JP5673938B2 - Electric vehicle control device - Google Patents

Description

  The present invention relates to an electric vehicle control device for realizing re-adhesion control for effective use of adhesive force for an inverter-controlled electric locomotive.

An electric vehicle, for example, a train, is accelerated and decelerated by a tangential force (also referred to as adhesive force) between wheels and rails. This tangential force generally has characteristics as shown in FIG. 18 with respect to the sliding speed. ing. FIG. 18 shows the tangential force (tangential force coefficient) with respect to the sliding speed, the horizontal axis is the sliding speed, the vertical axis is the tangential force (tangential force coefficient), the solid line is when the rail surface is wet, and the broken line is the rail surface. It shows the time of drying. The tangential force divided by the axial weight (vertical load applied to the rail per axle) is called the tangential force coefficient, and the maximum value of the tangential force coefficient is called the adhesion coefficient.
As shown in the figure, when torque that does not exceed the maximum value of the tangential force is generated by the main motor, idling / sliding does not occur, and the electric vehicle has a small sliding speed on the left side of the maximum value of the tangential force. Will travel. If a torque larger than the maximum value is generated, the sliding speed increases and the tangential force decreases, so the slipping speed increases and the slipping and sliding state increases, but the wheels and rails are generated by the main motor when the wheels and rails are dry. Since the performance of the vehicle is set so that the torque does not exceed the maximum value of the tangential force, idling / sliding does not occur.

However, as shown by the solid line, when the rail surface is wet due to rain or the like, the adhesion coefficient decreases, and the maximum value of the tangential force becomes smaller than the generated torque of the main motor corresponding to the set performance of the vehicle.
In this case, the slip speed increases and the vehicle is idled or slid. If left as it is, the tangential force decreases correspondingly, and the acceleration / deceleration force required to accelerate / decelerate the vehicle further decreases. Therefore, it is necessary to detect slipping / sliding and reduce the torque generated by the main motor to re-adhere. When re-adhesion is performed by controlling the torque in this way, control is performed so that the torque generated by the main motor is as close to the maximum value of the tangential force as possible while maintaining a low sliding speed. Effective utilization is necessary to improve the acceleration / deceleration performance of an electric vehicle.

As a method for realizing such re-adhesion control, the rotational speed of the main motor is estimated from the voltage / current applied to the main motor, and the estimated speed information and the calculated value of the main motor generated torque are used as input information. The main motor torque corresponding to the tangential force between the wheels and rails is estimated for each control cycle using the minimum dimension disturbance observer, and the generated torque of the main motor is controlled using the estimated torque at the time of idling / sliding detection Has been proposed (see Patent Document 1 and Non-Patent Document 1).
With this control method, it is possible to maintain the generated torque of the main motor as close to the maximum value of the tangential force as possible, that is, close to the adhesion limit value, while maintaining a good riding comfort.

However, the above control is realized because the acceleration / deceleration of the vehicle is kept almost constant even if the passenger's boarding rate fluctuates. It is.
On the other hand, for electric locomotives where it is highly necessary to increase the traction mass as much as possible, that is, for electric locomotives that require more effective use of adhesive force than trains, a single main motor is used like an inverter controlled electric locomotive. Even if the main circuit configuration can be controlled independently by a single inverter, the minimum value of the moving wheel speed in one electric locomotive is set as the reference speed based on the moving wheel speed calculated from the speed sensor. Since the method of detecting slipping according to the speed difference from the moving wheel speed is generally used, the slipping detection is delayed. Therefore, even when using vector control with a speed sensor with high torque response, the tangential force of the idling wheel has a slip speed / tangential force coefficient characteristic that decreases rapidly when the slip speed increases slightly. (Electric locomotives have a higher adhesion coefficient than trains, so if slipping occurs, the amount of decrease from the adhesion coefficient of the tangential force coefficient at the same sliding speed as the train is large). The driving wheel cannot be re-adhered unless the torque command value that defines the torque to be reduced is greatly reduced. From this point, the problem that the adhesive force cannot be effectively used can be mentioned first. In addition, after the point of re-adhesion, in general, control is performed to rapidly increase the torque command value of the main motor to the torque equivalent to the adhesive force immediately before idling from the viewpoint of effective use of the adhesive force. As the traction force (adhesive force) of each wheel changes rapidly, dynamic fluctuations in axle load within the same truck and dynamic fluctuations in axle load between trucks occur. For the reason that it becomes difficult to generate, there is a problem that effective use of adhesive force is not achieved.

