Method for optimizing eCVT system energy distribution based on high-precision map

Abstract

The invention discloses a method for optimizing eCVT system energy distribution based on a high-precision map, and the method comprises the steps: S1, obtaining the high-precision map information of a subsequent route of a vehicle navigation path according to the vehicle navigation path and the vehicle position; s2, dividing the vehicle navigation path into an uphill road section, a downhill road section or a horizontal road section according to the high-precision map information; s3, predicting passing data of a plurality of road sections of the vehicle navigation path, and generating a passing data map; and S4, generating and executing an energy distribution scheme according to the passing data map. The energy distribution processing efficiency can be improved; long-term energy allocation is carried out, and switching between an active discharging mode and an efficient charging mode is achieved.

Description

Technical Field

[0001] The present invention relates to the field of eCVT, and in particular to a method for optimizing energy distribution of an eCVT system based on a high-precision map. Background Art

[0002] The energy management strategy of the eCVT hybrid system is a method that uses advanced control strategies to intelligently control and manage the engine, motor and battery based on real-time driving data, road condition information, battery status and other factors to ensure efficient operation of the system.

[0003] The main energy management strategies are:

[0004] (1) Rule-based energy management strategy

[0005] According to the torque or power requirements, torque and power are distributed according to the determined rules or fuzzy logic algorithms. This strategy has relatively small calculation amount and is easy to implement, but the torque distribution and working point adjustment mainly rely on the experience of engineers.

[0006] (2) Energy management strategy based on optimization algorithm

[0007] Such as global optimization control strategy (dynamic programming, Pontryagin minimum principle and convex optimization), instantaneous optimization control strategy (equivalent fuel consumption minimum control and model predictive control), etc. These strategies can obtain global or local optimal solutions, but require accurate subsystem models and a lot of computing power.

[0008] In the existing technical solutions, there are the following disadvantages:

[0009] First, the rule-based energy management strategy relies on the experience of engineers to reasonably allocate torque and adjust working nodes, while the energy management strategy based on the optimization algorithm has high requirements on the system model accuracy and computing power, and is difficult to apply;

[0010] Second, the various current technical solutions all have a common problem. Energy management strategies are based on information that has already occurred. The existing energy management strategies are not able to respond to possible changes in future road conditions. Especially on long uphill and downhill sections, the battery cannot manage energy properly. As a result, when the engine and motor need to work at the same time and the energy utilization efficiency needs to be optimized through torque distribution, there may be insufficient battery energy storage, resulting in a single engine working and not running at the optimal point of the external characteristics, resulting in energy loss. Moreover, the energy management of the existing solutions does not have long-term planning for a large time span. Usually, energy management is short-sighted and cannot have a significant effect over a large time span.

[0011] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgment or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art. Summary of the invention

[0012] The purpose of the present invention is to provide a method for optimizing the energy distribution of an eCVT system based on a high-precision map, comprising the steps of: S1: acquiring high-precision map information of a subsequent route of the vehicle navigation path according to a vehicle navigation path and a vehicle position; S2: dividing the vehicle navigation path into uphill sections, downhill sections or horizontal sections according to the high-precision map information; S3: predicting the passing data of multiple sections of the vehicle navigation path and generating a passing data map; S4: generating and executing an energy distribution plan according to the passing data map.

[0013] In one or more embodiments, the step S1 includes: S11: obtaining permission to read the vehicle navigation path, vehicle position and high-precision map information; S12: reading the vehicle position and dividing the vehicle navigation path; S13: retaining the path data of the subsequent route in the vehicle navigation path; S14: extracting the corresponding high-precision map information based on the geographic coordinates of the path data of the subsequent route.

[0014] In one or more embodiments, the high-precision map information includes height information and slope information of the corresponding position, and the step S2 includes: S21: dividing the focus points of the high-precision map information; S22: determining the overall slope of the interval between adjacent focus points; S23: based on the overall slope, dividing the vehicle navigation path into uphill sections, downhill sections or horizontal sections.

