A longitudinal load-based slip prevention method for a metro train

Abstract

The application discloses a subway train slip prevention method based on longitudinal load, comprising the following steps: S1, grouping the train and distributing brake force; S2, setting a creep rate threshold, and judging the current train wheel rail state according to the creep rate; S3, in the case that the creep rate is less than the creep rate threshold, judging the current train wheel rail state through longitudinal load; and S4, implementing corresponding brake force according to the current train wheel rail state. The application can obtain the maximum track friction force in real time and accurately, and avoid train slip in advance, thereby improving subway operation efficiency.

Description

Technical Field

[0001] This invention relates to the field of urban rail transit signal control technology, specifically a method for preventing subway train slippage based on longitudinal load. Background Technology

[0002] The subway track environment is complex and variable. For example, transitions between underground and above-ground sections, inclement weather such as rain and snow, and scenarios involving sandblasting and oil spraying can all alter the maximum friction the track can provide. If the train's control system cannot apply appropriate braking force in real time according to these environmental changes, train slippage may occur. Train slippage increases braking distance and causes wear on the wheels and rails. Severe slippage can lead to safety accidents such as train collisions.

[0003] Currently, methods for preventing slippage include the following:

[0004] Firstly, environmental parameters are acquired through environmental sensors and then input into a model to predict track conditions, thereby preventing train slippage. For example, CN110271521B discloses a train anti-slip control method based on a signal system, which predicts the achievable braking rate of the current track section by detecting rainfall information on the windshield in front of the train. CN111994129B discloses a wheel-rail train anti-slip control method and system, which determines the maximum adhesion of the current track by using an image of the track in front of the train. CN117508237A discloses an intelligent prediction method, device, and storage medium for train slippage, which inputs track information, operating tags, environmental characteristics, operating condition characteristics, and types of rail surface attachments into a pre-trained slippage detection model to obtain slippage prediction results.

[0005] These methods rely on the completeness of empirical model algorithms. Once a scenario beyond the model's consideration or a factor that is difficult for sensors to measure occurs, the predictions given by the model algorithm will deviate significantly from the actual situation.

[0006] Secondly, by inputting the wheel speed, acceleration, and other motion sensor signals of each wheel into a preset algorithm for comparison, it is determined whether the wheel is slipping. If wheel slippage is detected, the braking force is immediately and significantly reduced, and after the slippage disappears, the braking force is slowly increased. If slippage is detected again, the above process is repeated. For example, CN114964833A discloses a train slippage detection method and device, which inputs the train speed and acceleration information detected by onboard sensors into a slippage detection model to obtain the slippage detection result output by the model. CN116902027A discloses a train slippage protection control method, device, equipment, and medium, which judges the slippage state by the values ​​of the odometer and accelerometer, and performs emergency braking when the train is determined to be slipping for a long time. CN116654061A discloses a train slippage control method based on ATO and TCMS, braking, and traction fusion, which judges the slippage state by monitoring and comparing the speed and acceleration of each axle, and gradually reduces the braking force within the operating section after slippage occurs. CN114771475A discloses a method and system for preventing slippage during train braking, which determines whether slippage occurs by comparing the speeds of each wheel axle and reduces the braking force of the slipping wheel axle.

[0007] These methods require sensors to detect abnormal wheel and vehicle movement after train slippage has already occurred to determine the slippage status. Such methods cannot prevent train slippage; they can only take measures to mitigate its impact after it has happened. In special slippage scenarios where the wheel and vehicle movement is outside the algorithm's consideration, false positives and false negatives are prone to occur.

[0008] Third, the train reports the slippage status to the central processing unit, which then notifies other trains to enter rain / snow mode in specific areas to reduce braking force and prevent slippage. For example, CN105549587B discloses a method and system for automatic train control in rainy and snowy weather. It determines whether it is rainy or snowy weather by the number of slipping trains and the number of slippages. Once rainy or snowy weather is determined, a command is sent to all trains to reduce braking force. CN109625037B discloses a method and device for prompting trains to enter rain / snow mode in fully automatic unmanned driving mode. It determines whether all trains on the line should enter rain / snow mode by the slippage location and number of slippages reported by the trains, as well as the proportion of slipping trains among all trains. After entering rain / snow mode, the braking force of all trains is reduced in stages. CN113911179B discloses a control method, device, electronic equipment, and storage medium for automatic trains. It notifies subsequent trains to enter rain / snow mode based on the slippage information given by the previous train, reducing braking force and preventing sand spillage.

