A method for automatic gear shifting control of off-road vehicles based on dynamic programming
By constructing an optimal gear shift map using dynamic programming algorithms, the problems of computational complexity and time consumption in multi-gear transmissions are solved, achieving efficient and practical automatic shift control and improving the power and economic performance of off-road vehicles.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TIANJIN UNIV
- Filing Date
- 2026-06-16
- Publication Date
- 2026-07-31
AI Technical Summary
Existing automatic shifting strategies are computationally complex and time-consuming, especially in multi-gear transmissions where the computational load increases exponentially. They are also highly dependent on real-world vehicle operating data and onboard chips, making it difficult to balance vehicle power and fuel economy.
A dynamic programming-based model of the powertrain system of off-road vehicles is established. By discretizing typical cyclic road spectra, an optimization objective function is constructed and solved using a dynamic programming algorithm. Finally, an optimal gear partition map is constructed, and the current optimal gear is determined in real time for gear shifting.
It reduces the complexity of shift pattern design and computation, shortens the development cycle, is applicable to multi-gear transmissions, reduces the on-board computing burden, and has strong portability and scalability, thereby improving vehicle power performance and fuel economy.
Smart Images
Figure CN122485960A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of vehicle automatic transmission control technology, and in particular to an automatic gear shifting control method for off-road vehicles based on dynamic programming. Background Technology
[0002] Off-road vehicles such as construction machinery and agricultural machinery operate in complex environments with drastic changes in external loads, resulting in a wide range of variations in their output torque and speed. To improve the fuel economy and power performance of their power systems, off-road vehicles typically feature transmissions with multiple gears, such as 16-speed automatic transmissions. Currently, traditional manual transmissions rely on the driver's experience and often struggle to maintain smooth and efficient operation. In contrast, automatic transmission systems can be preset with shift patterns and automatically complete the shifting process through an electronic control unit, flexibly adapting to complex working conditions and offering advantages such as ample power and high efficiency.
[0003] However, while the traditional three-parameter shift control strategy (using vehicle speed, throttle, and acceleration as control parameters) in existing automatic transmission strategies considers the dynamic characteristics of vehicle operation, it requires solving nonlinear polynomial equations for vehicle acceleration and fuel consumption to calculate the shift parameter interface between adjacent gears. This calculation process is complex and time-consuming, and the computational load increases exponentially with the number of transmission gears. Furthermore, while shift strategies based on intelligent algorithms such as neural networks and fuzzy control have emerged in recent years and can avoid complex nonlinear calculations, they require extensive training with real-world vehicle operating data and place high demands on the performance of onboard chips, making widespread application currently difficult.
[0004] Therefore, there is an urgent need for an automatic shift control method that is computationally simple, has low hardware requirements, is applicable to multi-gear transmissions, and can balance vehicle power and economy, while reducing computational complexity and ensuring the optimized performance of the shift strategy. Summary of the Invention
[0005] The purpose of this invention is to provide an automatic gear shifting control method for off-road vehicles based on dynamic programming, which overcomes the problems of computational complexity, long processing time, exponential increase in computational load with increasing gears, and strong dependence on real vehicle operating data and on-board chips in the existing technology. Thus, while reducing online computational complexity and hardware costs, it ensures the power performance and economic performance of the vehicle, and provides an efficient and practical automatic gear shifting control solution for multi-gear off-road vehicles.
[0006] To achieve the above objectives, the present invention provides an automatic gear shifting control method for off-road vehicles based on dynamic programming, comprising the following steps: Step S1: Establish a model of the powertrain system for non-road vehicles; Step S2: Based on the non-road vehicle powertrain system model, select typical cyclic road spectra and discretize them to construct an optimization objective function; Step S3: Use dynamic programming algorithm to solve the objective function to obtain the optimal gear partitioning diagram; Step S4: Collect the current driving conditions in real time, determine the current optimal gear by combining the optimal gear partition map, and output it to the transmission to perform the gear shifting operation.
