Vehicle automatic transmission skip-shift decision method based on dynamic optimization of predicted driving conditions

Abstract

The application discloses a kind of vehicle automatic transmission overdrive shift decision-making methods based on predicted driving condition dynamic optimization, comprising the following steps: step one, at a certain time t0, overdrive shift decision-making module receives the shift enabling signal sent by shift logic module, the value is 1, overdrive shift decision-making module is enabled, start calculation;Step two, overdrive shift decision-making module calculates the predicted termination time t f Of future driving condition;Step three, after obtaining predicted termination time t f , overdrive shift decision-making module starts calculating the objective function J of overdrive shift scheme and step-by-step shift scheme in this predicted time;Step four, if the objective function J of overdrive shift scheme Override Less than the objective function J of step-by-step shift scheme Step , overdrive shift decision-making module decides that overdrive shift is needed;If the objective function J of overdrive shift scheme Override Greater than the objective function J of step-by-step shift scheme Step , overdrive shift decision-making module decides that step-by-step shift is needed.

Description

Technical Field

[0001] This invention relates to the field of automotive automatic transmission control system technology, and in particular to a method for skip-shift decision-making in vehicle automatic transmissions based on dynamic optimization of predicted driving conditions. Background Technology

[0002] Optimized control of automatic transmission gears is a crucial step in heavy-duty commercial vehicles to adjust the distribution of engine operating points and achieve a balance between power, economy, and driving comfort.

[0003] Heavy-duty commercial vehicles, due to their wide range of load variations and complex operating environments, place greater emphasis on fuel economy, and therefore are often equipped with automatic transmissions with a higher number of gears. A higher number of gears allows for better traction, improved acceleration and hill-climbing ability, and also increases the likelihood of the engine operating in a low-fuel-consumption range, thereby reducing transportation costs for commercial vehicles.

[0004] However, while the increased number of gears in automatic transmissions for heavy-duty commercial vehicles brings advantages, it also introduces some disadvantages. For example, within the same speed range, heavy-duty commercial vehicles with more gears shift gears more frequently than ordinary cars. Currently, most automatic transmissions used in heavy-duty commercial vehicles are automated manual transmissions (AMT). Because AMT involves power interruption during gear shifts, frequent shifting leads to power loss, which is particularly severe when driving on inclines. Furthermore, frequent shifting significantly reduces driver comfort. Therefore, when vehicle speed changes rapidly, the time a vehicle maintains a particular gear is shorter, and the engine operates within its optimal RPM range for that gear for a shorter period. Compared to the disadvantages of frequent shifting, if a single shift could skip several gears, the number of shifts could be reduced, thus minimizing power loss during shifts and improving driver comfort.

[0005] Skipping gears is effective in reducing the number of gear changes and power loss. However, after each skipped shift, the engine's operating speed range is widened compared to sequential shifts. This may lead to a deterioration in fuel consumption and torque within certain speed ranges, depending on the engine's torque and fuel consumption characteristics. Therefore, the decision to skip gears is crucial, requiring a comprehensive consideration of fuel economy, power, and driver comfort to make a reasonable and expected outcome.

[0006] Currently, most decision-making methods for skipping gears are rule-based. For example, the literature (Cong Xiaoyan. Research on Automatic Gear Shifting Strategy and Key Parameters of Heavy Truck AMT [D]. Shandong University, 2017.) establishes a skipping gear shifting decision-making method under different loads based on acceleration. By calibrating different acceleration rules under different loads, it decides whether to skip gears. Vehicle acceleration characterizes the rate of change of vehicle speed. When the acceleration is large, the vehicle speed changes quickly, and the vehicle maintains a certain gear for a short time. At this time, skipping gears is indeed suitable. Therefore, establishing rules based on acceleration to guide the decision-making of skipping gears is a feasible solution. However, the acceleration during the acceleration process is greatly affected by the vehicle load and gear. If the acceleration threshold under different loads is used as the decision-making basis, it will lead to a large workload, and the optimization goal of the calibration process is too subjective, which may lead to the calibration results failing to achieve the expected goal of improving power and reducing power loss. Therefore, if we attempt to develop a model-based method for skip-shift decision-making by comprehensively comparing the performance of skip-shift and step-shift in terms of economy, power, and driving comfort based on the theory of vehicle longitudinal dynamics, it would be of great significance for solving the problems caused by step-shift in multi-gear AMTs of heavy commercial vehicles. Summary of the Invention

