Intelligent gear shifting control method for new energy reduction gearbox

Abstract

The invention relates to the field of automobile manufacturing, and discloses an intelligent gear shifting control method for a new energy reduction gearbox. According to the method, driving data such as the speed, the road condition and the motor rotating speed are collected in real time through a vehicle-mounted communication module and transmitted to a management platform for analysis, and a gear shifting strategy is generated. The automatic transmission system controls the two-gear speed reducer and the drive axle to complete gear shifting according to the strategy, and meanwhile data are recorded through the OTA and gear shifting logic and an energy management strategy are optimized. After gear shifting is completed, the system verifies whether the gear is matched with the actual requirement or not, and the driving efficiency is ensured. According to the method, the vehicle-road cooperation and machine learning technology is utilized, the dynamic gear shifting decision is achieved, the dynamic property and economical efficiency of the new energy vehicle are improved, and the method is suitable for complex road conditions and load-carrying scenes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy vehicles, in particular to a new energy reduction gearbox intelligent gear shifting control method. BACKGROUND

[0002] With the rapid development of new energy vehicle technology, the optimization and innovation of electric vehicle power systems have become the focus of industry research. The gear shifting system of traditional fuel vehicles mainly relies on the physical cooperation of mechanical manual gear and clutch to realize, and this mechanical transmission method is not only cumbersome to operate, but also prone to power interruption and strong jerk during gear shifting, which seriously affects the driving smoothness and ride comfort. New energy vehicles mostly use single-gear reducer structure, however, single-gear reducer has obvious limitations in dealing with complex road conditions.

[0003] The current gear shifting control strategy of new energy vehicles still has many technical bottlenecks. The traditional control method mainly makes simple logical judgment based on limited parameters such as vehicle speed and throttle opening, and lacks comprehensive consideration of multi-dimensional dynamic information. It fails to fully integrate real-time road condition information and lacks the ability to perceive the load state of the vehicle. The existing system generally lacks the ability to learn the habits of drivers and cannot optimize the gear shifting logic according to individual needs. These problems lead to inaccurate gear shifting timing, which not only affects the driving experience, but also reduces energy utilization efficiency. The application of vehicle-road cooperation technology in existing technical solutions has not been deeply integrated into the gear shifting control strategy, so that the vehicle cannot predict changes in the road ahead; the lack of advanced algorithms such as machine learning makes it difficult for the system to optimize the gear shifting logic through continuous learning. This fixed control mode shows obvious lack of adaptability when facing diversified driving scenarios, which cannot meet the needs of different driving styles and is difficult to respond to sudden changes in road conditions.

[0004] In view of the above technical defects, an intelligent gear shifting control method is needed, which can collect and comprehensively analyze multi-dimensional data such as vehicle state, environmental parameters and driving behavior in real time, and introduce adaptive learning algorithm, so that the gear shifting strategy can be continuously optimized and upgraded. SUMMARY

[0005] The purpose of the present application is to provide a new energy reduction gearbox intelligent gear shifting control method to solve at least one of the above problems.

[0006] The present application provides a new energy reduction gearbox intelligent gear shifting control method, comprising: Step S1, cyclically judge whether the preconditions are met, if yes, go to step S2, otherwise return to step S1; Step S2, real-time collection of vehicle driving data; Step S3, analyzing the vehicle driving data to obtain an ideal gear estimation value, and selecting a corresponding real-time gear shifting strategy from preset gear shifting strategies according to the ideal gear estimation value; Step S4, executing the real-time gear shifting strategy; Step S5, verifying whether the real-time gear shifting strategy meets actual requirements after a specified time length, returning to step S2 if the verification is passed, or entering a manual mode or an advanced automatic mode if the verification is not passed.

[0007] As a further technical solution, in step S2, the vehicle driving data includes vehicle state data, environment and load data; The vehicle state data includes vehicle speed and motor speed; The environment and load data includes body fluctuation degree and load state.