[0015] In one or more embodiments, the high-precision map information is an analog data type, i.e., continuous data, and the step S21 includes: S211: generating a slope change function of the high-precision map information according to the slope information; S212: traversing the slope coefficient change function to obtain the geographic coordinates corresponding to the zero point; S213: setting the focus point of the high-precision map information corresponding to the geographic coordinates corresponding to the zero point.

[0016] In one or more embodiments, the passing data includes a hybrid torque distribution scheme and a total difference between the battery SOC, and the step S3 includes: S31: acquiring vehicle attributes; S32: querying high-precision map information in the vehicle navigation path, and predicting the hybrid torque distribution scheme in combination with the vehicle attributes;

[0017] S33: According to the hybrid torque distribution scheme, the motor consumption is predicted to obtain a first battery SOC difference; S34: When the vehicle navigation path is a downhill section, the battery recovery amount is predicted to obtain a second battery SOC difference; S35: Sum the first battery SOC difference and the second battery SOC difference, and write the result into a total battery SOC difference; S36: Traverse the vehicle navigation path, correspond the total battery SOC difference to multiple sections, and obtain a passing data map.

[0018] In one or more embodiments, the vehicle attributes include external characteristics of the engine; the hybrid torque distribution scheme refers to the way in which the generator distributes torque when the engine operates in external characteristics; the step S32 includes: S321: obtaining the required torque based on the slope information; S322: obtaining the optimal torque of the engine based on the external characteristics of the engine; S323: subtracting the optimal torque of the engine from the required torque to obtain the generator torque, and further obtaining the generator power consumption rate.

[0019] In one or more embodiments, the step S33 includes: S331: integrating the generator power consumption rate within the vehicle navigation path to obtain the motor consumption.

[0020] In one or more embodiments, the step S4 includes: S41: obtaining the battery SOC initial value and the battery SOC power range; S42: according to the passing data map, traversing and calculating the battery SOC remaining value after passing through multiple focus points, and recording it as the battery SOC natural remainder; S43: comparing the battery SOC natural remainder with the battery SOC power range, and generating a battery SOC adjustment amount; S44: in the passing data map, calculating the superimposed position of the battery SOC adjustment amount in the opposite direction of the driving direction, generating an energy allocation plan and executing it.

[0021] In one or more embodiments, the step S43 includes: S431: when the natural SOC margin of the battery is higher than the peak value of the battery SOC power range, the battery SOC adjustment amount is calculated as the power that needs to be consumed in advance, and the value is a negative value; S432: when the natural SOC margin of the battery is lower than the minimum value of the battery SOC power range, the battery SOC adjustment amount is calculated as the power that needs to be charged in advance, and the value is a positive value.

[0022] In one or more embodiments, the step S44 includes: S441: searching each section in the opposite direction of the driving direction until a section to which the battery SOC adjustment amount can be adapted is found; S442: superimposing the battery SOC adjustment amount and recording the superimposed position; S443: generating an energy distribution plan based on the battery SOC adjustment amount and the superimposed position.

[0023] Compared with the prior art, the multiple technical solutions and embodiments provided by the present invention have at least the following technical effects or advantages:

[0024] By pre-dividing the road sections, we can provide indexes for subsequent large amounts of data and increase processing efficiency.

[0025] By generating the battery SOC adjustment value, long-term energy allocation can be carried out, and switching between active discharge and efficiency charging modes can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and can be considered as illustrative of various combinations of preferred embodiments and do not constitute an improper limitation on the present invention. In the drawings:

[0027] Figure 1 A schematic diagram of the overall process of a method for optimizing energy distribution of an eCVT system based on a high-precision map provided by the present invention;

[0028] Figure 2 A schematic diagram of a preferred detailed process flow of a method for optimizing energy distribution of an eCVT system based on a high-precision map provided by the present invention. DETAILED DESCRIPTION

[0029] Unless explicitly stated otherwise, throughout the specification and claims, the term "comprise" or its variations such as "include" or "comprising", "made of", etc. will be understood to include the stated elements or components but not to exclude other elements or other components.