[0007] The purpose of this invention is to address the problems of complex shifting decisions and large calibration workload in existing technologies by providing a method for automatic transmission shifting decisions based on dynamic optimization of predicted driving conditions. It should be noted that the shifting logic module's function is to determine when and to which gear to shift during vehicle operation. It uses real-time information such as driver accelerator pedal opening, vehicle speed, and actual gear position to determine whether the current driving conditions meet the shifting requirements. This invention targets shifting behavior during acceleration, setting the shifting level to level 1, i.e., shifting two gears at once. Therefore, this invention determines whether the current driving conditions meet the upshifting conditions. In this invention, the decision between shifting to a higher gear or shifting sequentially is made by comparing the vehicle's overall performance in terms of economy, power, and driving comfort under different scenarios. Specifically, the decision is made by comparing the overall performance of different scenarios within the same time frame (expressed as a cost function in this patent). Specifically, in terms of economy, the predicted fuel consumption per 100 kilometers during the driving conditions is used as a quantitative indicator; in terms of power, the predicted final vehicle speed during the driving conditions is used as a quantitative indicator; and in terms of driving comfort, a certain penalty for frequent gear shifts is imposed on the step-by-step shifting scheme as a quantitative indicator. The final objective function J is the weighted sum of the predicted fuel consumption per 100 kilometers, the final vehicle speed, and the penalty for frequent gear shifts during the driving conditions. Each quantitative indicator has its own corresponding weight coefficient, which facilitates the decision-making of skip-level shifts in the expected optimization direction.

[0008] The technical solution adopted to achieve the purpose of this invention is:

[0009] A method for skip-shift decision-making in vehicle automatic transmissions based on dynamic optimization of predicted driving conditions includes the following steps:

[0010] Step 1: At a certain moment t0, the skip-shift decision module receives a shift enable signal with a value of 1 sent by the shift logic module. The skip-shift decision module is then enabled and begins calculation.

[0011] Step 2: The skip-shift decision module calculates the predicted termination time t for future driving conditions. f ;

[0012] Step 3: Calculate the predicted termination time t f Then, the skip-shift decision module begins to calculate the objective function J of the skip-shift scheme and the step-shift scheme within this prediction time. The objective function of the skip-shift scheme is J. Override The objective function of the step-by-step shifting scheme is J Step ;

[0013] Step four, if the objective function J of the skip-level shifting scheme is... Override The objective function J of the step-by-step shifting scheme is less than Step If the skip-shift decision module determines that a skip-shift is required, it outputs a skip-shift enable signal with a value of 1 to the shift logic module; if the objective function J of the skip-shift scheme is... Override The objective function J of the step-by-step shifting scheme is greater than Step If the skip-shift decision module determines that a step-by-step shift is required, it outputs a skip-shift signal with a value of 0 to the shift logic module. After receiving skip-shift enable signals with different values, the shift logic module begins to take corresponding upshift measures, either skipping shifts or shifting up step-by-step, and finally outputs the corresponding target gear.

[0014] In the above technical solution, in step one, if the shift logic module determines that the upshift condition is met at time t0, it starts to send a shift enable signal with a value of 1 to the skip-shift decision module to enable the skip-shift decision module; at other times when the upshift condition is not met, the shift enable signal value is 0, and the shift decision module cannot be enabled.

[0015] In the above technical solution, in step two, the termination time t f Calculate using the following steps:

[0016] Predict the vehicle speed at the initial time t0+x using the vehicle speed v0 at time t0. Vehicle speed v0 can be obtained directly in real time. For ease of calculation, the decrease in wind resistance due to the decrease in vehicle speed during the power interruption from time t0 to time t0+x is negligible. The air resistance calculated from vehicle speed v0 is directly used as the air resistance at the time of power interruption in the future xs, then:

[0017]

[0018] In the formula, δ is the rotational mass coefficient, which is mainly related to the vehicle weight, wheels, engine flywheel moment of inertia, and transmission ratio; m is the vehicle mass; g is the acceleration due to gravity; f is the rolling resistance coefficient; θ is the road gradient; and C... d Where A is the drag coefficient and A is the frontal area.