[0008] As a further technical solution, in step S3, the ideal gear estimation value is obtained by:

[0009]

[0010] Among them, is the ideal gear estimation value at t, is the driving speed of the vehicle at t, is the motor speed related gear estimation value of the vehicle at t, is the load of the vehicle at t, is the theoretical critical gear shifting speed of the vehicle, is the maximum load reference value of the vehicle, is the variance of the body fluctuation degree of the vehicle in the time period is the specified time length, is the motor speed of the vehicle at t, is the instantaneous acceleration of the motor speed of the vehicle at t, is the corresponding coefficient of the vehicle speed at t, is the corresponding coefficient of the motor speed of the vehicle at t, is the corresponding coefficient of the body fluctuation degree of the vehicle at t.

[0011] As a further technical solution, step S3 includes: comparing the ideal gear estimation value with a preset gear threshold range to determine a target gear interval; if the ideal gear estimation value , it is determined that the vehicle gear should be a low gear;​ if the ideal gear estimation value then the vehicle gear should be high gear; wherein, is the gear shift threshold value.

[0012] As a further technical solution, in the step S5, the process of verifying whether the actual demand is met includes: Step S51, perform energy consumption evaluation verification, if the verification fails, go to step S52, Step S52, record the results, and ask the user to enter manual mode or enter advanced automatic mode through the vehicle-mounted HMI interface.

[0013] As a further technical solution, the energy consumption evaluation verification includes: detecting the actual power consumption consumed after the vehicle travels for the specified duration; comparing the actual power consumption with the ideal minimum power consumption under the same working condition in the energy consumption table; if the actual power consumption is less than or equal to the ideal minimum power consumption, it proves that the energy-saving effectiveness of the gear shifting strategy is effective, and the verification is passed; if the actual power consumption is greater than the ideal minimum power consumption, the verification is not passed.

[0014] As a further technical solution, the advanced automatic mode includes:

[0015]

[0016] wherein, the vehicle driving data further includes road condition coordination data, the road condition coordination data includes estimated road traffic state and driving habit score, is the driving habit score, is the corresponding coefficient of the estimated road traffic state data, is the estimated road traffic state data.

[0017] As a further technical solution, the process of obtaining the driving habit score includes:

[0018] wherein, is the initial driving full score value, is the throttle deduction value, is the brake deduction value, is the direction deduction value; the throttle deduction value The average number of times that the instantaneous change rate of the accelerator opening exceeds a preset threshold in each fixed distance in randomly selected multiple historical driving data is calculated to obtain the score of the accelerator; The brake deduction value The average number of times that the instantaneous change rate of the brake pressure exceeds a preset threshold in each fixed distance in randomly selected multiple historical driving data is calculated to obtain the score of the brake; The direction deduction value The average number of times that the steering wheel rotation speed exceeds a preset threshold in each fixed distance in randomly selected multiple historical driving data is calculated to obtain the score of the steering wheel.

[0019] As a further technical solution, if the driving total score is less than the safe driving score, the user is determined to have an aggressive driving habit, and a safety constraint mechanism is adopted at this time; The safety constraint mechanism comprises: When the motor bearing temperature is greater than or equal to an excessively high temperature threshold, an alarm is sent to the user, and the motor speed is limited; When the driving duration of the user reaches a fatigue threshold, the user is reminded, and if there is no response, the available power of the motor is gradually reduced by a fixed threshold per minute.

[0020] As a further technical solution, the precondition comprises the following conditions that need to be met at the same time: The calibration of the collection end is completed; The vehicle-mounted communication end is connected normally; The two-gear reducer needs to be in a normal standby action state; The preset gear shifting strategy is OTA updated; if the preset gear shifting strategy is not OTA updated, the OTA upgrade is performed in idle time.

[0021] In summary, the present application has the following at least one beneficial technical effect: 1. Intelligent gear shifting selects the optimal gear dynamically by analyzing real-time vehicle speed, load, road conditions and other data, reduces motor invalid power consumption, improves electric energy conversion efficiency, thereby reduces energy consumption, prolongs the endurance of new energy vehicles, accurately controls the gear shifting time based on algorithms, avoids the traditional mechanical gear shifting lag, improves the smoothness of gear shifting, realizes the gear shifting without feeling, and improves the driving comfort.