In order to improve such a current situation, the rotational speed of the main motor described in Patent Document 1 (or Non-Patent Document 1) described above is estimated from the voltage / current applied to the main motor, and the estimated speed Information and the calculated value of the generated torque of the main motor are used as input information, and the main motor torque corresponding to the tangential force between the wheels and rails is estimated for each control cycle using the minimum dimensional disturbance observer, and estimation at the time of idling / sliding detection When the torque control method used to control the torque generated by the main motor (speed sensorless vector control method / re-adhesion control method combined with disturbance observer estimation) is applied to an inverter-controlled electric locomotive as is, Such a problem occurs.
When the above speed sensorless vector control is used, the estimated delay of the estimated wheel axis acceleration is small, so if the threshold can be set appropriately, the idle rotation can be detected quickly by the wheel axis acceleration. Therefore, the adhesive force can be effectively used. However, unlike the case of trains, when towing a freight train with an electric locomotive, the towing mass varies greatly depending on the train, ranging from operating with one locomotive to the towing of a freight train with the maximum towing mass. Therefore, even when the same traction force is generated in the locomotive, the acceleration of the train changes greatly. If this traction mass is known before the start of locomotive travel, it is possible to appropriately set the threshold for idling detection by axial acceleration, but in practice means to know the traction mass before the start of locomotive travel Therefore, an appropriate threshold cannot be set as it is.
In the case of a locomotive-driven freight train, since various operating conditions are assumed, it is possible that the starting acceleration of the train is extremely smaller than in the case of a train. Therefore, it seems that it is quite difficult to accelerate the train stably.

Japanese Patent Laid-Open No. 11-252716 JP 58-215992 A JP-A-8-196100

Satoshi Kadowaki, Tadashi Hata, Hiroshi Hirose, Kiyoshi Oishi, Satoshi Iida, Masashi Takagi, Takashi Sano, Shinobu Hoshikawa: “Application of Speed Sensorless Vector Control / Disturbance Observer to Real Vehicle and its Evaluation-205 Series 5000 Examples of trains-", IEEJ Transactions D, Volume 124, September 2004, pp 909-915 Okuyama, Fujimoto, Matsui, Kubota: "Speed / Voltage Sensorless Vector Control Method for Induction Motors", IEEJ Transactions D, 107, February 1987, pp. 191-198 Kondo, Yuki: “Examination of application of induction motor speed sensorless vector control to railway vehicle drive”, IEEJ Transactions D, 125, 2005 (January 2005), pp1-8 Kanehara and Koyama: "Speed sensorless vector control method for induction motors including low speed and regenerative regions", IEEJ Transactions D, Volume 120, February 2000, pp 223-229 Sano: "Sensorless speed control system for traffic", Toyo Denki Technical Report, No. 109, 2003 (2003) -11, pp14-23

As described above, even in the case of electric locomotive tow trains, the effective use of the adhesive force realized in the train is re-adhesive using both the speed sensorless vector control method and the tangential force estimation by the disturbance observer as in the case of the train. It is desirable to realize this using a control method.
However, at present, as described above, no means has been found for appropriately setting the threshold value for detecting slipping by the wheel axle acceleration.

  The present invention has been devised in view of the above points, and the object of the present invention is to provide a traction force generated by the locomotive when the electric locomotive traction train departs from the yard and shifts to a state in which the train is accelerated. And a means for estimating a towed mass from train acceleration data, and setting an appropriate threshold for detecting slipping (by the wheel axle acceleration) based on the estimated towed mass. And when starting the train, it is stably started by the vector control with speed sensor, and after the time when the train speed becomes higher than the switching speed, the vector control with speed sensor is based on the voltage and current of the main motor from the time of starting the train. Similarly, the control moves to the speed sensorless vector control that started the control operation, and the re-adhesion control that uses the speed sensorless vector control method and the tangential force estimation by the disturbance observer using the threshold value of the idling detection based on the wheel axle acceleration set in this way. It is an object to provide an electric vehicle control device capable of performing acceleration control of an electric locomotive tow train that effectively uses adhesive force.