[0019] Solving the longitudinal dynamics equations of the vehicle using iteration Further solve for v(t):

[0020] The longitudinal dynamic equation of the vehicle is:

[0021]

[0022] Where δ is the rotational mass coefficient, T e (t) represents the engine output torque at time t, i g Let i0 be the gear ratio at gear n+1, i0 be the gear ratio of the main reducer, η be the transmission efficiency of the transmission system, r be the wheel rolling radius, and v(t) be the vehicle speed at time t in m / s. The initial time t0+x is predicted. Let be the acceleration at time t;

[0023] In each iteration of the solution process, the vehicle speed v(t) is calculated as follows:

[0024]

[0025] Where dt is the iteration step size for solving the vehicle speed iteratively;

[0026] Engine output torque T e (t) is a parameter expressed by the accelerator pedal operation, and the prediction model for the accelerator pedal is:

[0027]

[0028] In the formula, α(t) represents the accelerator pedal information, and α(0) represents the accelerator pedal opening at the predicted initial moment, which can be directly obtained in real time and is equal to the accelerator opening collected by the shift logic module at time t0. cThe initial throttle opening change rate is calculated in real time based on α(0), and is equal to (α(0) - α(0 - ΔT)) / ΔT, where ΔT is the scheduling cycle of the shift logic module, and α(0 - ΔT) is the throttle opening collected at time (t0 - ΔT). μ is the attenuation rate, defined as μ = α c / (2t′ f ), where t′ f The termination time for throttle opening prediction is T, and the step size T of the throttle opening prediction algorithm is... s The iteration step size dt is the same as that of the vehicle speed;

[0029] Engine output torque T e (t) also depends on the engine speed n. e (t), we have:

[0030] T e (t)=f(n e (t), α(t))

[0031] Engine speed n e (t) can be calculated from the vehicle speed v(t) in each iteration, as follows:

[0032]

[0033] In the formula, i g The gear ratios corresponding to the gears in the step-by-step shifting scheme are i0, i0 is the gear ratio corresponding to gear n+1, r is the wheel rolling radius, and 0.1047 is the result of π / 30, where π is the circumference ratio.

[0034] In each speed iteration, the vehicle speed result v(t) is compared with the speed threshold v for shifting from gear n+1 to gear n+2. (n+1)-(n+2) The comparison continues until a certain iteration ends, at which point the vehicle speed result v(t) ≥ v (n+1)-(n+2) Record the number of iterations m from the start of the iteration to this point, then time t f The value can be obtained by subtracting -x, which is: t f -x = m*dt + t0 + x;

[0035] Thus, the predicted termination time t is obtained. f :t f = m*dt+t0+x+x.

[0036] In the above technical solution, the specific expression of the objective function in step three is as follows:

[0037]

[0038] In the formula, J Eco Fuel consumption per 100 kilometers J is the terminal vehicle speed.Shift To address the shift penalty in a step-by-step shifting scheme, this invention sets J... Shift The value is 1, and the J value of the skip-level shifting scheme is 1. Shift =0, These are the weighting coefficients for economy, power, and driving comfort, respectively.

[0039] In the above technical solution, after the iterative calculation is completed, at the prediction termination time t... f The final vehicle speed of the skip-shift scheme can be obtained.

[0040] In the above technical solutions,

[0041] In the formula, Q Fuel (t) represents the fuel consumed by the engine during the time interval from time t to time t+dt, in grams (g) and liters (L). Dist (t) represents the distance traveled by the vehicle within the time range from time t to time t+dt, in meters.

[0042] In the above technical solution, for the skip-gear shifting scheme, the driving state is maintained throughout the prediction time range. Iterative calculations are completed using the dynamics and energy efficiency model of the driving process and substituted into J. Eco From the expression, J under the skip-shift scheme can be obtained. Eco i under the skip-level shifting scheme g This is the gear ratio corresponding to gear n+2.

[0043] In the above technical solution, for the step-by-step shifting scheme, there are driving and non-driving processes within the prediction time range. The dynamics and energy efficiency models corresponding to the driving and non-driving processes are iteratively calculated and substituted into the expression J. Eco In this way, J can be obtained under the step-by-step shifting scheme. Eco i under the step-by-step shifting scheme g This is the gear ratio corresponding to gear n+1.