[0030] Embodiment 1:

[0031] This embodiment provides a method for optimizing energy distribution of an eCVT system based on a high-precision map, characterized in that it includes steps S1, S2, S3, and S4:

[0032] S1: According to the vehicle navigation path and the vehicle position, high-precision map information of the subsequent route of the vehicle navigation path is obtained.

[0033] The vehicle energy optimization scheme adopted by the prior art can only be optimized according to the current road conditions, and cannot perform long-term energy regulation. Step S1 can read the vehicle navigation data, preferably obtain high-precision map information within 20 kilometers ahead, and optimize energy management according to the vehicle's scheduled itinerary. When the vehicle's destination is modified or the driving path is switched, this implementation can perform real-time updates and corrections to achieve full coverage of vehicle energy optimization. Specifically, the system obtains the Position, Stub, Segment, ProfileShort, ProfileLong, meta message sent by the map terminal T-BOX according to the Adamis V2 protocol, parses and obtains the current vehicle offset position information, obtains the slope value and its position offset, curvature value and its position offset, traffic sign speed limit and its position offset, sub-fork road offset position information in front of the vehicle, and stores them in an array for use as needed. In particular, when the vehicle is unmanned, this implementation can provide the optimal energy saving level.

[0034] As a preferred implementation of this embodiment, step S1 includes:

[0035] S11: Obtaining the permission to read the vehicle navigation path, vehicle location and high-precision map information;

[0036] S12: Read the vehicle position and divide the vehicle navigation path;

[0037] S13: retaining the path data of the subsequent route in the vehicle navigation path;

[0038] S14: Extracting the corresponding high-precision map information according to the geographic coordinates of the path data of the subsequent route.

[0039] Specifically, in steps S12 and S13, the routes to be traversed in the vehicle navigation path are screened. This embodiment can optimize energy allocation from any node of the entire vehicle navigation path. In particular, in the case of common vehicle route switching, such as switching to a route with fewer traffic lights or switching to a route with more highways, this embodiment can perform real-time updates and corrections from any breakpoint. Since high-precision map information usually has a large amount of data, after the route is updated, the system retains the data of the current route, compares the array offset according to the vehicle position, and deletes outdated array data located a certain distance behind the vehicle to release storage space. Step S14 associates the high-precision map information with the driving route to provide a more accurate location comparison.

[0040] S2: Divide the vehicle navigation path into an uphill section, a downhill section or a horizontal section according to the high-precision map information.

[0041] Specifically, the high-precision map information is an analog data type, that is, continuous data. In order to provide faster and more efficient indexing in navigation, step S2 converts the high-precision map information into digital information in the form of nodes and intervals, and divides it into uphill sections, downhill sections or horizontal sections, so as to facilitate retrieval during subsequent careful optimization of energy allocation methods.

[0042] As a preferred implementation of this embodiment, the high-precision map information includes height information and slope information of the corresponding position, and the step S2 includes:

[0043] S21: dividing the focus of high-precision map information;

[0044] S22: determining the overall slope of the interval between adjacent focus points;

[0045] S23: Based on the overall slope, divide the vehicle navigation path into an uphill section, a downhill section or a horizontal section.

[0046] As a further preferred implementation of this embodiment, step S21 includes:

[0047] S211: generating a slope change function of the high-precision map information according to the slope information;

[0048] S212: traverse the slope coefficient variation function to obtain the geographic coordinates corresponding to the zero point;

[0049] S213: Setting the focus point of the high-precision map information according to the geographic coordinates corresponding to the zero point.

[0050] Specifically, step S21 uses the slope change rate as the function dependent variable and the geographical location as the independent variable to construct the slope change function. The mathematical meaning of the zero point value is the uphill and downhill conversion, and the geographical coordinates of the zero point are used as the node (i.e., the focus point) of the interval to divide the interval into an overall uphill or downhill.

[0051] S3: Predicting the passing data of multiple sections of the vehicle navigation path and generating a passing data map.