[0007] Preferably, step S1 further includes obtaining engine characteristic parameters, transmission system parameters, and driving resistance characteristic parameters; Engine characteristic parameters include the engine's output torque data at different throttle openings and speeds, as well as fuel consumption rate data at different torques and throttle openings; transmission system parameters include the gear ratios of each gearbox, the rotational mass coefficients of each gear, the final drive ratio, and the mechanical transmission efficiency; driving resistance characteristic parameters include the vehicle's curb weight, frontal area, air resistance coefficient, tire radius, and tire rolling resistance coefficient.
[0008] Preferably, in step S2, the typical cycle route spectrum includes WTVC, WHTP and FTP Heavy-Duty; the discretization process is to discretize the total driving time after combining the typical cycle route spectrum with a time step of 1 second to obtain several typical working condition points.
[0009] Preferably, in step S2, the optimization objective function is constructed with minimizing vehicle fuel consumption as the optimization objective. The specific expression is: ; in, For the vehicle in the The gear, the first Instantaneous fuel consumption per second. This represents the total travel time.
[0010] Preferably, in step S3, when using the dynamic programming algorithm to solve the optimization objective function, the engine speed constraint and the engine torque constraint must also be satisfied. The specific expression for the engine speed constraint is: ; The specific expression for the engine torque constraint is: ; in, This is the minimum permissible engine speed. This refers to the engine output speed. This is the engine's maximum permissible speed. This represents the minimum torque output by the engine at its current speed. For engine output torque, This represents the maximum torque output by the engine at the current speed.
[0011] Preferably, in step S3, a dynamic programming algorithm is used to solve the objective function, specifically including: The process iterates through each gear at each typical operating point, calculates the instantaneous fuel consumption for each gear, and then calculates the cumulative fuel consumption through stage-by-stage recursion, thus optimizing the objective function. Solve The minimum value is used to determine the optimal gear at each moment; Extract the optimal gear under all typical operating conditions and construct an optimal gear partition map with vehicle speed, throttle opening and vehicle acceleration as inputs and the optimal gear as output.
[0012] Preferably, in step S4, the current driving conditions include the current vehicle speed, the current throttle opening, and the current vehicle acceleration.
[0013] Preferably, in step S4, determining the current optimal gear based on the optimal gear zoning map specifically includes: Calculate the distance between the current driving condition and each typical driving condition point in the optimal gear partition map. The specific expression is: ; in, Current vehicle speed For the current vehicle acceleration, The current throttle opening, For the first The current vehicle speed at a typical operating point For the first The current vehicle acceleration at a typical operating point For the first The current throttle opening at a typical operating point ; The gear corresponding to the typical operating condition point closest to the current driving condition is taken as the current optimal gear.
[0014] Therefore, the present invention employs the above-mentioned dynamic programming-based automatic gear shifting control method for off-road vehicles, and the beneficial technical effects are as follows: (1) This invention avoids the complex process of nonlinear polynomial fitting of engine characteristics in the traditional three-parameter shifting strategy. It does not require solving nonlinear polynomial equations or calculating shifting interfaces one by one, thereby reducing the design difficulty and computational complexity of shifting rules. It is especially suitable for non-road vehicles equipped with multi-gear transmissions.
[0015] (2) Based on the dynamic programming algorithm, the present invention performs global optimization under the combined working conditions of typical cyclic road spectrum (WTVC, WHTP, FTP Heavy-Duty), avoiding the repetitive calculation work of calculating the gear interface pair by pair in the traditional method, and effectively shortening the development cycle of the shifting strategy.
[0016] (3) In actual operation, the present invention only needs to calculate the distance between the current driving condition and each typical working condition point in the optimal gear partition map to determine the optimal gear, without the need to solve complex equations in real time, and will not increase the on-board computing burden.
[0017] (4) The present invention has strong portability. When changing vehicle models, only the engine characteristic data needs to be updated and the dynamic programming algorithm needs to be run again. There is no need to re-derive the shift boundary formula, which makes it easy to promote and apply it among different vehicle models.