[0044] In the above technical solutions, within the prediction timeframe, there are dynamic and energy efficiency models for the driving process:

[0045]

[0046] In the above technical solutions, within the prediction timeframe, for non-driven processes, there are dynamic and energy efficiency models:

[0047]

[0048] Compared with the prior art, the beneficial effects of the present invention are:

[0049] 1) This invention proposes a method for skip-level shifting decisions by comparing the benefits of different shifting strategies based on rolling predictions of dynamics and energy efficiency models within a future time window. This effectively considers the power loss caused by the interruption of driving force during the shifting process, making the decision-making for skip-level shifting more targeted.

[0050] 2) A multi-objective cost function that integrates dynamic performance, economy, and driving comfort within a future time window is proposed, and a model-based automatic optimization approach is adopted to effectively solve the problem that traditional algorithms rely on a large number of shift tables (MAPs) for calibration and have weak adaptability. Attached Figure Description

[0051] Figure 1 This is a framework diagram of the skip-level shift decision method of the present invention;

[0052] Figure 2 This is a flowchart illustrating step one of the skip-gear shift decision-making method of the present invention;

[0053] Figure 3 This is an abstract schematic diagram of steps two and three of the skip-gear shift decision method of the present invention;

[0054] Figure 4 This is a flowchart illustrating step four of the skip-gear shift decision method of the present invention;

[0055] Figure 5 The diagram shows the gear shifting effect of the skip-level shifting decision method of the present invention in a phase of acceleration and deceleration with a greater focus on power performance.

[0056] Figure 6 The diagram shows the gear shifting effect of the skip-gear shifting decision method of the present invention in the acceleration and deceleration process with a greater focus on economy.

[0057] Figure 7 The diagram shows the gear shifting effect of the skip-level shifting decision method of the present invention during an acceleration or deceleration process with a greater focus on driving comfort. Detailed Implementation

[0058] The present invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0059] like Figure 1 As shown in the framework diagram, this invention provides a method for skip-shift decision-making of vehicle automatic transmissions based on dynamic optimization of predicted driving conditions, specifically including the following steps:

[0060] Step 1, as follows Figure 2 As shown, at a certain time t0, the skip-shift decision module receives a shift enable signal with a value of 1 from the shift logic module. The skip-shift decision module is then enabled and begins calculation:

[0061] If the shift logic module determines that the upshift condition is met at time t0, it sends a shift enable signal with a value of 1 to the skip-shift decision module to enable it. At other times when the upshift condition is not met, the shift enable signal is 0, and the shift decision module is not enabled. The method by which the shift logic module determines whether the upshift condition is met is a known method in the industry and familiar to those skilled in the art; therefore, it will not be described in detail in this patent. The recommended, but not limited to, scheduling cycle for the entire vehicle's automatic transmission shift strategy is 0.02 seconds.

[0062] Step two, as Figure 3 As shown, the skip-shift decision module calculates the predicted termination time t for future driving conditions. f It should be noted that the speed curve in the figure only represents the acceleration and deceleration process, and does not represent the actual speed change curve during acceleration and deceleration.

[0063] The skip-shift decision module is enabled and begins calculation at time t0, with time t0+x as the initial time for predicting the driving conditions. Here, x represents the duration of the shift. At time t0+x, both the skip-shift scheme and the step-shift scheme start from the same starting point a (at the same speed) and begin acceleration. At this point, the two schemes are in different gears. Assuming the step-shift scheme shifts to gear n+1 at time t0+x, then the skip-shift scheme shifts to gear n+2 at time t0+x.

[0064] Predict the vehicle speed at the initial time t0+x using the vehicle speed v0 at time t0. Vehicle speed v0 can be obtained directly in real time. For ease of calculation, the decrease in wind resistance due to the decrease in vehicle speed during the power interruption from time t0 to time t0+x is negligible. The air resistance calculated from vehicle speed v0 is directly used as the air resistance at the time of power interruption in the future xs, then:

[0065]

[0066] In the formula, δ is the rotational mass coefficient, which is mainly related to the vehicle weight, wheels, engine flywheel moment of inertia, and transmission ratio; m is the vehicle mass; g is the acceleration due to gravity; f is the rolling resistance coefficient; θ is the road gradient; and C... d Where A is the drag coefficient and A is the frontal area.