[0009] These methods require the first or a few trains to slip before determining that the entire line or area has entered a rain / snow mode and instructing subsequent trains to reduce braking force. This method cannot prevent the first or a few trains from slipping. Furthermore, because real-time track conditions are unavailable, uniformly lower braking force is applied across the entire line or area to avoid subsequent trains slipping, severely impacting subway operational efficiency.

[0010] Fourthly, some patents utilize coupler force. For example, CN1043023C discloses a coupler stress-splitting traction method for multi-train heavy-haul trains, using coupler stress to coordinate the traction and braking force of the rear locomotives in a heavy-haul train, keeping their movement synchronized with the lead locomotive and reducing pressure and tension on the couplers. CN110525487B discloses an automatic driving method and system based on coupler force constraints, using coupler force to control traction through algorithms to maintain consistent movement of all parts of a heavy-haul train and prevent decoupling. CN113371005A discloses a device and method for calculating axle load transfer and controlling motor torque output through coupler force, using coupler force to determine the degree of train center of gravity transfer and adjust the braking force on the front and rear wheels to fully utilize the different track friction forces caused by the different downward pressure on the front and rear wheels. This method is similar to adjusting the front and rear brake ratio in racing.

[0011] These methods cannot determine the track condition, and therefore cannot prevent or avoid slippage.

[0012] Therefore, to address the above shortcomings, a method for preventing subway train slippage based on longitudinal load is provided. Summary of the Invention

[0013] The purpose of this invention is to overcome the shortcomings of existing methods and provide a method for preventing subway train slippage based on longitudinal load. By accurately obtaining the maximum friction force of the track in real time, the method can prevent train slippage in advance and improve the efficiency of subway operation.

[0014] The technical solution to achieve the above objectives is:

[0015] A method for preventing subway train slippage based on longitudinal load includes:

[0016] Step S1: Group the trains and assign braking force;

[0017] Step S2: Set the creep rate threshold and determine the current wheel-rail status of the train based on the creep rate;

[0018] Step S3: If the creep rate is less than the creep rate threshold, determine the current wheel-rail status of the train by longitudinal load.

[0019] Step S4: Apply the corresponding braking force according to the current wheel-rail condition of the train.

[0020] Preferably, step S1 includes:

[0021] Step S11: Divide the subway train cars into three groups, namely A, B and C. Group A is located at the front of the train in the direction of travel, group C is located at the rear of the train in the direction of travel, and group B is located between A and C.

[0022] Step S12: Install a longitudinal load sensor α between train section A and train group B, and install a longitudinal load sensor β between train group B and train group C; wherein, the longitudinal load can be divided into impact force and traction force, the impact force is the force of mutual compression between train groups, and the traction force is the force of mutual stretching between train groups.

[0023] Step S13: During braking, train group B uses braking force equal to the system command, train group A uses braking force slightly greater than the system command, and train group C uses braking force slightly less than the system command.

[0024] Preferably, in step S2, the creep rate threshold is set to 20%. When the creep rate increases to the point where the wheel and rail completely lose adhesion and the wheel completely slips, the adhesion coefficient gradually decreases as the creep rate continues to increase. At this time, the longitudinal load between the train sets is relatively small. By setting the creep rate threshold, it is determined whether the train wheel and rail are in a slipping state. If the creep rate exceeds the creep rate threshold, it is determined that the train wheel and rail are in a slipping state.

[0025] Preferably, step S3 includes:

[0026] Step S31: When the creep rate is less than the creep rate threshold, the adhesion coefficient-creep rate curve is divided into two parts, an upward region and a downward region, through the peak point. The left side is the upward region and the right side is the downward region.