[0018] (5) The present invention is easy to extend to multiple objectives. It can introduce shift penalty or driving style factor into the optimization objective function, and extend the shift strategy into a multi-objective optimization framework, so as to be closer to the actual driving conditions and driver needs. Attached Figure Description
[0019] Figure 1 This is a flowchart illustrating an embodiment of an automatic gear shifting control method for off-road vehicles based on dynamic programming according to the present invention; Figure 2 This is a diagram showing engine characteristic parameters of an embodiment of the automatic gear shifting control method for off-road vehicles based on dynamic programming according to the present invention. Figure 2 (a) shows the engine output torque data and fitting function graph at different throttle openings and speeds. Figure 2 (b) shows the fuel consumption rate data and fitting function graph of the engine under different torques and different throttle openings; Figure 3 This is a typical driving route map of a non-road vehicle according to an embodiment of the non-road vehicle automatic gear shifting control method based on dynamic programming of the present invention; Figure 4 This is an optimal gear partition diagram of an embodiment of the off-road vehicle automatic gear shifting control method based on dynamic programming according to the present invention; Figure 5 This is a schematic diagram of a vehicle powertrain system simulation model according to an embodiment of the off-road vehicle automatic gear shifting control method based on dynamic programming of the present invention. Figure 6 This is an embodiment of the optimal gear determination process for an off-road vehicle automatic gear shifting control method based on dynamic programming according to the present invention, wherein... Figure 6 (a) in the diagram represents the optimal gear selection process for the three-parameter economic shifting strategy. Figure 6(b) in the figure represents the optimal gear determination process of the method of the present invention; Figure 7 The following are simulation test results of the full-throttle acceleration dynamics of an embodiment of the off-road vehicle automatic gear shifting control method based on dynamic programming according to the present invention. Figure 7 (a) shows the vehicle acceleration process under two shifting strategies. Figure 7 (b) shows the gear shifting results under the two shifting strategies; Figure 8 The above are the comprehensive cyclic road spectrum simulation test results of an embodiment of the off-road vehicle automatic gear shifting control method based on dynamic programming according to the present invention, wherein, Figure 8 (a) in the figure represents the speed-following capability. Figure 8 In the figure, (b) represents the engine speed. Figure 8 (c) in the figure represents the change in fuel consumption over time. Figure 8 (d) in the text represents the gear shifting situation. Detailed Implementation
[0020] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.
[0021] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.
[0022] Example 1 like Figure 1 As shown, an automatic gear shifting control method for off-road vehicles based on dynamic programming includes the following steps: Step S1: Establish a model of the powertrain system for non-road vehicles.
[0023] This embodiment takes a non-road vehicle equipped with a 16-speed automatic transmission as the research object, and simplifies the vehicle's power transmission system into four main components: engine, transmission, final drive, and wheel ends.
[0024] Specifically, step S1 also includes acquiring engine characteristic parameters, transmission system parameters, and driving resistance characteristic parameters.
[0025] Obtain engine output torque data at different throttle openings and engine speeds, as well as fuel consumption rate data at different torques and throttle openings, i.e., engine characteristic parameters, such as... Figure 2 As shown, where, Figure 2 (a) shows the engine output torque data and fitting function graph at different throttle openings and speeds. Figure 2 (b) shows the fuel consumption rate data and fitting function graph of the engine under different torques and different throttle openings; the relationship between the data can be represented by the following fitting function: ; ; in, Engine fuel consumption rate. This refers to the engine output speed. For engine output torque, This refers to the throttle opening.
[0026] The transmission system parameters include the gear ratios of each gearbox, the rotational mass coefficients of each gear, the final drive ratio, and the mechanical transmission efficiency. Driving resistance characteristic parameters include the vehicle's curb weight, frontal area, drag coefficient, tire radius, and tire rolling resistance coefficient. Specific values are shown in Table 1.
[0027] Table 1 Vehicle Parameters
[0028] Step S2: Based on the non-road vehicle powertrain system model, select typical cyclic road spectra and discretize them to construct an optimization objective function.
[0029] Typical cycle test patterns include WTVC (World Transient Vehicle Cycle), WHTP (Worldwide Harmonized Vehicle Test Procedure), and FTPHeavy-Duty (Federal Test Procedure for Heavy-Duty Vehicles). These three test patterns are widely used typical operating conditions in the heavy-duty vehicle field and can effectively cover various operating characteristics such as acceleration, deceleration, and steady-state operation. By combining multiple cycle test patterns, the range of operating conditions can be expanded to a certain extent, thereby improving the adaptability of the constructed shifting strategy to complex operating conditions.
