Dynamic adjustment method and system for sliding energy recovery parameters of electric vehicle

Abstract

The invention belongs to the technical field of electric vehicle control, and provides a dynamic adjustment method and system for electric vehicle sliding energy recovery parameters, and the method comprises the steps: obtaining the current vehicle state data of an electric vehicle and the road spectrum data of a target line; based on the obtained current vehicle state data and the target line road spectrum data, the type of a road section where the electric vehicle is located is positioned, and current working condition information of the vehicle is determined by combining the type of the road section where the vehicle is located; calculating a sliding energy recovery parameter of the electric vehicle according to the determined current working condition information of the vehicle; and the sliding energy recovery intensity of the vehicle is adjusted according to the obtained sliding energy recovery parameters of the electric vehicle, and dynamic adjustment of the sliding energy recovery parameters of the electric vehicle is completed.

Description

Technical Field

[0001] This invention belongs to the field of electric vehicle control technology, specifically relating to a method and system for dynamically adjusting electric vehicle coasting energy recovery parameters. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the popularization of new energy vehicles, fixed-route pure electric vehicles (such as electric buses operating in mountainous areas and short-distance freight vehicles) have become an important direction for the transformation of the transportation sector due to their zero-emission advantages. Their energy recovery efficiency directly affects the driving range and operating costs, and coasting energy recovery, as a core energy-saving method, has become a key research focus in the industry.

[0004] Currently, coasting energy recovery control in electric vehicles mainly falls into two categories: One type uses a fixed parameter mode, which presets fixed coasting energy recovery parameters (e.g., setting the coasting energy recovery negative torque to 10% of the rated torque) to maintain a constant recovery intensity throughout the journey. While the control logic is simple, it doesn't consider differences in route characteristics. For example, on fixed routes with significant altitude changes, such as in mountainous areas, downhill sections can convert more gravitational potential energy into electrical energy, leading to energy waste due to fixed low recovery parameters. The other type uses a local operating condition adaptive mode, which dynamically adjusts the coasting energy recovery parameters by collecting data such as vehicle speed and battery state of charge (SOC) in real time using onboard sensors. For example, some solutions increase the negative torque of coasting braking in economic mode to enhance the energy recovery effect; however, this type of approach has obvious shortcomings: First, the response is lagging, requiring waiting for changes in vehicle speed and other operating conditions to trigger adjustments, making it impossible to predict the altitude difference and slope changes in mountainous sections; second, it lacks a global perspective, relying solely on onboard data for adjustments, and cannot combine the stable road conditions of fixed routes for early optimization, which can easily lead to a mismatch between recovery intensity and steering requirements before sharp curves (such as the drag caused by strong recovery affecting steering smoothness); third, it requires the installation of multiple onboard sensors, resulting in high overall implementation costs.

[0005] However, existing electric vehicle coasting energy recovery control systems share a common problem: they do not combine the pre-stored road spectrum characteristics (especially altitude changes) of fixed routes with real-time vehicle conditions. The altitude, slope, and other characteristics of fixed routes (such as mountain bus routes) are stable, and the operating conditions can be predicted in advance through pre-stored road spectra. However, existing technologies do not utilize this characteristic and only rely on real-time data for passive adjustments. In addition, mountain routes have large altitude differences (some sections have an altitude difference of more than 50m per kilometer), and the impact of gravitational potential energy on energy recovery is much greater than on flat roads. Existing solutions have not been optimized specifically for this, resulting in a low energy recovery rate on downhill sections. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method and system for dynamically adjusting the coasting energy recovery parameters of electric vehicles. Based on the coordinated operation of road spectrum data, a remote monitoring platform, and the vehicle control unit, the method achieves dynamic adjustment of the vehicle's coasting energy recovery parameters, effectively avoiding the lag in dynamic adjustment of coasting energy recovery parameters caused by insufficient road condition prediction.