In order to solve the above-described problems, the present invention provides a vector controller with a speed sensor that vector-controls the main motor based on speed information from a speed sensor attached to the main motor of the inverter-controlled electric locomotive, A speed sensorless vector controller that vector-controls the main motor based on the estimated speed calculated from the voltage and current of the main motor,
When starting from the stop state of the vehicle, the vector controller with speed sensor is started and accelerated based on the speed information of the main motor, and the inverter-controlled electric locomotive is started and accelerated by the vector controller with speed sensor. The speed sensorless vector controller is operated simultaneously with acceleration,
After the speed of the inverter-controlled electric locomotive reaches the switching speed, the electric vehicle control device controls acceleration of the main motor by the speed sensorless vector controller,
A speed calculator for idling detection that computes a speed used for idling detection from the estimated speed of the main motor estimated by the speed sensorless vector controller and the speed information from the speed sensor until the switching speed is reached;
A traction mass estimator for calculating an estimated traction mass from an average acceleration and an average traction force of the inverter control electric locomotive during a predetermined period after the inverter control electric locomotive shifts from zero speed to start acceleration control; ,
A threshold of idling detection using the wheel axle acceleration when the main motor is accelerated by the speed sensorless vector control function from the estimated estimated traction mass (that is, the locomotive exhibits the maximum traction force from the estimated estimated traction mass) The speed / acceleration characteristics of the train when accelerating the vehicle, and the idling detection threshold value set by adding this to the idling detection threshold setting constant, hereinafter referred to as the idling detection threshold value by the wheel axle acceleration a threshold calculator for setting the say),
The speed used for the idling detection is regarded as each wheel speed, the minimum value of the wheel speed is set as a reference speed, and the difference speed of each wheel speed with respect to the reference speed and the threshold obtained by the threshold calculator are used. For an inverter-controlled electric locomotive equipped with an idling detector that detects idling and having a speed sensorless vector control function and a speed sensorless vector control function, acceleration control is performed by vector control with a speed sensor until the switching speed is reached from speed zero. In parallel with this, the speed sensorless vector control function is also operated from zero speed, the estimated speed is calculated from the voltage and current of the main motor, and it is used for slip detection by the differential speed from the speed obtained from the speed sensor and the estimated speed. The speed is calculated, and the speed used for the idling detection is regarded as each wheel speed, and this wheel speed is reached until the switching speed is reached. The minimum value is set as the reference speed, and acceleration control is performed while detecting idling based on the difference speed of each wheel speed with respect to this reference speed and the idling detection threshold based on the difference speed, and during a certain period during this acceleration control. Estimate the traction mass from the average acceleration and the average traction force of the locomotive. Based on this estimated traction mass, set the threshold for idling detection based on the wheel axle acceleration, and shift to speed sensorless vector control when the train speed exceeds the switching speed. After that, idling detection is performed based on the set threshold value for idling detection and the driving wheel shaft acceleration calculated by the speed sensorless vector controller. The power is used effectively.

That is, in the present invention, the above problem is solved as follows.
For an inverter-controlled electric locomotive having a vector control function with a speed sensor and a speed sensorless vector control function, acceleration control is performed by the vector control with the speed sensor until the switching speed is reached from the speed zero. The speed sensorless vector control function is also operated to calculate the estimated speed from the voltage and current of the main motor, and the speed used for slip detection by the difference speed is calculated from the speed obtained from the speed sensor and the estimated speed. The speed used in the above is regarded as each wheel speed, and the minimum value among the wheel speeds is set as the reference speed, and the acceleration control is performed while detecting the idling based on the difference speed of each wheel speed with respect to the reference speed.
Then, during the acceleration control of the main motor, the traction mass is estimated by any one of the following methods (1) to (4), and the threshold value of the idling detection by the wheel axle acceleration detection is set based on the estimated traction mass. Set, after the train speed reaches the switching speed, it shifts to speed sensorless vector control, performs idling detection by the threshold value set in this way and the driving wheel shaft acceleration calculated by the speed sensorless vector controller, Train acceleration control is performed while performing re-adhesion control in combination with speed sensorless vector control method and tangential force estimation by disturbance observer.
(1) After the inverter-controlled electric locomotive shifts from the zero speed to the start acceleration control, the inverter-controlled electric locomotive is detected from the average acceleration and the average traction force of the inverter-controlled electric locomotive during a certain period from the preset time. Estimate the traction mass.
(2) When the first idling is detected in each driving wheel, the traction mass is estimated from the average acceleration and the average traction force of the inverter locomotive during a period that is a certain time after the first idling detection time.
(3) From the time when start acceleration is started by instructing a set torque command value τc that is as large as possible within a range in which each driving wheel of the inverter-controlled electric locomotive does not idle, during a certain period from the preset time The traction mass of the inverter-controlled electric locomotive is estimated from the average acceleration of the inverter-controlled electric locomotive and the torque command value τc.
(4) After generating and starting a traction force greater than the starting resistance of the entire train when the maximum traction mass assumed in the inverter-controlled electric locomotive is towed, the inverter-controlled electric locomotive After the time when the time change of the acceleration of the inverter controlled electric locomotive calculated from the respective wheel speeds falls below a set level, the inverter controlled electric is performed by the method described in (1), (2) or (3) above. Estimate the traction mass of the locomotive.