[0030] The total travel time after combining the three typical cyclic road patterns is discretized with a time step of 1 second to obtain multiple typical working condition points. In this embodiment, the total travel time after combining the three typical cyclic road patterns is 5400 seconds, and a total of 5400 typical working condition points are obtained after discretization. The vehicle speed at each typical working condition point changes with time as follows: Figure 3 As shown.
[0031] With minimizing vehicle fuel consumption as the optimization objective, an optimization objective function is constructed. The specific expression is: ; in, For the vehicle in the The gear, the first Instantaneous fuel consumption per second. This represents the total travel time.
[0032] It should be noted that, This is obtained by querying the engine characteristic data acquired in step S1. Under specific vehicle driving conditions, different gears correspond to different engine speeds and output torques, and their corresponding fuel consumption can be obtained by querying the engine characteristic data.
[0033] Step S3: Use dynamic programming algorithm to solve the objective function and obtain the optimal gear partitioning diagram.
[0034] When using dynamic programming to solve the objective function, engine speed constraints and engine torque constraints must also be satisfied.
[0035] The specific expression for the engine speed constraint is: .
[0036] The specific expression for the engine torque constraint is: ; in, This is the minimum permissible engine speed. This refers to the engine output speed. This is the engine's maximum permissible speed. This represents the minimum torque output by the engine at its current speed. For engine output torque, This represents the maximum torque output by the engine at the current speed.
[0037] Under actual operating conditions, the set of gears currently available for the vehicle is as follows: However, the gear selection must simultaneously meet the above-mentioned engine speed constraints and engine torque constraints.
[0038] Under the premise of satisfying the above constraints, the dynamic programming algorithm is used to solve the optimization objective function, specifically including: The objective function is to iterate through all 16 gears at each typical operating point, calculate the instantaneous fuel consumption for each gear, and then calculate the cumulative fuel consumption through stage-by-stage recursion. Solve The minimum value is used to determine the optimal gear at each moment.
[0039] Extract the optimal gear for all typical operating conditions and construct an optimal gear partitioning map with vehicle speed, throttle opening, and vehicle acceleration as inputs and the optimal gear as output, such as... Figure 4 As shown.
[0040] Step S4: Collect the current driving conditions in real time, determine the current optimal gear by combining the optimal gear partition map, and output it to the transmission to perform the gear shifting operation.
[0041] During actual vehicle operation, the current driving conditions are collected in real time. The current driving conditions include the current vehicle speed, current throttle opening, and current vehicle acceleration.
[0042] Calculate the distance between the current driving condition and each typical driving condition point in the optimal gear partition map. The specific expression is: ; in, Current vehicle speed For the current vehicle acceleration, The current throttle opening, For the first The current vehicle speed at a typical operating point For the first The current vehicle acceleration at a typical operating point For the first The current throttle opening at a typical operating point .
[0043] The gear corresponding to the typical operating condition point closest to the current driving condition is taken as the current optimal gear.
[0044] The currently optimal gear, as determined above, is output to the transmission to perform a gear shift.
[0045] To verify the effectiveness and practicality of the method of this invention, a system was built on the Matlab / Simulink platform as follows. Figure 5 The vehicle powertrain simulation model shown consists of five parts: a road module, a driver module, an engine module, a transmission module, and a driving resistance module. The road module is provided by a cyclic road spectrum; in this embodiment, a WTVC road spectrum is used for simulation verification. The driver module uses a PID controller to simulate the actual driver's operation, converting the difference between the required vehicle speed and the actual vehicle speed into an engine throttle signal. The engine module, through... Figure 1 The engine test data shown is used to establish and calculate the engine's output torque and fuel consumption rate in real time; the transmission module is based on the gear ratios of each gear to achieve torque transmission; the driving resistance module is based on wind resistance. Rolling resistance Ramp resistance and acceleration resistance Together, they constitute a system that calculates the current vehicle acceleration and current speed in real time based on Newton's second law. Current vehicle speed For density, The road slope angle, The rotational mass coefficient, For time.
[0046] This embodiment uses a traditional economical three-parameter shifting strategy as a comparison benchmark. Specifically, the economical three-parameter shifting strategy aims to minimize fuel consumption. It calculates the shift interfaces between adjacent gears in a three-dimensional space of vehicle speed, throttle opening, and vehicle acceleration by solving nonlinear polynomial equations. For a 16-speed transmission, 15 shift interfaces need to be calculated pairwise. During shift decision-making, the current vehicle speed, throttle opening, and vehicle acceleration are used to determine the current interface range and thus the appropriate gear to engage.