[0027] Step S32: If both longitudinal load sensor α and longitudinal load sensor β measure impact force after low-pass filtering, the train is in the rising region of the adhesion coefficient-creep rate curve, and the train wheel and rail are determined to be in normal condition.

[0028] Step S33: If the longitudinal load sensor α measures traction force after low-pass filtering and the longitudinal load sensor β measures impact force after low-pass filtering, the train is in the critical region of the rise and fall of the adhesion coefficient-creep rate curve, and the train wheel and rail are determined to be in a critical state.

[0029] Step S34: If both longitudinal load sensor α and longitudinal load sensor β measure traction force after low-pass filtering, the train is in the decreasing region of the adhesion coefficient-creep rate curve, and it is determined that the train wheel and rail are in a slipping state.

[0030] Preferably, in step S32, the train is in the rising region of the adhesion coefficient-creep rate curve. The motor torque of train group A is relatively large, and the wheel-rail creep rate is also relatively large. Train group A obtains a large adhesion coefficient from the track, that is, a large braking force. At this time, the creep rates of each train group are ranked as S A >S B >S C The adhesion coefficients obtained from each train group are sorted as μ A >μ B >μ C .

[0031] Preferably, in step S33, the train is in the critical region of the rising and falling of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and a larger wheel-rail creep rate. In the rising region of the adhesion coefficient-creep rate curve, the creep rate of train group A has exceeded the optimal creep rate, resulting in a smaller adhesion coefficient obtained from the track than that of train group B, which has a smaller creep rate. At this time, the creep rates of each train group are ranked as S A >S B >S C The adhesion coefficients obtained from each train group are sorted as μ B >μ A ≈μ C .

[0032] Preferably, in step S34, the train is in the decreasing region of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and a larger wheel-rail creep rate. The creep rate of train group A has exceeded the optimal creep rate, resulting in an adhesion coefficient obtained from the track that is smaller than that of train group B, which has a smaller creep rate. At this time, the creep rates of each train group are ranked as S A >S B >S C The adhesion coefficients obtained from each train group are sorted as μ. C >μ B >μ A .

[0033] Preferably, step S4 includes:

[0034] Step S41: If the current train is in a normal state, the electric motor torque applied by the train can be increased or decreased as needed.

[0035] Step S42: If the current train is in a critical state, the braking force obtained by the train at this time is the maximum friction force that the current track can provide. The motor torque applied by the train cannot be increased, but can be reduced as needed.

[0036] Step S43: If the current train is in a slipping state, the electric motor torque applied by the train should be reduced immediately until the train enters a critical state in order to obtain the maximum friction force that the current track can provide.

[0037] The beneficial effects of this invention are as follows: By grouping trains and applying different braking forces to different groups of carriages within the same subway train, and measuring the longitudinal load between groups, this invention can determine in real time whether the train's braking force has reached the maximum friction force that the track can provide. This allows the train's braking force to be controlled at the maximum friction force that the track can provide, enabling timely stop commands to increase braking force and prevent train slippage. This invention is adaptable to all environmental types, including dry, humid, sandblasted, and oil-sprayed environments. It eliminates the need for additional sensors for external environmental factors, reducing subway operating costs. Attached Figure Description

[0038] Figure 1 This is a flowchart of a subway train slippage prevention method based on longitudinal load according to the present invention;

[0039] Figure 2 This is a flowchart illustrating the specific process of grouping trains and allocating braking force in this invention.

[0040] Figure 3 This is a flowchart illustrating the process of determining the current train wheel-rail status by longitudinal load when the creep rate is less than the creep rate threshold in this invention.

[0041] Figure 4 This is a flowchart illustrating the specific process of implementing corresponding braking forces based on the current wheel-rail condition of the train in this invention.

