battery is lower than the set threshold; Condition 3: The vehicle's remaining driving range is less than the remaining distance from the vehicle's current location to the destination location.

6. A path quadratic planning system for an extreme battery life mode, characterized in that, The system includes: Navigation device; Vehicle control unit (VCU) connected to the navigation device; Vehicle control unit (VCU) connected to the input unit. The input unit is used to receive the destination location entered by the user and send it to the vehicle control unit (VCU). The navigation device is used to locate the vehicle's current position and send it to the vehicle control unit (VCU); After detecting that the vehicle is in the ultimate range mode, the vehicle controller (VCU) turns off the vehicle's comfort functions and plans the driving path with the minimum energy consumption from the current position to the target position based on the path quadratic planning method in the ultimate range mode as described in any one of claims 1 to 5.

7. An electric vehicle, characterized in that, The electric vehicle integrates a path secondary planning system for the ultimate range mode as described in claim 6.

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