[0052] Specifically, the passing data refers to the theoretical energy consumption value after the vehicle passes through multiple sections (i.e., the uphill section, downhill section, or horizontal section in step S2) according to the optimal solution. Step S3 records the corresponding geographic coordinates of the passing data into a map to generate a passing data map.

[0053] As a preferred implementation of this embodiment, the passing data includes the hybrid torque distribution scheme and the total difference of the battery SOC, and the step S3 includes:

[0054] S31: Obtain vehicle attributes;

[0055] S32: querying high-precision map information within the navigation path of the vehicle, and predicting the hybrid torque distribution scheme in combination with the vehicle attributes;

[0056] S33: predicting the motor consumption according to the hybrid torque distribution scheme to obtain a first battery SOC difference;

[0057] S34: when the vehicle navigation path is a downhill section, predicting the battery recovery amount to obtain a second battery SOC difference;

[0058] S35: summing the first battery SOC difference and the second battery SOC difference, and writing the result into the battery SOC total difference;

[0059] S36: traverse the vehicle navigation route, correspond the total battery SOC difference to multiple road sections, and obtain a passing data map.

[0060] Specifically, the eCVT hybrid system can make the engine work at the highest external characteristic efficiency by running the motor and distributing torque, thereby improving work efficiency and saving fuel energy. The vehicle attributes include the external characteristics of the engine. Step S3 takes into account that when the vehicle goes downhill, the vehicle can recover electrical energy to the battery as the second battery SOC difference; plus the energy consumption of the vehicle hybrid distribution motor as the first battery SOC difference, the two are summed to obtain the total battery SOC difference, that is, the change in battery charge after passing the road section. The total battery SOC difference is positive when the vehicle recovers more electrical energy, that is, there is a situation where the battery energy increases after the vehicle goes downhill.

[0061] As a further preferred implementation of this embodiment, the hybrid torque distribution scheme refers to the way in which the generator distributes torque when the engine is operating in the external characteristic;

[0062] The step S32 comprises:

[0063] S321: Obtaining required torque according to the slope information;

[0064] S322: Obtaining an optimal torque of the engine according to external characteristics of the engine;

[0065] S323: subtracting the optimal torque of the engine from the required torque to obtain the torque of the generator, and further obtain the power consumption rate of the generator;

[0066] The step S33 comprises:

[0067] S331: Integrate the generator power consumption rate within the vehicle navigation path to obtain the motor consumption.

[0068] In steps S32 and S33, the engine is adjusted to work in the external characteristic, and the motor torque is adjusted to the torque difference. The power consumption rate of the generator is obtained by looking up the table, and it is integrated within the vehicle navigation path to calculate the motor consumption.

[0069] S4: Generate and execute an energy allocation plan based on the passing data map.

[0070] As an important technical detail, the battery SOC has a power range limitation. As an example, the battery power needs to work in the range of 25% to 85% of the total capacity. The battery power cannot be overcharged, nor can it be too low. It needs to be kept within the power range to supply power normally. Therefore, this embodiment finds that when the vehicle is on a downhill section, the recovered electric energy is used to reverse charge the battery, and there is electric energy that exceeds the power range. The excess electric energy can only be discarded. This is a technical problem that cannot be solved by the prior art and will lead to energy waste. Therefore, this embodiment considers a way to increase the power consumption in advance on a relatively straight section of the road, reduce the energy consumption of the engine, and reserve excess electric energy storage capacity in advance to achieve the utilization of excess electric energy. In essence, the excess electric energy pre-compensates the fuel consumption of the engine and achieves energy optimization. On another point, the present embodiment takes into account the situation of insufficient electric energy storage in an uphill section. In the middle of the uphill section, the battery power may be lower than the minimum value of the power range, the motor cannot run to distribute the engine torque, and the engine cannot operate at the outer characteristic point, resulting in reduced efficiency and increased energy consumption. The present embodiment proposes another means of pre-charging to reserve surplus electric energy when the engine operating pressure is low.