  In the present invention, as described above, the start acceleration of the train from the zero speed is performed by the vector controller with a speed sensor, and the speed sensorless vector controller is also operated simultaneously with the start of the start by the vector controller with the speed sensor. The estimated speed is calculated by the speed sensorless vector controller from the voltage and current of the motor, the speed used for slip detection by the differential speed is calculated from the speed obtained from the speed sensor and the estimated speed, and the speed used for the slip detection is calculated for each driving wheel. It is regarded as a speed, the minimum value of the wheel speed is set as the reference speed, acceleration control is performed while detecting idling based on the difference speed of each wheel speed with respect to this reference speed and the idling detection threshold based on the difference speed, and the switching speed The traction mass is derived from the average traction force and average acceleration of the inverter-controlled electric locomotive during a certain period until the train speed reaches Estimated by the estimator, set the threshold for idling detection by the wheel axle acceleration based on this estimated mass, and after the train speed exceeds the switching speed, shift to speed sensorless vector control by the speed sensorless vector controller Since the idling detection based on the wheel axle acceleration is performed using the set idling detection threshold, the following effects can be obtained.

(1) When the train speed is less than or equal to the switching speed, the speed used for idling detection is calculated from the speed obtained from the speed sensor and the estimated speed obtained by speed sensorless vector control, and the speed used for idling detection is calculated as each wheel speed. Therefore, acceleration control is performed while the minimum value of the moving wheel speed is set as a reference speed and idling detection is performed based on the difference speed of each moving wheel speed with respect to the reference speed.
Thus, when the train speed is less than or equal to the switching speed, the estimated speed is calculated by speed sensorless vector control, and this estimated speed is the speed information of the estimated delay that is much smaller than the speed measurement delay obtained from the speed sensor. Therefore, the idling detection can be performed more quickly than the idling detection based on the differential speed using only the speed from the speed sensor.
In particular, since the influence of the estimated speed on the speed used for idling detection increases as the speed increases, idling detection can be performed more quickly than idling detection based on the differential speed using only the speed from the speed sensor. In addition, since the sliding speed of the moving wheel at the time of idling is reduced, the adhesive force can be effectively used correspondingly.

(2) If the train speed exceeds the switching speed, the control shifts to speed sensorless vector control, and using the threshold value of idling detection by the driving wheel axis acceleration obtained based on the estimated mass as described above, the driving wheel axis acceleration is determined. Therefore, it is possible to estimate the motor torque corresponding to the tangential force coefficient estimated by the rapid idling detection and the disturbance observer with a small estimated delay. Since adhesion control is possible, it is possible to realize a high utilization rate of adhesive force.
Further, by performing the re-adhesion control after the idling detection using this estimated torque, as described in Non-Patent Document 1, a large fluctuation of the torque command value does not occur, and therefore, the torque command value is controlled. There is almost no dynamic change in axle load within the same truck or between trucks. For this reason, it is possible to generate an adhesive force close to the adhesive coefficient of each moving shaft, and from this point, the adhesive force can be effectively used.
(3) By estimating the traction mass from the average traction force or torque command value of the electric locomotive and the average acceleration, the traction mass can be estimated appropriately. The detection threshold can be set to an appropriate value.
(4) In the present invention, two types of control functions are used: a vector control function with a speed sensor and a vector control function with a speed sensor. The vector control function with a speed sensor uses software that implements a speed sensorless vector control function. This can be realized by changing / adding a part. Therefore, it is possible to realize two types of control functions, that is, a vector control function with a speed sensor and a vector control function without a speed sensor, with a common control apparatus, without complicating the apparatus configuration compared to the conventional one. The present invention can be realized.

It is a figure which shows the traction mass estimation method in 1st Example of this invention. It is a figure which shows the traction mass estimation method in 2nd Example of this invention. It is a figure which shows the traction mass estimation method in the 3rd Example of this invention. It is a figure which shows the traction mass estimation method in the 4th Example of this invention. It is a block diagram which shows schematic structure of the electric vehicle control apparatus of this invention. It is a block diagram which shows operation | movement of the speed calculator for idling detection. It is a figure which shows the coefficient for speed calculation used for idling detection. It is a flowchart (1) showing operation | movement of the traction mass estimator (A) in 1st Example of this invention. It is a flowchart (2) showing operation | movement of the traction mass estimator (A) in 1st Example of this invention. It is a flowchart showing operation | movement of the traction mass estimator (B) in 2nd Example of this invention. It is a flowchart showing operation | movement of the traction mass estimator (C) in the 3rd Example of this invention. It is a flowchart showing operation | movement of the traction mass estimator (D) in the 4th Example of this invention. It is a block diagram which shows operation | movement of the threshold value calculator of the idling detection by a driving wheel shaft acceleration. It is a block diagram which shows operation | movement of a reference speed calculator. It is a flowchart showing operation | movement of a slipping detector. It is a figure which shows the threshold value of the idling | spinning detection by a driving wheel shaft acceleration computed from the estimated pulling mass. It is a figure which shows the control method of the torque command value in the adhesion control which used speed sensorless vector control system and the tangential force estimation by a disturbance observer together. It is a figure which shows the general characteristic with respect to the sliding speed of a tangential force coefficient (or tangential force).