[0007] According to some embodiments, the first aspect of the present invention provides a method for dynamically adjusting the parameters of electric vehicle coasting energy recovery, employing the following technical solution: A method for dynamically adjusting the parameters of electric vehicle coasting energy recovery includes: Acquire current vehicle status data and target route road spectrum data for electric vehicles; Based on the acquired current vehicle status data and target route spectrum data, the type of road segment where the electric vehicle is located is determined, and the current operating condition information of the vehicle is determined in combination with the type of road segment where the vehicle is located. Calculate the coasting energy recovery parameters of the electric vehicle based on the determined current operating condition information of the vehicle; The intensity of vehicle coasting energy recovery is adjusted based on the obtained electric vehicle coasting energy recovery parameters, thus completing the dynamic adjustment of the electric vehicle coasting energy recovery parameters.

[0008] As a further technical limitation, the current vehicle status data acquired includes at least the current location information of the electric vehicle, the remaining battery power, and the real-time vehicle speed; the target route road spectrum data acquired includes at least the elevation change characteristics, gradient value, curve curvature, and speed limit information of each road segment.

[0009] As a further technical limitation, in the process of adjusting the intensity of vehicle coasting energy recovery, the intensity of coasting energy recovery is adjusted according to real-time vehicle status data, that is, the upper and lower limits of recovery intensity are corrected based on the remaining battery power, and the speed limit requirements of the road spectrum are matched based on the real-time vehicle speed.

[0010] As a further technical limitation, the road segment where the electric vehicle is located includes at least downhill, flat road, before a curve, and road segment with reduced speed limit; the determined current operating condition information of the vehicle includes at least key operating condition information such as altitude change trend, curve curvature value, and speed limit standard, and the altitude change trend includes the downhill starting point, downhill length, and slope.

[0011] As a further technical limitation, in the process of calculating the coasting energy recovery parameters of electric vehicles based on the determined current operating conditions of the vehicle, when the electric vehicle is on a downhill section, the elevation difference and slope value are used as the calculation basis. As the elevation difference and slope value increase, the base value of coasting energy recovery intensity is increased. Then, the coasting energy recovery intensity is adjusted according to the correction value of the remaining battery power of the electric vehicle to obtain the coasting energy recovery parameters of the electric vehicle.

[0012] Furthermore, the energy recovery adjustment ratio is calculated based on the road spectrum data of the downhill section, i.e. , ;in, The energy recovery adjustment ratio is calculated based on the road spectrum data of the downhill section. These are the standard energy recovery parameter values ​​for vehicles. The target values ​​for energy recovery parameters are calculated based on road spectrum data of downhill sections. The elevation difference is due to the downhill section. This represents the average gradient of the downhill section. This is the maximum value adjusted for the intensity of gliding energy recovery.

[0013] According to some embodiments, a second aspect of the present invention provides a dynamic adjustment system for electric vehicle coasting energy recovery parameters, employing the following technical solution: A dynamic adjustment system for electric vehicle coasting energy recovery parameters, comprising: The acquisition module is configured to acquire the current vehicle status data and target route road spectrum data of the electric vehicle; The positioning module is configured to locate the type of road segment where the electric vehicle is located based on the acquired current vehicle status data and target route spectrum data, and determine the current operating condition information of the vehicle by combining the type of road segment where the vehicle is located. The calculation module is configured to calculate the coasting energy recovery parameters of the electric vehicle based on the determined current operating condition information of the vehicle. The adjustment module is configured to adjust the gliding energy recovery intensity of the vehicle based on the obtained gliding energy recovery parameters of the electric vehicle, thereby completing the dynamic adjustment of the gliding energy recovery parameters of the electric vehicle.

[0014] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium, employing the following technical solution: A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the method for dynamically adjusting electric vehicle coasting energy recovery parameters as described in the first aspect of the present invention.

[0015] According to some embodiments, the fourth aspect of the present invention provides an electronic device, which adopts the following technical solution: An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps in the method for dynamically adjusting the gliding energy recovery parameters of an electric vehicle as described in the first aspect of the present invention.