[0071] As a preferred implementation of this embodiment, step S4 includes:

[0072] S41: Obtaining the battery SOC initial value and the battery SOC power range;

[0073] S42: traversing and calculating the battery SOC remaining value after passing through the plurality of the focus points according to the passing data map, and recording it as the battery SOC natural margin;

[0074] S43: Compare the battery SOC natural margin with the battery SOC power range to generate a battery SOC adjustment amount;

[0075] S44: In the passing data map, the superimposed position of the battery SOC adjustment amount is calculated in the opposite direction of the driving direction, and an energy distribution plan is generated and executed.

[0076] Specifically, the battery SOC adjustment amount refers to the surplus or missing electricity when the electric energy is insufficient or excess electric energy occurs. After calculating the specific battery SOC adjustment amount for the entire journey, this embodiment traverses the entire driving distance to seek a section that can supplement the battery SOC adjustment amount for pre-energy distribution.

[0077] As a further preferred implementation of this embodiment, step S43 includes:

[0078] S431: when the battery SOC natural margin is higher than the peak value of the battery SOC power range, the battery SOC adjustment amount is calculated as the power that needs to be consumed in advance, and the value is a negative value;

[0079] S432: When the natural SOC margin of the battery is lower than the minimum value of the battery SOC power range, the battery SOC adjustment amount is calculated as the power required to be charged in advance, and the value is a positive value.

[0080] As a further preferred implementation of this embodiment, step S44 includes:

[0081] S441: searching for each road section in the opposite direction of the driving direction until a road section to which the battery SOC adjustment amount can be adapted is found;

[0082] S442: superimposing the battery SOC adjustment amount and recording the superimposed position;

[0083] S443: Generate an energy allocation plan according to the battery SOC adjustment amount and the superposition position.

[0084] Specifically, after the battery SOC adjustment amount is obtained, the present application searches for a road section that can pre-distribute energy in the opposite direction of the driving direction, obtains the most suitable road section after one or more searches, and sets an energy distribution plan when passing through the road section to supplement the battery SOC adjustment amount. For example, if the power range is exceeded when recovering electric energy downhill after multiple road section changes, when passing through this straight road section, the system adjusts the hybrid motor to consume more energy and the engine to reduce energy consumption; or, the system predicts that a certain uphill section after multiple road section changes is longer and steeper, and the battery's power is not enough to support the end of the section. In this straight road section, the system controls the engine to output the maximum power to charge the battery pack. In other words, the present application can pre-store or consume energy before multiple road sections, can perform long-distance and long-time energy allocation, realize the switching of active discharge and efficiency charging modes, and is expected to save about 3% of fuel consumption based on the original vehicle fuel consumption.

[0085] Embodiment 2:

[0086] This embodiment provides an energy distribution control system. Based on the same concept, this embodiment is used to implement a method for optimizing energy distribution of an eCVT system based on a high-precision map as described in Embodiment 1. The energy distribution control system includes:

[0087] An acquisition module, used for acquiring high-precision map information of a subsequent route of the vehicle navigation path according to the vehicle navigation path and the vehicle position;

[0088] A division module, used for dividing the vehicle navigation path into an uphill section, a downhill section or a horizontal section according to the high-precision map information;

[0089] A first generating module, used for predicting the passing data of multiple sections of the vehicle navigation path and generating a passing data map;

[0090] The second generating module is used to generate and execute an energy allocation plan according to the passing data map.

[0091] The foregoing description of specific exemplary embodiments of the present invention is for the purpose of illustration and demonstration. These descriptions are not intended to limit the present invention to the precise form disclosed, and it is clear that many changes and variations can be made based on the above teachings. The purpose of selecting and describing the exemplary embodiments is to explain the specific principles of the present invention and its practical application, so that those skilled in the art can realize and utilize various different exemplary embodiments of the present invention and various different selections and changes. The scope of the present invention is intended to be limited by the claims and their equivalents.

Claims

1. A method for optimizing energy distribution of an eCVT system based on a high-precision map, characterized in that: Includes steps: S1: acquiring high-precision map information of a subsequent route of the vehicle navigation path according to the vehicle navigation path and the vehicle position; S2: dividing the vehicle navigation path into an uphill section, a downhill section or a horizontal section according to the high-precision map information; S3: predicting the passing data of multiple sections of the vehicle navigation path and generating a passing data map; S4: Generate and execute an energy allocation plan based on the passing data map.

2. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 1, characterized in that: The step S1 comprises: S11: Obtaining the permission to read the vehicle navigation path, vehicle location and high-precision map information; S12: Read the vehicle position and divide the vehicle navigation path; S13: retaining the path data of the subsequent route in the vehicle navigation path; S14: Extracting the corresponding high-precision map information according to the geographic coordinates of the path data of the subsequent route.

3. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 1, characterized in that: The high-precision map information includes height information and slope information of the corresponding position, and the step S2 includes: S21: dividing the focus of high-precision map information; S22: determining the overall slope of the interval between adjacent focus points; S23: Based on the overall slope, divide the vehicle navigation path into an uphill section, a downhill section or a horizontal section.

4. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 3, characterized in that: The step S21 comprises: S211: generating a slope change function of the high-precision map information according to the slope information; S212: traverse the slope coefficient variation function to obtain the geographic coordinates corresponding to the zero point; S213: Setting the focus point of the high-precision map information according to the geographic coordinates corresponding to the zero point.

5. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 1, characterized in that: The passing data includes the hybrid torque distribution scheme and the total difference of the battery SOC, and the step S3 includes: S31: Obtain vehicle attributes; S32: querying high-precision map information within the navigation path of the vehicle, and predicting the hybrid torque distribution scheme in combination with the vehicle attributes; S33: predicting the motor consumption according to the hybrid torque distribution scheme to obtain a first battery SOC difference; S34: when the vehicle navigation path is a downhill section, predicting the battery recovery amount to obtain a second battery SOC difference; S35: summing the first battery SOC difference and the second battery SOC difference, and writing the result into the battery SOC total difference; S36: traverse the vehicle navigation route, correspond the total battery SOC difference to multiple road sections, and obtain a passing data map.

6. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 5, characterized in that: The vehicle attributes include the external characteristics of the engine; the hybrid torque distribution scheme refers to the way in which the generator distributes torque when the engine operates in the external characteristics; The step S32 comprises: S321: Obtaining required torque according to the slope information; S322: Obtaining an optimal torque of the engine according to external characteristics of the engine; S323: Subtract the optimal torque of the engine from the required torque to obtain the generator torque, and further obtain the generator power consumption rate.

7. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 6, characterized in that: The step S33 comprises: S331: Integrate the generator power consumption rate within the vehicle navigation path to obtain the motor consumption.

8. A method for optimizing energy distribution of an eCVT system based on a high-precision map as claimed in any one of claims 6 and 7, characterized in that: The step S4 comprises: S41: Obtaining the battery SOC initial value and the battery SOC power range; S42: traversing and calculating the battery SOC remaining value after passing through the plurality of the focus points according to the passing data map, and recording it as the battery SOC natural margin; S43: Compare the battery SOC natural margin with the battery SOC power range to generate a battery SOC adjustment amount; S44: In the passing data map, the superimposed position of the battery SOC adjustment amount is calculated in the opposite direction of the driving direction, and an energy distribution plan is generated and executed.

9. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 8, characterized in that: The step S43 comprises: S431: when the battery SOC natural margin is higher than the peak value of the battery SOC power range, the battery SOC adjustment amount is calculated as the power that needs to be consumed in advance, and the value is a negative value; S432: When the natural SOC margin of the battery is lower than the minimum value of the battery SOC power range, the battery SOC adjustment amount is calculated as the power required to be charged in advance, and the value is a positive value.

10. The method for optimizing energy distribution of an eCVT system based on a high-precision map according to claim 8, characterized in that: The step S44 comprises: S441: searching for each road section in the opposite direction of the driving direction until a road section to which the battery SOC adjustment amount can be adapted is found; S442: superimposing the battery SOC adjustment amount and recording the superimposed position; S443: Generate an energy allocation plan according to the battery SOC adjustment amount and the superposition position.

Images