[0022] 2. Intelligent gear shifting can match the high-efficiency working interval of the motor, quickly respond to the speed change demand, improve the power transportation efficiency, reduce the wear of mechanical parts, reduce the maintenance cost, prolong the service life of the reduction gearbox, analyze the user driving habits based on machine learning, continuously update the personalized gear shifting strategy through OTA, make the gear shifting time more in line with the user's expectation, and reduce the number of invalid gear shifting.

[0023] 3. With multiple fault protection mechanism, real-time driving data can be obtained, combined with sensor data, the system can intelligently identify special working conditions such as climbing and heavy load, and improve the power response speed of the vehicle in complex road conditions. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 is a schematic diagram of the working process of the intelligent gear shifting control method of the new energy reduction gearbox. DETAILED DESCRIPTION

[0025] The embodiments of the present application will be described in detail below, and examples of the embodiments are shown in the accompanying drawings.

[0026] In the description of the present specification, the description of the terms "some embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the described embodiments or examples are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0027] Referring to Figure 1 The present application discloses an intelligent gear shifting control method for a new energy reduction gearbox, which comprises the following steps: Step S1, cyclically determine whether the preconditions are met, if yes, go to step S2, otherwise return to step S1; Step S2, real-time acquisition of vehicle driving data; Step S3, analysis of the vehicle driving data to obtain an ideal gear position estimate, and selection of a corresponding real-time gear shifting strategy from a pre-set gear shifting strategy according to the ideal gear position estimate; Step S4, execution of the real-time gear shifting strategy; Step S5, verification of whether the real-time gear shifting strategy meets the actual demand after a specified time period, if the verification is passed, return to step S2, if the verification is not passed, enter the manual mode or enter the advanced automatic mode.

[0028] In the present embodiment, the vehicle driving data in step S2 includes vehicle state data, environmental and load data; The vehicle state data includes vehicle speed and motor speed; The environmental and load data includes the degree of body fluctuation and the load state.

[0029] In the present embodiment, the ideal gear position estimate in step S3 is obtained by the following method:

[0030]

[0031] wherein, is the ideal gear estimate at time t, is the vehicle speed at time t, is the vehicle speed related gear estimate at time t, is the vehicle load at time t, is the theoretical critical shift speed of the vehicle, is the maximum load reference value of the vehicle, is the variance of the body heave of the vehicle in the time period is the specified time length, is the motor speed of the vehicle at time t, is the instantaneous acceleration of the motor speed of the vehicle at time t, is the corresponding coefficient of the vehicle speed at time t, is the corresponding coefficient of the motor speed of the vehicle at time t, is the corresponding coefficient of the body heave of the vehicle at time t; wherein, is the gear threshold range, is the non-dimensional operation, = 90 KM / h, = 0.2, = 0.1, = 0.1.

[0032] In the embodiment, the step S3 comprises: comparing the ideal gear estimate with a preset gear threshold range to determine a target gear interval; the preset gear threshold range is is the low gear range, is the high gear range;

[0033] if the ideal gear estimate , it is determined that the vehicle gear should be a low gear; if the ideal gear estimate , it is determined that the vehicle gear should be a high gear; In the embodiment, in the step S5, the process of verifying whether the actual demand is met comprises: Step S51, energy consumption evaluation verification is performed, and if the verification fails, step S52 is entered; ​Step S52, record the result, and ask the user to enter the manual mode or the advanced automatic mode through the vehicle-mounted HMI interface.

[0034] In this embodiment, the energy consumption evaluation verification includes: detecting the actual power consumption consumed by the automobile driving for the specified duration of 30 minutes; comparing the actual power consumption with the ideal minimum power consumption under the same working condition in the energy consumption table; if the actual power consumption is less than or equal to the ideal minimum power consumption, it proves that the energy-saving effectiveness of the shift strategy is effective, and the verification is passed; if the actual power consumption is greater than the ideal minimum power consumption, the verification is not passed.