[0016] According to some embodiments, the fifth aspect of the present invention provides a computer program product, which adopts the following technical solution: A computer program product includes software code, wherein the program in the software code performs the steps in the method for dynamically adjusting the parameters of electric vehicle coasting energy recovery as described in the first aspect of the present invention.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention predicts elevation changes by pre-stored road spectrum, allowing for early activation of high recovery intensity on downhill sections. Based on the coordinated operation of road spectrum data, a remote monitoring platform, and the vehicle control unit, it enables dynamic adjustment of vehicle coasting energy recovery parameters, effectively avoiding the lag in dynamic adjustment of coasting energy recovery parameters caused by insufficient road condition prediction. Attached Figure Description

[0018] The accompanying drawings, which form part of this embodiment, are used to provide a further understanding of this embodiment. The illustrative embodiments and their descriptions are used to explain this embodiment and do not constitute an improper limitation of this embodiment.

[0019] Figure 1 This is a flowchart of the dynamic adjustment method for electric vehicle coasting energy recovery parameters in Embodiment 1 of the present invention; Figure 2 This is an architecture diagram of the dynamic adjustment method for electric vehicle coasting energy recovery parameters in Embodiment 1 of the present invention; Figure 3 This is a structural block diagram of the dynamic adjustment system for electric vehicle coasting energy recovery parameters in Embodiment 2 of the present invention. Detailed Implementation

[0020] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0022] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0023] In this invention, terms such as "upper," "lower," "left," "right," "front," "back," "vertical," "horizontal," "side," and "bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used only to facilitate the description of the structural relationships of the various components or elements of this invention and do not specifically refer to any component or element in this invention. They should not be construed as limiting the invention.

[0024] In this invention, terms such as "fixed connection," "connected," and "linked" should be interpreted broadly, indicating a fixed connection, an integral connection, or a detachable connection; a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can determine the specific meaning of these terms in this invention based on the specific circumstances, and they should not be construed as limitations on the invention.

[0025] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0026] Example 1 Embodiment 1 of the present invention introduces a method for dynamically adjusting the parameters of electric vehicle coasting energy recovery.

[0027] like Figure 1 The method for dynamically adjusting the parameters of electric vehicle coasting energy recovery, as shown, includes: Acquire current vehicle status data and target route road spectrum data for electric vehicles; Based on the acquired current vehicle status data and target route spectrum data, the type of road segment where the electric vehicle is located is determined, and the current operating condition information of the vehicle is determined in combination with the type of road segment where the vehicle is located. Calculate the coasting energy recovery parameters of the electric vehicle based on the determined current operating condition information of the vehicle; The intensity of vehicle coasting energy recovery is adjusted based on the obtained electric vehicle coasting energy recovery parameters, thus completing the dynamic adjustment of the electric vehicle coasting energy recovery parameters.

[0028] The fixed-parameter mode does not take into account changes in route elevation, and cannot fully utilize gravitational potential energy recovery on downhill sections; the local adaptive mode relies on real-time vehicle conditions for passive adjustment, which lacks sufficient prediction of elevation change trends in mountainous sections and suffers from a lag in recovery intensity response. This embodiment adopts the following... Figure 2 The architecture of the dynamic adjustment method for electric vehicle coasting energy recovery parameters shown is that the dynamic adjustment of coasting energy recovery parameters is achieved through a collaborative technical architecture of "road spectrum data - remote monitoring platform - vehicle ECU".

[0029] As one or more implementation methods, the remote monitoring platform pre-stores the surveyed road spectrum data of the target fixed route, analyzes the road spectrum data using the road spectrum ID as a unique identifier, and numbers and identifies long downhill sections. The remote monitoring platform associates the road spectrum ID with the vehicles operating on that route (using VIN as the unique identifier for each vehicle). The road spectrum data includes at least the elevation change characteristics, gradient values, curve curvature, and speed limit information for each road segment. The road spectrum data is updated regularly to ensure consistency with actual road conditions, and data cleaning algorithms are used to remove abnormal elevation data caused by GPS drift, improving the accuracy of the road spectrum.