  The present invention has an electric vehicle control device for an inverter-controlled electric locomotive having a vector controller with a speed sensor and a speed sensorless vector controller. In parallel with this, the speed sensorless vector controller is also operated from zero speed to calculate the estimated speed from the voltage and current of the main motor, and the speed difference obtained from the speed and estimated speed obtained from the speed sensor Calculates the speed used for idling detection, regards the speed used for idling detection as each wheel speed, sets the minimum value of this wheel speed as the reference speed, and detects idling by the difference speed of each wheel speed with respect to this reference speed. The traction mass is estimated from the average acceleration and the average traction force of the locomotive during a certain period during the acceleration control. After setting the slip detection threshold based on the pulling mass and moving to the speed sensorless vector control when the train speed exceeds the switching speed, use the set slip detection threshold. By detecting idling by acceleration, re-adhesion control is quickly performed while the sliding speed is small so as to effectively use the adhesive force.

Examples of the present invention will be described below. In the following description, each symbol is used in the following meaning.
Fav1 to Fav4: Driving wheel first axis to fourth axis average traction force,
Slip1 to Slip4: Driving wheel first axis to fourth axis idling detection signal,
T _a1 : Average traction force calculation start time (Example 1),
T _b1 : Average tractive force calculation end time (Example 1),
Favj: First the average tractive force in the period ΔT1 further back from the timing predated idling detection time T ₀₂ from time δT idling sensed wheel j,
Slipj: idling detection signal of driving wheel j
δT: Time when the driving wheel j is assumed to start idling (set value)
ΔT1: Average tractive force calculation period (Example 1), α _b1 : locomotive average acceleration V _a1 : locomotive speed at time T _a1 , V _b1 : locomotive speed at time T _b1 ,
V (t): locomotive speed, α (t): locomotive acceleration,
T _a2 : Average traction force calculation start time (Example 2), T _b2 : Average traction force calculation end time (Example 2),
ΔT2: Average traction force calculation period (Example 2),
α _b2 : locomotive average acceleration corresponding to the average traction force,
V _a2 : locomotive speed at time T _a2 , V _b2 : locomotive speed at time T _b2 ,
T _end : Traction mass estimation operation upper limit time, T _a3 : Operation mode start time for tractive mass estimation,
T _b3 : Operation mode end time for estimating the traction mass,
ΔT3: period of operation mode for traction mass estimation,
α _b3 : the average acceleration of the locomotive corresponding to the period of the driving mode for towing mass estimation,
V _a3 : locomotive speed at time T _a3 , V _b3 : locomotive speed at time T _b3 ,
T _z : The last time to continue to command a traction force that is larger than the starting resistance of the entire train when the maximum traction mass is assumed,
PG: speed sensor, Pulse: speed pulse, Slipz: idling detection signal,
V _ref : reference speed, V _pg : speed calculated based on speed pulse by vector controller CA with speed sensor V _cmbj : idling detection speed, V _est : estimated speed, V _ch : switching speed α ^ _d : estimated Driving wheel axis acceleration,
α _slip : slipping detection threshold value due to wheel axle acceleration ΔV _slip : slipping detection threshold value V ^* : three-phase voltage command, V _u : u-phase voltage, V _v : v-phase voltage, i _u : u-phase current, i _v : v-phase current V _cmbj : other wheel speed, T _cmdi : torque command value of other wheel, M _estj : estimated traction mass,
k _est : a coefficient at which the value is zero at zero speed, increases linearly as the speed increases, and becomes 1 when the switching speed V _ch is reached,
k _pg : a value of 1 at zero speed, a coefficient that decreases as a linear function as the speed increases and reaches zero when the switching speed V _ch is reached,
α _z : Train acceleration of estimated tractive mass when locomotive exerts maximum tractive force,
δτ: Decrease amount of torque command value after idling detection,
τ _est : Estimated torque corresponding to the tangential force when slipping is detected,
τ _a : The minimum value of the torque command value for re-adhering the driving wheel, and selected to be as large as possible within the range where it can be reliably re-adhered.
T1: period for commanding τ _a , T2: period for commanding τ _c ,
τ _c : Torque commanded after re-adhesion,
v: voltage, i ₁ : primary current, R ₁ : primary resistance, t: time,
L ₁ : primary self-inductance, L ₂ : secondary self-inductance, M: mutual inductance ω ^ _s : slip angular velocity, ω ^: secondary magnetic flux angular velocity, ω ^ _m : motor angular velocity Ψ _2v : voltage model secondary magnetic flux, Ψ _2vα : α component of voltage model secondary magnetic flux,
Ψ _2vβ : β component of voltage model secondary magnetic flux,
i _1α : α component of primary current, i _1β : β component of primary current