[0042] Figure 5 This is a graph showing the relationship between the rail surface adhesion coefficient and the creep rate in this invention;

[0043] Figure 6 This is a schematic diagram of the subway train car grouping and the installation of the longitudinal load sensor in this invention;

[0044] Figure 7 This is a graph showing the relationship between the rail surface adhesion coefficient and the creep rate after setting the creep rate threshold in this invention;

[0045] Figure 8 This is a schematic diagram of the adhesion coefficient-creep rate curve in this invention, which is divided into rising and falling regions by the peak point;

[0046] Figure 9This is a schematic diagram of the adhesion coefficient-creep rate curve of the train under normal conditions in this invention;

[0047] Figure 10 This is a schematic diagram of the adhesion coefficient-creep rate curve of the train under critical conditions in this invention;

[0048] Figure 11 This is a schematic diagram of the adhesion coefficient-creep rate curve of the train in a slipping scenario in this invention. Detailed Implementation

[0049] The technical solution of the present invention will now be clearly and completely described in conjunction with the accompanying drawings. In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0050] The invention will now be further described with reference to the accompanying drawings.

[0051] Based on wheel-rail adhesion theory and engineering practice, the relationship between the rail surface adhesion coefficient and creep rate is as follows: Figure 5 As shown, regardless of whether the rail surface is dry, wet, or of other types, the trends of the adhesion coefficient and creep rate curves are the same: as the creep rate increases, the adhesion coefficient first rises to a peak point and then decreases. If the creep rate continues to increase and exceeds a certain point, the wheel and rail will completely lose adhesion, and the wheel will completely slip. After the wheel and rail have completely slipped, further increases in the creep rate will only lead to a slow decrease in the adhesion coefficient.

[0052] like Figure 1 As shown, a method for preventing subway train slippage based on longitudinal load includes:

[0053] Step S1: Group the trains and assign braking force.

[0054] like Figure 2 As shown, step S1 includes:

[0055] Step S11: Divide the subway train cars into three groups, namely groups A, B, and C, as follows: Figure 6 As shown, train group A is located at the front of the train in the direction of travel, train group C is located at the rear of the train in the direction of travel, and train group B is located between A and C.

[0056] Step S12: Install a longitudinal load sensor α between train section A and train group B, and install a longitudinal load sensor β between train group B and train group C; wherein, the longitudinal load can be divided into impact force and traction force. The impact force is the force that squeezes between train groups, and the traction force is the force that stretches between train groups.

[0057] Step S13: During braking, train group B uses braking force equal to the system command, train group A uses braking force slightly greater than the system command, and train group C uses braking force slightly less than the system command.

[0058] Step S2: Set the creep rate threshold and determine the current wheel-rail status of the train based on the creep rate.

[0059] like Figure 7 As shown, the creep rate threshold is set to 20%. When the creep rate increases to the point where the wheel and rail completely lose adhesion and the wheel completely slips, the adhesion coefficient decreases gradually as the creep rate continues to increase. At this time, the longitudinal load between the train sets is relatively small. By setting the creep rate threshold, it is determined whether the train wheel and rail are in a slipping state. If the creep rate exceeds the creep rate threshold, it is determined that the train wheel and rail are in a slipping state.

[0060] Step S3: If the creep rate is less than the creep rate threshold, determine the current wheel-rail status of the train by longitudinal load.

[0061] like Figure 3 As shown, step S3 includes:

[0062] Step S31: When the creep rate is less than the creep rate threshold, the adhesion coefficient-creep rate curve is divided into two parts, an upward region and a downward region, through the peak point. The left side is the upward region and the right side is the downward region.

[0063] like Figure 8 As shown, the peak point corresponds to the maximum adhesion coefficient and optimal creep rate of the current rail surface environment. When the train runs near the peak point, it can utilize the maximum friction force provided by the track. Dividing the area from the peak point, the left side is the rising region and the right side is the falling region. When the train runs in the rising region, as the system commands the motor to increase the braking torque, the creep rate between the wheel and rail increases, and the braking force provided by the rail surface also increases. In this region, the system braking command and the rail surface friction force are positively correlated, and the train will not experience slippage. However, if the system continues to command the motor to increase the braking torque, the wheel-rail adhesion state will cross the peak point and enter the falling region. As the creep rate increases, the braking force provided by the rail surface will decrease. In this region, the system braking command and the rail surface friction force are negatively correlated. As the train system braking command increases, the wheel and rail will gradually become unstable and slip until they lock up completely, seriously affecting driving safety.