[0047] Simulation tests were conducted using both the economical three-parameter shifting strategy and the method of this invention. The input parameters were current vehicle speed, current throttle opening, and current vehicle acceleration. The objective of the economical three-parameter shifting strategy is to determine which two shift points the current driving condition falls between. The optimal gear determination process is as follows: Figure 6 As shown in (a) above, the method of this invention solves for the typical operating condition closest to the current driving condition in three-dimensional coordinates. The optimal gear determination process is as follows: Figure 6 As shown in (b) of the diagram.
[0048] With the driver's accelerator pedal set to 1 and the road model's slope set to 0, the vehicle was kept traveling in a straight line. Simulation tests of full-throttle acceleration dynamics were conducted using two different shifting strategies. The simulation results are as follows: Figure 7 As shown.
[0049] like Figure 7 As shown in (a), the maximum vehicle speed is 50 km / h under both shift strategies. The vehicle accelerating to its maximum speed under the economy three-parameter shift strategy takes 8.88 s, while the vehicle controlled by the method of this invention takes 8.75 s, a reduction of approximately 1.4%. This demonstrates that the method of this invention provides superior power performance for the vehicle. Figure 7 As shown in (b), the gear shifting results show that both shifting strategies have a fast shifting rhythm, completing the shifting of 16 gears within 3 seconds.
[0050] Simulation tests were conducted using combined WTVC, WHTP, and FTP heavy-duty road spectrum to verify the fuel economy of the shifting strategy. The driver's throttle input depends on the difference between the required and actual vehicle speeds; the vehicle maintains a straight-line trajectory with a zero-slope road gradient. Simulation results are as follows: Figure 8 As shown, where, Figure 8 (a) in the figure represents the speed-following capability. Figure 8 In the figure, (b) represents the engine speed. Figure 8 (c) in the figure represents the change in fuel consumption over time. Figure 8 (d) in the text represents the gear shifting situation.
[0051] like Figure 8 As shown in (a), the vehicles under both shift strategies can achieve good speed following, which indicates that whether it is the method of the present invention or the economic three-parameter shift strategy, the vehicle can still fully meet the power demand while optimizing fuel economy.
[0052] like Figure 8 As shown in (b), the engine operates at medium speeds (1200 RPM~1500 RPM) under most driving conditions. Figure 8 As shown in (c), the fuel consumption of the vehicles under the two shift strategies is very close. The average fuel consumption per 100 kilometers of the vehicle under the economic three-parameter shift strategy is 30.61L, while the average fuel consumption per 100 kilometers of the vehicle under the method of the present invention is 30.59L, which is 0.06% lower than that of the economic three-parameter shift strategy, indicating that the method of the present invention has good fuel economy.
[0053] All simulation tests were conducted on a computer with an i7-10700 / 2.90GHz CPU and 16GB of RAM. The average computation time required for the three-parameter shifting strategy to query the current gear is... The average calculation time required for the method of this invention to plan the current gear once is... The results show that the method of the present invention does not require improving chip performance or increasing the onboard computing burden, and can be directly applied to real vehicles by replacing the traditional three-parameter shifting strategy.
[0054] In summary, the method of this invention avoids nonlinear polynomial fitting of engine characteristics and eliminates the need to solve complex nonlinear equations, thereby reducing model dependence and making it applicable to multi-gear transmissions. It eliminates the need to calculate gear shift boundaries pairwise, directly optimizing based on typical road spectra, and exhibits strong transferability: when changing vehicle models, only engine characteristic data needs to be updated, without re-deriving the shift boundary formula. Furthermore, the method facilitates multi-objective extension, allowing the introduction of shift frequency penalties or driving style factors into the optimization objective function, expanding it into a multi-objective optimization framework that more closely reflects actual driving conditions and driver needs.