FIG. 1 is a diagram showing a traction mass estimation method in a first embodiment of the present invention, FIG. 5 is a block diagram showing a schematic configuration of an electric vehicle control device of the present invention, and FIG. 6 is an operation of a speed calculator for idling detection. FIG. 7 is a diagram showing speed calculation coefficients used for idling detection, and FIGS. 8 and 9 are flowcharts showing the operation of the traction mass estimator (A) in the first embodiment of the present invention.
FIG. 13 is a block diagram showing the operation of the threshold calculator for idling detection by the wheel axle acceleration, FIG. 14 is a block diagram showing the operation of the reference speed calculator, and FIG. 15 is a flowchart showing the operation of the idling detector.
FIG. 16 is a diagram showing a threshold for idling detection based on the driving wheel shaft acceleration calculated from the estimated traction mass. The horizontal axis represents the speed, the vertical axis represents the maximum traction force characteristic of the locomotive, and the idling by the axis acceleration obtained from the estimated traction mass. The detection thresholds (A, B) and the acceleration of the estimated tractive mass train when the locomotive exerts the maximum tractive force are shown.
FIG. 17 is a diagram showing a torque command value control method in the adhesion control in which the velocity sensorless vector control method is combined with tangential force estimation by a disturbance observer. The horizontal axis represents time, and FIG. 5A shows the torque command value so that τ _a is maximized within _a range where it can be re- _adhered from the estimated torque τ _est corresponding to the tangential force at the time of idling detection. In addition, the torque command value is set so that the torque τ _c commanded after re-adhesion is as close as possible to the estimated torque τ _est . FIG. 5B shows the moving wheel speed, and FIG. 5C shows the idling detection signal.

Hereinafter, the first embodiment will be described based on FIGS. 1, 5, 6, 7, 8, 9, and 13 to 17. FIG.
FIG. 1 is a diagram showing a traction force estimation method in the first embodiment of the present invention, in which the horizontal axis is time, and FIGS. 1A and 1B are traction forces of the first to fourth shaft driving wheels. The average traction force of the first axis to the fourth axis, the idling detection signal of the first axis to the fourth axis are shown, (c) and (d) show the sliding speed of the driving wheels of the first axis to the fourth axis, and (e) Is the locomotive speed, and (f) is the locomotive acceleration and average acceleration.
FIG. 5 is a diagram showing a schematic configuration of the electric vehicle control device of the present invention.
In FIG. 5, 1 is a main motor that drives an electric vehicle, 2 is a speed sensor that detects the speed of the main motor, 3 is a PWM inverter that drives the main motor 1, and the electric vehicle control device of this embodiment is As shown in the figure, a vector controller CA with speed sensor and a speed sensorless vector controller CB for controlling the PWM inverter are provided.
In FIG. 5, 4 is a torque command value generator for generating a torque command value corresponding to the notch command, 5 is a speed V _PG calculated by the vector controller CA with a speed sensor, and a speed sensorless vector controller CB. The idling detection speed calculator for calculating the idling detection speed V _cmbj of the j-axis driving wheel from the estimated speed V _est estimated in step 5, and 6 is the idling detection speed V _cmbj , the reference speed V _ref , and idling by the driving wheel axis acceleration. slipping detector for outputting idling detection signal Slipz receives the threshold alpha _slip detection, 7 calculates what the lowest rate in the other driving wheel speed V _Cmbi inputted idling sensing velocity V _Cmbj A reference speed calculator 8 for outputting as a reference speed V _ref ; 8 a calculator for calculating an idle detection threshold value based on an axial acceleration, which is obtained by calculating an estimated slip detection threshold value α _slip based on a moving wheel shaft acceleration upon receiving an estimated traction mass; Is the locomotive This is a traction mass estimator that estimates the traction mass to be _pulled and outputs it as an estimated traction mass M _estj .