[0030] The remote monitoring platform acquires real-time vehicle location information, real-time altitude data, and battery SOC data via 4G / 5G networks (transmission latency ≤200ms). Based on the current location information, it matches it with pre-stored road spectrum data to pinpoint the altitude change trend of the road segment where the vehicle is located (e.g., downhill start point, downhill length, gradient), addressing the issue of insufficient prediction of altitude change trends in mountainous road sections by the local adaptive mode. Combining the matched road spectrum altitude characteristics (e.g., downhill elevation difference, downhill length) and the vehicle's real-time status (SOC, speed, etc.), the remote monitoring platform dynamically calculates optimal coasting energy recovery parameters using a preset algorithm. For example, it increases recovery intensity (30%-50% higher than on flat roads) on sections with decreasing altitude, and gradually reduces recovery intensity near curves or sections with reduced speed limits. After calculation, the parameters are sent to the vehicle's ECU in real time.

[0031] In this embodiment, taking a downhill section as an example, the calculation is based on the elevation difference and slope. For every 10m increase in elevation difference and every 1° increase in slope, the basic value of gliding energy recovery intensity increases by 3%-5%, with a maximum of no more than 50%. Then, it is corrected according to the battery SOC. When the SOC is below 30%, the intensity is increased by 20% on the upper limit, and when the SOC is above 90%, the intensity is decreased by 20% on the lower limit, ensuring that the recovered energy is sufficient while avoiding battery overcharging.

[0032] The energy recovery adjustment ratio is calculated based on the road spectrum data of the downhill section, i.e. , ;in, The energy recovery adjustment ratio is calculated based on the road spectrum data of the downhill section. These are the standard energy recovery parameter values ​​for vehicles. The target values ​​for energy recovery parameters are calculated based on road spectrum data of downhill sections. The elevation difference is due to the downhill section. This represents the average gradient of the downhill section. This is the maximum value adjusted for the intensity of gliding energy recovery.

[0033] In this embodiment, road spectrum data provides "operating condition prediction basis" for parameter calculation and serves as the core directional guide for parameter adjustment; specifically: (1) The characteristics of altitude change directly determine the overall trend of recovery intensity. Downhill sections have sufficient gravitational potential energy, so it is predicted that the recovery intensity needs to be increased to fully recover energy; uphill sections need to appropriately reduce the intensity to reduce the impact on vehicle power output.

[0034] (2) The slope value quantifies the scale of gravitational potential energy. The greater the slope, the more energy can be recovered, and the higher the calculated recovery intensity; conversely, the intensity is reduced.

[0035] (3) The curvature of the curve and the speed limit information determine the decay rhythm of the recovery intensity. The greater the curvature and the lower the speed limit, the earlier the recovery intensity needs to be reduced to ensure the driving safety and smoothness of the vehicle when turning or decelerating.

[0036] In this embodiment, real-time vehicle status data provides a "real-time adaptation benchmark" for parameter calculation, serving as a dynamic correction item for parameter adjustment; specifically: (1) Battery SOC correction recycling intensity upper and lower limits to prevent battery overcharging due to excessive recycling or wasting energy due to insufficient recycling, and to ensure that the parameters meet the current charging and discharging capacity of the battery.

[0037] (2) Match the real-time vehicle speed with the road spectrum speed limit requirements to avoid mismatch between the recovery intensity and the actual driving speed. For example, if the recovery intensity is too high when driving at high speed, it may cause sudden deceleration and affect the driving experience.

[0038] In this embodiment, the remote monitoring platform receives vehicle operation data and current location information transmitted from the terminal in real time. When the platform determines that the vehicle is about to reach the starting point of the downhill section, it immediately calculates the optimal coasting energy recovery parameters based on the detailed road map information of the downhill section, combined with the vehicle's current speed, SOC, etc., and generates a remote control command to send to the remote terminal. When the platform determines that the vehicle has reached the end point of the downhill section, it calculates and generates new energy recovery parameters and remotely sends them to the remote terminal.