[0067] At the predicted initial time t0+x, the step-by-step shifting scheme, due to its lower gears and larger gear ratios, theoretically has stronger acceleration capabilities than the skip-gear shifting scheme. Therefore, it reaches the upshift speed threshold for the target gear of the skip-gear shifting scheme faster, i.e., the speed threshold for shifting from gear n+1 to gear n+2. Figure 3The line segment ab in the equation. Therefore, the successive gear shifting scheme can be iteratively solved according to the vehicle longitudinal dynamics equation. It is predicted that acceleration begins at the initial time t0+x, and how long it takes to reach the speed threshold (line segment jk) for shifting from gear n+1 to n+2. During the iterative solution process, the vehicle longitudinal dynamics equation is:

[0068]

[0069] Where δ is the rotational mass coefficient, T e (t) represents the engine output torque at time t, i g Let i0 be the gear ratio at gear n+1, i0 be the gear ratio of the main reducer, η be the transmission efficiency of the transmission system, r be the wheel rolling radius, and v(t) be the vehicle speed at time t in m / s. The initial time t0+x is predicted. Let be the acceleration at time t.

[0070] In each iteration of the solution process, the vehicle speed v(t) is calculated as follows:

[0071]

[0072] Where dt is the iteration step size for solving the vehicle speed iteratively, and the present invention recommends, but is not limited to, 0.02s.

[0073] Engine output torque T during the iteration process e (t) is the key point of this invention for predicting driving conditions, and the engine output torque is a parameter expressed by the accelerator pedal operation. Therefore, accurate prediction of the accelerator pedal opening is crucial. Based on the literature (Xiangrui ZE, Kaisheng HU, Fanbo ME. Model predictive control for parallel hybrid electric vehicles with potential real-time capability. Journal of Automotive Safety and Energy. 2012 Jun 18; 3(2): 165.), the prediction model of the accelerator pedal is obtained as follows:

[0074]

[0075] In the formula, α(t) represents the accelerator pedal information, and α(0) represents the accelerator pedal opening at the predicted initial moment, which can be directly obtained in real time and is equal to the accelerator opening collected by the shift logic module at time t0. cThe rate of change of throttle opening at the initial moment can be obtained in real time from α(0), and is equal to (α(0)-α(0-ΔT)) / ΔT, where ΔT is the scheduling cycle of the shift logic module, and α(0-ΔT) is the throttle opening collected at time (t0-ΔT). μ is the attenuation rate, defined as μ=α c / (2t′ f ), where t′ f The present invention sets an termination time t′ to represent the termination time for throttle opening prediction. f Recommended, but not limited to, 2 seconds, the distance step length T of the throttle opening prediction algorithm. s The iteration step size dt should be the same as that for vehicle speed, and is recommended but not limited to 0.02s.

[0076] After predicting the accelerator pedal opening in the next 2 seconds from the initial time t0+1, the engine output torque T e (t) also depends on the engine speed n. e (t), we have:

[0077] T e (t)=f(n e (t), α(t))

[0078] In the formula, the engine speed n e (t) can be calculated from the vehicle speed v(t) in each iteration, as follows:

[0079]

[0080] In the formula, i g The gear ratios corresponding to the gears in the step-by-step shifting scheme are i0, i0 is the gear ratio corresponding to gear n+1, r is the wheel rolling radius, and 0.1047 is the result of π / 30, where π is the circumference ratio.

[0081] In each speed iteration, the vehicle speed result v(t) is compared with the speed threshold v for shifting from gear n+1 to gear n+2. (n+1)-(n+2) The comparison continues until a certain iteration ends, at which point the vehicle speed result v(t) ≥ v (n+1)-(n+2) Record the number of iterations m from the start of the iteration to this point, then time t f The value can be obtained by subtracting -x, which is: t f -x = m*dt + t0 + x;

[0082] Thus, the predicted termination time t is obtained. f :t f =m*dt+t0+x+x

[0083] Step 3: Calculate the predicted termination time t fThen, the skip-shift decision module begins to calculate the objective function J of the skip-shift scheme and the step-shift scheme during this prediction time:

[0084] In this invention, the specific expression of the objective function is:

[0085]

[0086] In the formula, J Eco Fuel consumption per 100 kilometers J is the terminal vehicle speed. Shift To address the shift penalty in a step-by-step shifting scheme, this invention sets J... Shift The value is 1, and the J value of the skip-level shifting scheme is 1. Shift It is 0. These are the weighting coefficients for economy, power, and driving comfort, respectively, where J... Eco The expression is:

[0087]

[0088] In the formula, Q Fuel (t) represents the fuel consumed by the engine during the time interval from time t to time t+dt, in grams (g) and liters (L). Dist (t) represents the distance traveled by the vehicle within the time range from time t to time t+dt, in meters.