In the vector controller CA with a speed sensor, for example, the main motor 1 is controlled using a method described in Patent Document 2 known in the art. In order to obtain from the speed sensor 2 speed information having a sufficiently small temporal variation component that can be used for main motor control, for example, a time interval of about 25 (ms) is required, and a detection delay is a speed used for idling detection. Although it is large, when the train is started in a state where it is stopped in the climb slope section, sometimes the train starts from a state where the train is retreated at a low speed, but even in that case, stable slope start can be realized.
On the other hand, as the speed sensorless vector control system used in the speed sensorless vector controller CB, the system described in Non-Patent Document 2 to Non-Patent Document 4 and Non-Patent Document 1 (or Non-Patent Document 5 or Patent Document 3) are described. Can be considered.

Among these, in the case of the method described in Non-Patent Document 2, a speed regulator (ASR) using proportional / integral control so that the estimated speed (ω ^ _r ) follows the speed command value (ω _r ^* ). The current regulator (ACR1) using proportional / integral control so that the q-axis current (i _1q ) follows the q-axis current value [torque current] command value (i _1q ^* ) obtained as a result. It is controlled by. In this process, the estimated speed (ω ^ _r ) is calculated. That is, since integral control is used in the process of calculating the estimated speed (ω ^ _r ), the speed estimation is delayed by the integral control.
In the case of the method described in Non-Patent Document 3, integral control is used in the calculation formula for the estimated speed, and the speed estimation is also delayed by the integral control.
Further, in the case of the method described in Non-Patent Document 4, speed estimation using an adaptive magnetic flux observer is performed, but integral control is used therein, and a delay occurs in speed estimation as well.

As described above, in any of the methods described in Non-Patent Document 2 to Non-Patent Document 4, it is apparent that there is a delay in speed estimation. In this way, in the method in which there is a delay in the speed estimation, there is a frequent occurrence of an event in which the idling / sliding speed increases rapidly, or the idling / sliding wheels rapidly re-adhere, as in the re-adhesion control. In a possible application example, since the follow-up of the estimated speed is delayed, the follow-up delay also occurs in the generated torque, and there is a high possibility that the improvement of the re-adhesion control performance by using the speed sensorless vector control cannot be expected.
On the other hand, in the method described in Non-Patent Document 1 (or Non-Patent Document 5 or Patent Document 3), the speed estimation delay is only one control cycle (about 100 μs or less).

The reason is as follows.
In the speed sensorless vector control described in Non-Patent Document 1 (or Non-Patent Document 5 or Patent Document 3), the speed of the induction motor is calculated from the input voltage v and current i of the induction motor according to the following equations (1) to (4). Estimate ω ^ _m .

・ ・ ・ ・ ・ ・ ・ (1)
(2)
.... (3)
.... (4)

here,
Ψ _2v : voltage model secondary magnetic flux, v: voltage, i ₁ : primary current, R ₁ : primary resistance, t: time, L1, L2, M: primary self inductance, secondary self inductance, mutual inductance, ω ^ _s : slip angular velocity,
ω ^: 2-order magnetic flux angular velocity, ω ^ _m: motor angular _velocity, Ψ 2vα, Ψ 2vβ: α component of the voltage model secondary magnetic flux, β _{component, i 1α, · i 1α:} α component of the primary current, β component

That is, the voltage model secondary magnetic flux is calculated by the equation (1), and the slip angular velocity ω ^ _s is calculated from the equation (2). Further, as shown in the equation (3), the phase angle of the voltage model secondary magnetic flux Ψ _2v is time-differentiated to obtain the secondary magnetic flux angular velocity ω ^ _s . Then, the angular velocity ω ^ _{m of the} motor is obtained by subtracting the slip angular velocity ω ^ _s from the secondary magnetic flux angular velocity ω ^ according to the equation (4). Since the slip angular velocity ω ^ _s obtained by the equation (2) is highly likely to include various control errors, the slip angular velocity command value ω _s ^* uniquely determined is actually used.