[0039] As one or more implementation methods, the vehicle-side ECU immediately performs anomaly detection upon receiving parameters. If an anomaly is detected (such as missing instructions or parameters exceeding the safe range), the ECU refuses to execute the instruction and reports the anomaly information to the remote monitoring platform. If the parameters are normal, the ECU immediately performs parameter adjustments and reports the adjustment results back to the remote monitoring platform, forming a closed-loop control. Upon receiving instructions from the platform, the remote terminal immediately forwards them to the vehicle-side ECU. The ECU parses the instruction content and determines whether the target parameter value exceeds the normal range. If it exceeds the normal range, the ECU refuses to execute the instruction and returns an error message to the remote terminal. If the parameter is within the normal range, the ECU gradually adjusts the coasting energy recovery parameters to the target value according to the gradient change principle.

[0040] The vehicle ECU program is equipped with a dedicated program for dynamically adjusting coasting energy recovery parameters: (1) it can receive parameter adjustment instructions from remote terminals; (2) it presets the normal parameter range and can determine if the parameter exceeds the threshold; (3) it determines whether the remote terminal is disconnected through life signals; (4) it presets the default parameters, and when the remote terminal is disconnected, it dynamically and gradually adjusts to the default parameters and records the operation log and error information locally.

[0041] It should be noted that during the vehicle-side anomaly detection process, after the vehicle-side ECU receives the optimal coasting energy recovery parameter command from the remote monitoring platform, it first verifies the integrity of the command format, checking whether it includes necessary fields such as parameter type (e.g., recovery of negative torque percentage), target parameter value, command effective time, and data checksum. If any field is missing or the format is incorrect, it is initially determined to be a command anomaly. The target parameter value in the command is extracted and compared in real time with the ECU's internally preset safe range for coasting energy recovery parameters to determine whether the target value is within the safe range. If it exceeds the range, it is marked as a numerical anomaly. Upon detecting any of the above anomalies, the vehicle-side ECU immediately refuses to execute the parameter command and automatically switches to the preset safe recovery parameter mode (e.g., default recovery intensity of 10%-15% on flat roads). At the same time, an anomaly report is generated, including the anomaly type (abnormal command format, numerical out-of-bounds, logical conflict, etc.), current vehicle location, and abnormal parameter value, which is fed back to the remote monitoring platform via the 4G / 5G network to facilitate the platform's troubleshooting.

[0042] Abnormal parameter conditions in this embodiment include: (1) Value exceeds the limit: The target value of the coasting energy recovery intensity is less than the minimum value of the preset safety range (the minimum safety threshold. Below this value, the recovery effect is negligible and may cause abnormal coasting resistance of the vehicle) or greater than the maximum value of the preset safety range (the maximum safety threshold. Above this value, it is easy to cause risks such as motor overload, power battery charging overcurrent, and wheel lock-up).

[0043] (2) Missing or incorrect format of instructions: The parameter instructions are missing key fields such as data check code and effective time, or the instruction data format does not conform to the ECU's preset parsing rules (such as incorrect data bit length or encoding format mismatch), which causes the ECU to be unable to parse the parameters normally.

[0044] In this embodiment, the safety range of parameters is determined based on the hardware performance parameters of the vehicle's motor and battery. For example, the maximum allowable regenerative torque of the motor is 80% of the rated torque, corresponding to an upper limit of 80% for the regenerative intensity. The upper limit of the regenerative energy corresponding to the maximum charging current of the battery is used to deduce the safety threshold of the regenerative intensity, avoiding hardware overload damage. Combined with the synergistic effect of the vehicle's braking system, real vehicle tests have verified that excessively high regenerative intensity, when superimposed with mechanical braking, can easily lead to wheel lock-up, thus setting an upper limit for the intensity. At the same time, it is ensured that the minimum regenerative intensity can provide basic gliding resistance to prevent the vehicle from losing control due to excessive gliding speed, thus setting a lower limit for the intensity. Through multiple sets of real vehicle driving tests, driving feedback under different regenerative intensities is collected to determine the regenerative intensity range (e.g., 5%-80%) without obvious drag or sudden deceleration, which serves as the comfort and safety threshold.