[0064] Step S32: If both longitudinal load sensor α and longitudinal load sensor β measure impact force after low-pass filtering, the train is in the rising region of the adhesion coefficient-creep rate curve, and the train wheel and rail are determined to be in normal condition.

[0065] like Figure 9 As shown, under good track surface conditions, the maximum frictional force that the track can provide is higher than the system's desired braking force. The train is in the rising region of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and a larger wheel-rail creep rate. Train group A obtains a larger adhesion coefficient from the track, i.e., a larger braking force. At this time, the creep rates of each train group are ranked as S. A >S B >S C The adhesion coefficients obtained from each train group are sorted as μ A >μ B >μ C .

[0066] When both longitudinal load sensor α and longitudinal load sensor β measure traction force, it could also be μ. C <μ B ,μ B >μ A ,μ B -μ C >>μ B -μ A In this scenario, although train group A has passed the peak point, the overall creep rate of the train is still some distance from the peak point, and this scenario is also considered a normal state.

[0067] Step S33: If the longitudinal load sensor α measures traction force after low-pass filtering, and the longitudinal load sensor β measures impact force after low-pass filtering, the train is in the critical region of the rise and fall of the adhesion coefficient-creep rate curve, and the train wheel and rail are determined to be in a critical state.

[0068] like Figure 10 As shown, under critical conditions of the rail surface environment, the maximum frictional force that the track can provide is approximately equal to the system's desired braking force. The train as a whole will run at the peak point, and the train is in the critical region of the rising and falling of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and its wheel-rail creep rate is also larger. In the rising region of the adhesion coefficient-creep rate curve, the creep rate of train group A has exceeded the optimal creep rate, resulting in its adhesion coefficient obtained from the track being smaller than that of train group B, which has a smaller creep rate. At this time, the creep rates of each train group are ranked as S. A >S B >S C The adhesion coefficients obtained from each train group are sorted as μB >μ A ≈μ C .

[0069] Step S34: If both longitudinal load sensor α and longitudinal load sensor β measure traction force after low-pass filtering, the train is in the decreasing region of the adhesion coefficient-creep rate curve, and it is determined that the train wheel and rail are in a slipping state.

[0070] like Figure 11 As shown, under harsh track surface conditions, the maximum friction force provided by the track is less than the system's desired braking force. This leads to a creep rate greater than the optimal creep rate under the system's desired commanded motor torque. The train is in the descending region of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and a larger wheel-rail creep rate. Train group A's creep rate has exceeded the optimal creep rate, resulting in a smaller adhesion coefficient obtained from the track compared to train group B, which has a smaller creep rate. At this point, the creep rates of the various train groups are ranked as S. A >S B >S C The adhesion coefficients obtained from each train group are sorted as μ. C >μ B >μA.

[0071] When both longitudinal load sensor α and longitudinal load sensor β measure traction force, it could also be μ. C <μ B ,μ B >μ A ,μ B -μ C <<μ B -μ A In this scenario, although train group C has not exceeded the peak point, the overall creep rate of the train has exceeded the peak point by a significant margin, and this scenario is also judged as a slipping state.

[0072] Step S4: Apply the corresponding braking force according to the current wheel-rail condition of the train.

[0073] like Figure 4 As shown, step S4 includes:

[0074] Step S41: If the train is in a normal state, the electric motor torque applied by the train can be increased or decreased as needed.

[0075] Step S42: If the current train is in a critical state, the braking force obtained by the train at this time is the maximum friction force that the current track can provide. The motor torque applied by the train cannot be increased, but can be reduced as needed.

[0076] Step S43: If the current train is in a slipping state, the electric motor torque applied by the train should be reduced immediately until the train enters a critical state in order to obtain the maximum friction force that the current track can provide.