[0089] Within the prediction timeframe, for the driving process, there are dynamic and energy efficiency models:

[0090]

[0091] Within the prediction timeframe, for non-driven processes, there are kinetic and energy efficiency models:

[0092]

[0093] For skip-shift schemes, the driving state is maintained within the predicted time range, such as... Figure 3 The vehicle speed curves ag and gd in the model are used to perform iterative calculations based on the dynamics and energy efficiency model of the driving process, and then substituted into J. Eco From the expression, J under the skip-shift scheme can be obtained. Eco It should be noted that the i under the skip-level shifting scheme g This is the gear ratio corresponding to gear n+2.

[0094] After the iterative calculation is completed, at the prediction termination time t f The final vehicle speed of the skip-shift scheme can be obtained.

[0095] For a step-by-step shifting scheme, there are driving and non-driving processes within the prediction time range. The driving process is as follows: Figure 3 Medium vehicle speed curve ab, non-driving process as follows Figure 3 The medium speed curve is bc. Each curve segment is substituted into the corresponding dynamics and energy efficiency models to complete iterative calculations and then input into the expression J. Eco In this way, J can be obtained under the step-by-step shifting scheme. Eco It should be noted that the i under the step-by-step shifting scheme g This is the gear ratio corresponding to gear n+1.

[0096] After the iterative calculation is completed, at the prediction termination time t f The final vehicle speed of the step-by-step shifting scheme can be obtained.

[0097] J obtained from the two methods Eco , and J Shift Substitute these values ​​into the objective function expression of each solution, and then set different weight coefficients according to the different optimization objectives. Finally, the objective function J under both schemes can be obtained.

[0098] Step four, as Figure 4 As shown, after calculating the objective functions J of the skip-shift scheme and the step-shift scheme, their magnitudes are compared. If the objective function J of the skip-shift scheme is... Override The objective function J of the step-by-step shifting scheme is less than Step If the skip-shift decision module determines that a skip-shift is required, it outputs a skip-shift enable signal with a value of 1 to the shift logic module; if the objective function J of the skip-shift scheme is... Override The objective function J of the step-by-step shifting scheme is greater than Step If the skip-shift decision module determines that a step-by-step shift is required, it outputs a skip-shift signal with a value of 0 to the shift logic module. After receiving skip-shift enable signals with different values, the shift logic module begins to take corresponding upshift measures, either skipping shifts or shifting up step-by-step, and finally outputs the corresponding target gear.

[0099] It should be noted that in step two, under certain driving conditions, the vehicle speed curve ab of the step-by-step shifting scheme will never reach the vehicle speed threshold v for shifting from gear n+1 to gear n+2. (n+1)-(n+2) (Line segment jk) If this situation is found, that is, when the vehicle speed can no longer be increased, the iteration process stops, and the skip-level shift enable signal is 0, and only the step-by-step shift scheme can be implemented.

[0100] Adjusting weighting coefficients To make the optimization objective place greater emphasis on dynamic performance, we obtain gear shift diagrams for unloaded and fully loaded vehicles during an acceleration and deceleration process, such as... Figure 5As shown in the figure, both unloaded and fully loaded conditions allow for skip-gear shifting, and these skip-gear shifts always occur in relatively low gear ranges. This is because lower gears offer better acceleration compared to higher gears. Within the same time window, the skip-gear shifting scheme provides x seconds of acceleration time compared to the step-by-step shifting scheme, and this x seconds of acceleration time accounts for a larger proportion of the total predicted time in lower gears compared to higher gears. On the other hand, in the high gear range, the speed curve ab of the step-by-step shifting scheme will never reach the speed threshold v for shifting from gear n+1 to gear n+2. (n+1)-(n+2) The possibility of (line segment jk) is also greater, so only a step-by-step upgrade scheme can be implemented.