[0045] When the parameters are normal, this embodiment can perform gradient adjustments. To avoid sudden parameter changes that could reduce vehicle ride smoothness, the ECU performs adjustments according to the principle of "adjustment increment ≤ 10% per second." For example, if the current recovery intensity is 20% and the target value is 50%, the ECU completes the adjustment in 3 seconds: adjusting to 30% in the first second, 40% in the second, and 50% in the third, gradually approaching the target value. During the adjustment process, the ECU collects the actual coasting energy recovery intensity every 0.5 seconds and compares it with the target value. If the deviation exceeds 5%, the adjustment rate is corrected in real time. Simultaneously, data such as the actual adjustment progress, current recovery intensity, and real-time vehicle speed are uploaded to the remote monitoring platform via 4G / 5G network, forming a "deployment-execution-feedback" closed-loop control system, facilitating real-time monitoring of the adjustment effect. The ECU fully records the entire parameter adjustment process, including parameter reception time, target value, adjustment start / end time, and real-time parameter values ​​during the adjustment process. The local storage period is no less than 30 days, facilitating subsequent fault tracing and parameter optimization analysis.

[0046] This embodiment predicts elevation changes by pre-stored road spectrum, allowing for early activation of high recovery intensity on downhill sections. Based on the coordinated operation of road spectrum data, remote monitoring platform, and vehicle control unit, dynamic adjustment of vehicle coasting energy recovery parameters is achieved, effectively avoiding the lag in dynamic adjustment of coasting energy recovery parameters caused by insufficient road condition prediction.

[0047] Example 2 Embodiment 2 of the present invention introduces a dynamic adjustment system for the gliding energy recovery parameters of an electric vehicle.

[0048] like Figure 3 The illustrated dynamic adjustment system for electric vehicle coasting energy recovery parameters includes: The acquisition module is configured to acquire the current vehicle status data and target route road spectrum data of the electric vehicle; The positioning module is configured to locate the type of road segment where the electric vehicle is located based on the acquired current vehicle status data and target route spectrum data, and determine the current operating condition information of the vehicle by combining the type of road segment where the vehicle is located. The calculation module is configured to calculate the coasting energy recovery parameters of the electric vehicle based on the determined current operating condition information of the vehicle. The adjustment module is configured to adjust the gliding energy recovery intensity of the vehicle based on the obtained gliding energy recovery parameters of the electric vehicle, thereby completing the dynamic adjustment of the gliding energy recovery parameters of the electric vehicle.

[0049] The detailed steps are the same as the dynamic adjustment method for electric vehicle coasting energy recovery parameters provided in Example 1, and will not be repeated here.

[0050] Example 3 Embodiment 3 of the present invention provides a computer-readable storage medium.

[0051] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the method for dynamically adjusting electric vehicle coasting energy recovery parameters as described in Embodiment 1 of the present invention.

[0052] The detailed steps are the same as the dynamic adjustment method for electric vehicle coasting energy recovery parameters provided in Example 1, and will not be repeated here.

[0053] Example 4 Embodiment 4 of the present invention provides an electronic device.

[0054] An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the steps in the method for dynamically adjusting the gliding energy recovery parameters of an electric vehicle as described in Embodiment 1 of the present invention.

[0055] The detailed steps are the same as the dynamic adjustment method for electric vehicle coasting energy recovery parameters provided in Example 1, and will not be repeated here.

[0056] Example 5 Embodiment 5 of the present invention provides a computer program product.

[0057] A computer program product includes software code, wherein the program in the software code performs the steps in the method for dynamically adjusting the parameters of electric vehicle coasting energy recovery as described in Embodiment 1 of the present invention.

[0058] The detailed steps are the same as the dynamic adjustment method for electric vehicle coasting energy recovery parameters provided in Example 1, and will not be repeated here.