[0055] Therefore, the present invention adopts the above-mentioned automatic gear shifting control method for non-road vehicles based on dynamic programming, which overcomes the problems of complex calculation, long time consumption, exponential increase in calculation amount when the number of gears increases, and strong dependence on real vehicle operating data and on-board chips in the prior art. Thus, while reducing online calculation complexity and hardware cost, it ensures the power performance and economic performance of the vehicle, and provides an efficient and practical automatic gear shifting control solution for multi-gear non-road vehicles.
[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.
Claims
1. A method for automatic gear shifting control of off-road vehicles based on dynamic programming, characterized in that, Includes the following steps: Step S1: Establish a model of the powertrain system for non-road vehicles; Step S2: Based on the non-road vehicle powertrain system model, select typical cyclic road spectra and discretize them to construct an optimization objective function; Step S3: Use dynamic programming algorithm to solve the objective function to obtain the optimal gear partitioning diagram; Step S4: Collect the current driving conditions in real time, determine the current optimal gear by combining the optimal gear partition map, and output it to the transmission to perform the gear shifting operation.
2. The method for automatic gear shifting control of off-road vehicles based on dynamic programming according to claim 1, characterized in that, Step S1 also includes obtaining engine characteristic parameters, transmission system parameters, and driving resistance characteristic parameters; Engine characteristic parameters include the engine's output torque data at different throttle openings and speeds, as well as fuel consumption rate data at different torques and throttle openings; transmission system parameters include the gear ratios of each gearbox, the rotational mass coefficients of each gear, the final drive ratio, and the mechanical transmission efficiency; driving resistance characteristic parameters include the vehicle's curb weight, frontal area, air resistance coefficient, tire radius, and tire rolling resistance coefficient.
3. The method for automatic gear shifting control of off-road vehicles based on dynamic programming according to claim 1, characterized in that, In step S2, the typical cycle route spectrum includes WTVC, WHTP and FTP Heavy-Duty; the discretization process is to discretize the total travel time after combining the typical cycle route spectrum with a time step of 1 second to obtain several typical working condition points.
4. The method for automatic gear shifting control of off-road vehicles based on dynamic programming according to claim 1, characterized in that, In step S2, with minimizing vehicle fuel consumption as the optimization objective, an optimization objective function is constructed. The specific expression is: ； in, For the vehicle in the The gear, the first Instantaneous fuel consumption per second. This represents the total travel time.
5. The method for automatic gear shifting control of off-road vehicles based on dynamic programming according to claim 1, characterized in that, In step S3, when using the dynamic programming algorithm to solve the optimization objective function, the engine speed constraint and the engine torque constraint must also be satisfied. The specific expression for the engine speed constraint is: ； The specific expression for the engine torque constraint is: ； in, This is the minimum permissible engine speed. This refers to the engine output speed. This is the engine's maximum permissible speed. This represents the minimum torque output by the engine at its current speed. For engine output torque, This represents the maximum torque output by the engine at the current speed.
6. The method for automatic gear shifting control of off-road vehicles based on dynamic programming according to claim 5, characterized in that, In step S3, the dynamic programming algorithm is used to solve the objective function, specifically including: The process iterates through each gear at each typical operating point, calculates the instantaneous fuel consumption for each gear, and then calculates the cumulative fuel consumption through stage-by-stage recursion, thus optimizing the objective function. Solve The minimum value is used to determine the optimal gear at each moment; Extract the optimal gear under all typical operating conditions and construct an optimal gear partition map with vehicle speed, throttle opening and vehicle acceleration as inputs and the optimal gear as output.
7. The method for automatic gear shifting control of off-road vehicles based on dynamic programming according to claim 1, characterized in that, In step S4, the current driving conditions include the current vehicle speed, the current throttle opening, and the current vehicle acceleration.
8. The method for automatic gear shifting control of off-road vehicles based on dynamic programming according to claim 1, characterized in that, In step S4, the current optimal gear is determined by combining the optimal gear zoning map, specifically including: Calculate the distance between the current driving condition and each typical driving condition point in the optimal gear partition map. The specific expression is: ； in, Current vehicle speed For the current vehicle acceleration, The current throttle opening, For the first The current vehicle speed at a typical operating point For the first The current vehicle acceleration at a typical operating point For the first The current throttle opening at a typical operating point ; The gear corresponding to the typical operating condition point closest to the current driving condition is taken as the current optimal gear.