[0101] Adjusting weighting coefficients To make the optimization objective more focused on economy, we obtain the gear shifting effects of unloaded and fully loaded vehicles during a certain acceleration and deceleration process, such as... Figure 6 As shown in the figure, both no-load and full-load conditions allow for skip-gear upshifting, but the frequency of skip-gear upshifts is significantly reduced. This is because the step-by-step upshifting scheme increases the probability of the engine operating in the low fuel consumption range, thus allowing the J in the objective function to be optimized. Eco They were smaller, so the final decision was that they shouldn't skip levels and upgrade.

[0102] Adjusting weighting coefficients To prioritize driving comfort in the optimization objective, we obtained gear shift diagrams for unloaded and fully loaded vehicles during an acceleration and deceleration process, such as... Figure 7 As shown in the figure, both unloaded and fully loaded conditions allow for skipping gears, with a significantly increased frequency of skipping gears. This is because, in terms of improving driving comfort, skipping gears is equivalent to shifting gears sequentially, resulting in fewer gear changes and thus better driving comfort.

[0103] It should be noted that the primary motivation for proposing skip-level shifting in engineering applications is that step-by-step shifting schemes suffer from frequent power interruptions. Therefore, theoretically, skip-level shifting is proposed to address the power loss caused by frequent shifting. Thus, in practical engineering applications, the optimization objective of the skip-level shifting decision method proposed in this invention is to focus more on power performance.

[0104] In summary, the above steps and Figure 5 , Figure 6 , Figure 7As can be seen, the automatic transmission skip-shift decision method for vehicles based on dynamic optimization of predicted driving conditions proposed in this invention effectively considers the power loss caused by the interruption of driving force during the shifting process when predicting driving conditions, making the skip-shift decision more targeted. On the other hand, it comprehensively considers the vehicle's power, economy, and driving comfort within the prediction time window, and performs model-based automatic optimization. The optimization results also match the predicted optimization objectives, effectively solving the problem of weak adaptability of traditional skip-shift decision algorithms that rely on a large number of shift tables (MAPs).

[0105] The above description is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for skip-shift decision-making in vehicle automatic transmissions based on dynamic optimization of predicted driving conditions, characterized in that, Includes the following steps: Step 1: At a certain moment t0, the skip-shift decision module receives a shift enable signal with a value of 1 sent by the shift logic module. The skip-shift decision module is then enabled and begins calculation. Step two, the step-up gear shift decision module calculates the predicted end time t of the future driving condition f ; Step three, obtain the predicted end time t f After that, the step-up shift decision module starts to calculate the objective function J of the step-up shift scheme and the step-by-step shift scheme in this predicted time, the objective function of the step-up shift scheme is J Override , and the objective function of the step-by-step shift scheme is J Step ; Step four, if the objective function J of the skip-level shifting scheme is... Override The objective function J of the step-by-step shifting scheme is less than Step If the skip-shift decision module determines that a skip-shift is required, it outputs a skip-shift enable signal with a value of 1 to the shift logic module; if the objective function J of the skip-shift scheme is... Override The objective function J of the step-by-step shifting scheme is greater than Step If the skip-shift decision module determines that a step-by-step shift is required, it outputs a skip-shift signal with a value of 0 to the shift logic module. After receiving skip-shift enable signals with different values, the shift logic module begins to take corresponding upshift measures, either skipping shifts or shifting up step-by-step, and finally outputs the corresponding target gear.

2. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 1, characterized in that, In step one, if the shift logic module determines that the upshift condition is met at time t0, it starts sending a shift enable signal with a value of 1 to the skip-shift decision module to enable the skip-shift decision module; at other times when the upshift condition is not met, the shift enable signal value is 0, and the shift decision module cannot be enabled.

3. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 1, characterized in that, In step two, the termination time t f Calculate using the following steps: Predict the vehicle speed at the initial time t0+x using the vehicle speed v0 at time t0. Vehicle speed v0 can be obtained directly in real time. For ease of calculation, the decrease in wind resistance due to the decrease in vehicle speed during the power interruption from time t0 to time t0+x is negligible. The air resistance calculated from vehicle speed v0 is directly used as the air resistance at the time of power interruption in the future xs, then: In the formula, δ is the rotational mass coefficient, m is the vehicle mass, g is the gravitational acceleration, f is the rolling resistance coefficient, θ is the road gradient, and C d Where A is the drag coefficient and A is the frontal area. Solving the longitudinal dynamics equations of the vehicle using iteration Further solve for v(t): The longitudinal dynamic equation of the vehicle is: Where δ is the rotational mass coefficient, T e (t) represents the engine output torque at time t, i g Let i0 be the gear ratio at gear n+1, i0 be the gear ratio of the main reducer, η be the transmission efficiency of the transmission system, r be the wheel rolling radius, and v(t) be the vehicle speed at time t in m / s. The initial time t0+x is predicted. Let be the acceleration at time t; In each iteration of the solution process, the vehicle speed v(t) is calculated as follows: Where dt is the iteration step size for solving the vehicle speed iteratively; Engine output torque T e (t) is a parameter expressed by the accelerator pedal operation. The prediction model for the accelerator pedal is: In the formula, α(t) represents the accelerator pedal information, and α(0) represents the accelerator pedal opening at the predicted initial moment, which can be directly obtained in real time and is equal to the accelerator opening collected by the shift logic module at time t0. c The rate of change of throttle opening at the initial moment is calculated in real time based on α(0), and is equal to (α(0)-α(0-ΔT)) / ΔT, where ΔT is the scheduling cycle of the shift logic module, α(0-ΔT) is the throttle opening collected at time (t0-ΔT), and μ is the attenuation rate, defined as μ=α c / (2t′ f ), where t′ f The termination time for throttle opening prediction is T, and the step size T of the throttle opening prediction algorithm is... s The iteration step size dt is the same as that of the vehicle speed; Engine output torque T e (t) also depends on the engine speed n. e (t), we have: T e (t)=f(n e (t),α(t)) Engine speed n e (t) can be calculated from the vehicle speed v(t) in each iteration, as follows: In the formula, i g The gear ratios corresponding to the gears in the step-by-step shifting scheme are i0, i0 is the gear ratio corresponding to gear n+1, r is the wheel rolling radius, and 0.1047 is the result of π / 30, where π is pi. In each speed iteration, the vehicle speed result v(t) is compared with the speed threshold v for shifting from gear n+1 to gear n+2. (n+1)-(n+2) The comparison continues until a certain iteration ends, at which point the vehicle speed result v(t) ≥ v (n+1)-(n+2) Record the number of iterations m from the start of the iteration to this point, then time t f –x can then be used to obtain: t f –x=m*dt+t0+x; Thus, the predicted termination time t is obtained. f :t f = m*dt+t0+x+x.

4. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 1, characterized in that, In step three, the specific expression of the objective function is: In the formula, J Eco Fuel consumption per 100 kilometers J is the terminal vehicle speed. Shift To address the shift penalty in a step-by-step shifting scheme, this invention sets J... Shift The value is 1, and the J value of the skip-level shifting scheme is 1. Shift =0, These are the weighting coefficients for economy, power, and driving comfort, respectively.

5. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 4, characterized in that, After the iterative calculation is completed, at the prediction termination time t f The final vehicle speed of the skip-shift scheme can be obtained.

6. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 4, characterized in that, In the formula, Q Fuel (t) represents the fuel consumed by the engine during the time interval from time t to time t+dt, expressed in grams (g) and liters (L). Dist (t) represents the distance traveled by the vehicle within the time range from time t to time t+dt, in meters.

7. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 4, characterized in that, For the skip-shift scheme, the driving state is maintained throughout the prediction time range. Iterative calculations are performed using the dynamics and energy efficiency model of the driving process, and J is then input. Eco From the expression, J under the skip-shift scheme can be obtained. Eco i under the skip-level shifting scheme g This is the gear ratio corresponding to gear n+2.

8. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 4, characterized in that, For the step-by-step shifting scheme, there are driving and non-driving processes within the prediction time range. The dynamics and energy efficiency models corresponding to the driving and non-driving processes are iteratively calculated and substituted into the expression J. Eco In this way, J under the step-by-step shifting scheme can be obtained. Eco i under the step-by-step shifting scheme g This is the gear ratio corresponding to gear n+1.

9. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 7 or 8, characterized in that, Within the prediction timeframe, for the driving process, there are dynamic and energy efficiency models:

10. The method for skip-shift decision-making of vehicle automatic transmission based on dynamic optimization of predicted driving conditions as described in claim 7 or 8, characterized in that, Within the prediction timeframe, for non-driven processes, there are kinetic and energy efficiency models:

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