[0059] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0060] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0061] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0062] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0063] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0064] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0065] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. A method for dynamically adjusting the parameters of electric vehicle coasting energy recovery, characterized in that, include: Acquire current vehicle status data and target route road spectrum data for electric vehicles; Based on the acquired current vehicle status data and target route spectrum data, the type of road segment where the electric vehicle is located is determined, and the current operating condition information of the vehicle is determined in combination with the type of road segment where the vehicle is located. Calculate the coasting energy recovery parameters of the electric vehicle based on the determined current operating condition information of the vehicle; The intensity of vehicle coasting energy recovery is adjusted based on the obtained electric vehicle coasting energy recovery parameters, thus completing the dynamic adjustment of the electric vehicle coasting energy recovery parameters.

2. The method for dynamically adjusting the parameters of electric vehicle coasting energy recovery as described in claim 1, characterized in that, The acquired current vehicle status data includes at least the electric vehicle's current location, remaining battery power, and real-time vehicle speed; the acquired target route road spectrum data includes at least the elevation change characteristics, gradient, curve curvature, and speed limit information for each road segment.

3. The method for dynamically adjusting the parameters of electric vehicle coasting energy recovery as described in claim 1, characterized in that, In adjusting the intensity of vehicle coasting energy recovery, the intensity of coasting energy recovery is adjusted according to real-time vehicle status data, that is, the upper and lower limits of recovery intensity are corrected based on the remaining battery power, and the speed limit requirements of the road spectrum are matched based on the real-time vehicle speed.

4. The method for dynamically adjusting the parameters of electric vehicle coasting energy recovery as described in claim 1, characterized in that, The types of road sections where the electric vehicle is located include at least downhill, flat road, before a curve, and sections with reduced speed limits; the current operating condition information of the determined vehicle includes at least key operating condition information such as altitude change trend, curve curvature value, and speed limit standard, and the altitude change trend includes the starting point of the downhill, the length of the downhill, and the gradient.

5. The method for dynamically adjusting the parameters of electric vehicle coasting energy recovery as described in claim 1, characterized in that, In the process of calculating the coasting energy recovery parameters of electric vehicles based on the determined current vehicle operating condition information, when the electric vehicle is on a downhill section, the elevation difference and slope value are used as the basis for calculation. As the elevation difference and slope value increase, the base value of coasting energy recovery intensity is increased. The coasting energy recovery intensity is then adjusted based on the correction value of the remaining battery power of the electric vehicle to obtain the coasting energy recovery parameters of the electric vehicle.

6. The method for dynamically adjusting the parameters of electric vehicle coasting energy recovery as described in claim 5, characterized in that, The energy recovery adjustment ratio is calculated based on the road spectrum data of the downhill section, i.e. , ;in, The energy recovery adjustment ratio is calculated based on the road spectrum data of the downhill section. These are the standard energy recovery parameter values ​​for vehicles. The target values ​​for energy recovery parameters are calculated based on road spectrum data of downhill sections. The elevation difference is due to the downhill section. This represents the average gradient of the downhill section. This is the maximum value adjusted for the intensity of gliding energy recovery.

7. A dynamic adjustment system for electric vehicle coasting energy recovery parameters, characterized in that, include: The acquisition module is configured to acquire the current vehicle status data and target route road spectrum data of the electric vehicle; The positioning module is configured to locate the type of road segment where the electric vehicle is located based on the acquired current vehicle status data and target route spectrum data, and determine the current operating condition information of the vehicle by combining the type of road segment where the vehicle is located. The calculation module is configured to calculate the coasting energy recovery parameters of the electric vehicle based on the determined current operating condition information of the vehicle. The adjustment module is configured to adjust the gliding energy recovery intensity of the vehicle based on the obtained gliding energy recovery parameters of the electric vehicle, thereby completing the dynamic adjustment of the gliding energy recovery parameters of the electric vehicle.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method for dynamically adjusting the electric vehicle coasting energy recovery parameters as described in any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of the method for dynamically adjusting the electric vehicle coasting energy recovery parameters as described in any one of claims 1-6.

10. A computer program product, comprising software code, characterized in that, The program in the software code executes the steps of the method for dynamically adjusting the electric vehicle coasting energy recovery parameters as described in any one of claims 1-6.

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