[0035] In this embodiment, the advanced automatic mode includes:

[0036]

[0037] The automobile driving data further includes road condition coordination data, and the road condition coordination data includes estimated road traffic state and driving habit score, the driving habit score, a corresponding coefficient of the estimated road traffic state data, the estimated road traffic state data; The estimated road traffic state data includes:

[0038] wherein, a congestion distance of a driving road section at t time, a maximum congestion distance reference value of the driving road section, a time for a traffic signal lamp to change at t time, a corresponding coefficient of the congestion distance of the driving road section at t time, a corresponding coefficient of the time for the traffic signal lamp to change at t time; and a dimensionless operation, =0.7, =0.2, =0.1, =0.2.

[0039] In this embodiment, the driving habit score acquisition process includes:

[0040] wherein, a full score value for initial driving, a throttle deduction value, a brake deduction value, a direction deduction value; = 100; the throttle deduction value is calculated by the average number of times that the instantaneous change rate of the throttle opening exceeds a preset threshold in each fixed distance in randomly selected historical driving data, and the average number of times that the instantaneous change rate of the throttle opening exceeds the preset threshold 2 times in 100 kilometers in randomly selected three sections of historical driving data, and each time exceeding the preset threshold deducts 5 points; the brake deduction value is calculated by the average number of times that the instantaneous change rate of the brake pressure exceeds a preset threshold in each fixed distance in randomly selected historical driving data, and the average number of times that the instantaneous change rate of the brake pressure exceeds the preset threshold 3 times in 100 kilometers in randomly selected three sections of historical driving data, and each time exceeding the preset threshold deducts 6 points; the direction deduction value is calculated by the average number of times that the steering wheel rotation speed exceeds a preset threshold in each fixed distance in randomly selected historical driving data, and the average number of times that the steering wheel rotation speed exceeds the preset threshold 3 times in 100 kilometers in randomly selected three sections of historical driving data, and each time exceeding the preset threshold deducts 7 points.

[0041] In this embodiment, if the driving total score is less than 70 points of the safe driving score, it is determined that the user has an aggressive driving habit, and a safe constraint mechanism is adopted at this time; The safe constraint mechanism includes: When the motor bearing temperature is greater than or equal to an excessively high temperature threshold of 200°, an alarm is sent to the user, and the motor rotation speed is limited; When it is detected that the user driving duration reaches a fatigue threshold, the user is reminded, and the fatigue threshold can be divided into three sections: The first stage is to detect that the user driving duration reaches two hours, and the user is asked for the first time; The second stage is to detect that the user driving duration reaches three hours, and the user is asked for the second time, and the seat vibration reminder and voice prompt are turned on; The third stage is to detect that the user driving duration reaches four hours, and the user is asked for the third time, and if there is no response, the available power of the motor is gradually reduced, and the available power of the motor is reduced by 5% per minute.

[0042] In this embodiment, the precondition includes the following conditions that need to be met at the same time: The calibration of the acquisition end is completed; The vehicle-mounted communication end is normally connected; The two-gear reducer needs to be in a normal standby action state; The OTA update of the preset gear shifting strategy is completed; if the OTA update of the preset gear shifting strategy is not completed, the OTA upgrade is performed in an idle state.

[0043] Although the embodiments of the present application have been shown and described above, it should be understood by those skilled in the art that the above embodiments are exemplary and cannot be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A new energy reduction gearbox intelligent gear shifting control method, characterized in that, The method comprises the following steps: Step S1, judging whether the preconditions are met, if yes, entering step S2, otherwise returning to step S1; Step S2, collecting real-time vehicle driving data; Step S3, analyzing the vehicle driving data to obtain an ideal gear estimation value, and selecting a corresponding real-time gear shifting strategy from a preset gear shifting strategy according to the ideal gear estimation value; Step S4, executing the real-time gear shifting strategy; Step S5, verifying whether the real-time gear shifting strategy meets the actual demand after a specified time period, if yes, returning to step S2, if not, entering a manual mode or an advanced automatic mode.

2. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 1, characterized in that, In step S2, the vehicle driving data comprises vehicle state data, environment and load data; The vehicle state data comprises vehicle speed and motor speed; The environment and load data comprises body fluctuation degree and load state.

3. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 2, characterized in that, In step S3, the method for obtaining the ideal gear estimation value comprises: ； wherein, is the ideal gear estimate at time t, is the vehicle speed at time t, is the vehicle speed related gear estimate at time t, is the vehicle load at time t, is the theoretical threshold shift speed of the vehicle, is the maximum load reference value of the vehicle, is the variance of the vehicle body heave over the time period is the specified time period, is the specified time period, is the motor speed of the vehicle at time t, is the instantaneous acceleration of the motor speed of the vehicle at time t, is the corresponding coefficient of the vehicle speed at time t, is the corresponding coefficient of the motor speed of the vehicle at time t, is the corresponding coefficient of the vehicle body heave at time t.

4. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 1, characterized in that, In step S3, the method for obtaining the ideal gear estimation value comprises: estimating the ideal gear value comparing the ideal gear value with a preset gear threshold range to determine a target gear interval if the ideal gear estimate is low, then the vehicle gear is determined to be low if the ideal gear estimate then determine that the vehicle gear should be a high gear; wherein is the gear boundary value.

5. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 3, characterized in that, In step S5, the process of verifying whether the real-time gear shifting strategy meets the actual demand comprises: Step S51, performing energy consumption evaluation verification, if not, entering step S52; Step S52, recording the result and asking the user to enter the manual mode or the advanced automatic mode through the vehicle-mounted HMI interface.

6. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 5, characterized in that, The energy consumption evaluation verification comprises: detecting the actual power consumption of the vehicle after driving for the specified time period; comparing the actual power consumption with the ideal minimum power consumption under the same working condition in the energy consumption table; if the actual power consumption is less than or equal to the ideal minimum power consumption, it is proved that the energy-saving effectiveness of the gear shifting strategy is verified; if the actual power consumption is greater than the ideal minimum power consumption, the verification is not passed.

7. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 5, characterized in that, The advanced automatic mode comprises: ； ； The automobile driving data further comprises road condition coordination data, the road condition coordination data comprises estimated road traffic state and driving habit score, The driving habit score, The corresponding coefficient of the estimated road traffic state data, The estimated road traffic state data.

8. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 7, characterized in that, The process of obtaining the driving habit score comprises: ； wherein, is an initial driving full score value, is an accelerator deduction value, is a brake deduction value, is a direction deduction value; The throttle deduction value The average number of times that the instantaneous change rate of the throttle opening exceeds a preset threshold in each fixed distance in randomly extracted multi-section historical driving data is calculated to obtain. The brake deduction value The brake deduction value is calculated by the average number of times that the instantaneous change rate of brake pressure exceeds a preset threshold in each fixed distance in randomly selected multi-section historical driving data. The direction deduction value is obtained by calculating the average number of times that the steering wheel rotation speed exceeds a preset threshold in each fixed distance in randomly selected historical driving data.

9. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 6, characterized in that, If the total driving score is less than the safe driving score, it is determined that the user has an aggressive driving habit, and a safety constraint mechanism is adopted at this time; The safety constraint mechanism comprises: when the motor bearing temperature is greater than or equal to an excessively high temperature threshold, an alarm is sent to the user, and the motor speed is limited; when the driving time length reaches a fatigue threshold, the user is reminded, and if there is no response, the available power of the motor is gradually reduced by a fixed threshold per minute.

10. The intelligent gear shifting control method of a new energy reduction gearbox according to claim 1, characterized in that, The preconditions comprise the following conditions that need to be met simultaneously: the calibration of the collection end is completed; the vehicle-mounted communication end is connected normally; the two-gear reducer is in a normal standby action state; the preset gear shifting strategy is OTA updated, if the preset gear shifting strategy is not OTA updated, OTA upgrade is performed in idle time.

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