[0077] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for preventing subway train slippage based on longitudinal load, characterized in that, include: Step S1: Group the trains and assign braking force; Step S2: By setting a creep rate threshold, it is determined whether the train wheel and rail are in a slipping state. If the creep rate exceeds the creep rate threshold, it is determined that the train wheel and rail are in a slipping state. Step S3: If the creep rate is less than the creep rate threshold, determine the current wheel-rail status of the train by longitudinal load. Step S4: Apply the corresponding braking force according to the current wheel-rail condition of the train; Step S1 includes: Step S11: Divide the subway train cars into three groups, namely A, B and C. Group A is located at the front of the train in the direction of travel, group C is located at the rear of the train in the direction of travel, and group B is located between A and C. Step S12: Install a longitudinal load sensor α between train section A and train group B, and install a longitudinal load sensor β between train group B and train group C; wherein, the longitudinal load can be divided into impact force and traction force, the impact force is the force of mutual compression between train groups, and the traction force is the force of mutual stretching between train groups. Step S13: During braking, train group B uses braking force equal to the system command, train group A uses braking force slightly greater than the system command, and train group C uses braking force slightly less than the system command. Step S3 includes: Step S31: When the creep rate is less than the creep rate threshold, the adhesion coefficient-creep rate curve is divided into two parts, an upward region and a downward region, through the peak point. The left side is the upward region and the right side is the downward region. Step S32: If both longitudinal load sensor α and longitudinal load sensor β measure impact force after low-pass filtering, the train is in the rising region of the adhesion coefficient-creep rate curve, and the train wheel and rail are determined to be in normal condition. Step S33: If the longitudinal load sensor α measures traction force after low-pass filtering, and the longitudinal load sensor β measures impact force after low-pass filtering, the train is in the critical region of the rise and fall of the adhesion coefficient-creep rate curve, and the train wheel and rail are determined to be in a critical state. Step S34: If both longitudinal load sensor α and longitudinal load sensor β measure traction force after low-pass filtering, the train is in the decreasing region of the adhesion coefficient-creep rate curve, and it is determined that the train wheel and rail are in a slipping state.

2. The method for preventing subway train slippage based on longitudinal load according to claim 1, characterized in that, In step S2, the creep rate threshold is set to 20%. When the creep rate increases to the point where the wheel and rail will completely lose adhesion and the wheel will completely slip, the creep rate continues to increase and the adhesion coefficient decreases gradually. At this time, the longitudinal load between the train sets is relatively small.

3. The method for preventing subway train slippage based on longitudinal load according to claim 1, characterized in that, In step S32, the train is in the rising region of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and a larger wheel-rail creep rate. Train group A obtains a larger adhesion coefficient from the track, i.e., a larger braking force. At this time, the creep rates of each train group are ranked as S A > S B > S C The adhesion coefficients obtained from each train group are sorted as μ A >μ B >μ C .

4. The method for preventing subway train slippage based on longitudinal load according to claim 1, characterized in that, In step S33, the train is in the critical region of the rising and falling of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and a larger wheel-rail creep rate. In the rising region of the adhesion coefficient-creep rate curve, the creep rate of train group A has exceeded the optimal creep rate, resulting in a smaller adhesion coefficient obtained from the track than that of train group B, which has a smaller creep rate. At this point, the creep rates of each train group are ranked as S. A > S B > S C The adhesion coefficients obtained from each train group are sorted as μ B >μ A ≈μ C .

5. The method for preventing subway train slippage based on longitudinal load according to claim 1, characterized in that, In step S34, the train is in the decreasing region of the adhesion coefficient-creep rate curve. Train group A has a larger motor torque and a larger wheel-rail creep rate. The creep rate of train group A has exceeded the optimal creep rate, resulting in an adhesion coefficient obtained from the track that is actually smaller than that of train group B, which has a smaller creep rate. At this point, the creep rates of the various train groups are ranked as S. A > S B > S C The adhesion coefficients obtained from each train group are sorted by μ. C >μ B >μ A .

6. The method for preventing subway train slippage based on longitudinal load according to claim 1, characterized in that, Step S4 includes: Step S41: If the current train is in a normal state, the electric motor torque applied by the train can be increased or decreased as needed. Step S42: If the current train is in a critical state, the braking force obtained by the train at this time is the maximum friction force that the current track can provide. The motor torque applied by the train cannot be increased, but can be reduced as needed. Step S43: If the current train is in a slipping state, the electric motor torque applied by the train should be reduced immediately until the train enters a critical state in order to obtain the maximum friction force that the current track can provide.

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