As can be understood from these equations, since the speed can be estimated from the instantaneous value of the current, the speed estimation delay is only one control period (about 100 μs or less), and the speed information with sufficiently small temporal fluctuation component is almost ignored. It can be obtained with as little delay as possible.
That is, in the speed sensorless vector control used in this embodiment, the secondary magnetic flux angular velocity rotation ω ^ is obtained from the α component and β component of the voltage model secondary magnetic flux, and the slip angular velocity command value ω _s ^* is obtained as the slip angular velocity ω. as ^ _s, from the secondary magnetic flux angular velocity rotation omega ^ slip angular velocity omega ^ _s subtracted and seeking motor angular velocity omega ^ _m, by obtaining the motor angular velocity omega ^ _m in this manner, the estimated speed with a small delay Can be obtained.
Therefore, even if the idling / sliding speed increases rapidly during re-adhesion control or the event that the idling / sliding wheel rapidly re-adheres, the follow-up of the estimated speed will not be delayed. High-speed response characteristics can be maintained. Therefore, the improvement of the re-adhesion control performance can be expected as compared with the vector control with speed sensor.
Also, with regard to the driving wheel shaft acceleration obtained as a speed difference, stable acceleration information with sufficiently small temporal fluctuation components can be obtained with a delay shorter than a detection delay for obtaining stable speed information using a speed sensor. it can. Good control performance is obtained in the idling re-adhesion control by the speed sensorless vector control / disturbance observer described in Non-Patent Document 1 described above. This is due to the fact that it can be detected and that an appropriate torque control can be performed using an estimated value of the tangential force with a small estimated delay at the time of slipping detection. Therefore, even in the case of an electric locomotive towing freight train, if the towing mass can be estimated appropriately, the threshold for idling detection based on the wheel axle acceleration can be set to an appropriate value, and re-adhesion with a high adhesive force utilization rate due to rapid idling detection. Control performance may be obtained.

For the reasons described above, the speed sensorless vector controller CB controls the main motor using the speed sensorless vector control described in Non-Patent Document 1 (or Non-Patent Document 5 or Patent Document 3).
In the speed sensorless vector control, there is a possibility that the frequency once becomes zero during the control of the inverter frequency in the situation where the train is started from a state where the train is retreated at a low speed as described above. In principle, when the inverter frequency becomes zero, that is, when the inverter becomes DC, information on the speed from the rotor of the main motor cannot be obtained. Therefore, it is necessary to accelerate through the zero frequency using a predictive control method. When towing a freight train whose acceleration may be extremely low, it can be considered that it is quite difficult to accelerate the train stably only by speed sensorless vector control.
Therefore, after the main motor is controlled using vector control with a speed sensor in the extremely low speed region, and after passing through the extremely low speed region, the speed described in Non-Patent Document 1 (or Non-Patent Document 5 or Patent Document 3). If control that shifts to sensorless vector control is performed, there is a high possibility that re-adhesion control performance with a high utilization rate of adhesive force by rapid idling detection will be obtained.

Although FIG. 5 shows a configuration example in which the vector controller with speed sensor CA and the speed sensorless vector controller CB are separately provided, the speed calculated based on the information from the speed sensor as the motor angular speed ω ^ _m is shown. If the configuration of the vector control with speed sensor for obtaining the secondary magnetic flux angular velocity ω ^ from the relationship of the above equation (4) is applied, the function of vector control with speed sensor can be built around the speed sensorless vector control function. Since the amount of software for vector control can be reduced, a configuration example in which the functions of the vector controller with speed sensor CA and the speed sensorless vector controller CB are configured by a single vector controller can be considered.
The speed sensor-equipped vector controller CA and the speed sensorless vector controller CB in the present invention are as described above.

  In FIG. 5, a notch command issued from a master controller (not shown) operated by the engineer is input to the torque command value generator 4. In response to the notch command, the torque command value generator 4 generates a torque command value and outputs it to the speed sensor-equipped vector controller CA and the speed sensorless vector controller CB. Further, since it is necessary for estimating the traction mass in another electric vehicle control device, a torque command value corresponding to the notch command is transmitted to the other electric vehicle control device. From the PWM inverter 3, a voltage for two phases (in FIG. 5, a u-phase voltage and a v-phase voltage) and a current (a u-phase current and a v-phase current) are input to the speed sensorless vector controller CB, and the speed sensor. A speed pulse from a speed sensor 2 attached to the main motor 1 is input to the attached vector controller CA.

The vector controller CA with speed sensor calculates the speed V _pg based on the speed pulse Pulse from the speed sensor 2 and generates a three-phase voltage command V ^* to generate torque according to the input torque command value. Output to the PWM inverter. In the PWM inverter 3 to which the three-phase voltage command V ^* is input, a voltage according to the voltage command is generated and applied to the main motor 1 to generate a torque according to the torque command value to rotate the main motor 1. The locomotive begins to accelerate. The speed sensorless vector controller CB to which the torque command value is input from the torque command value generator 4 starts operating simultaneously with the start of acceleration of the locomotive by the operation of the vector controller CA with speed sensor. A three-phase voltage command is generated in the same manner as the vector controller CA with a speed sensor so as to generate a torque according to the torque command value based on the estimated speed V _est by estimating and calculating the speed from the voltage / current of 1. However, if the speed of the locomotive is less than switching speed V _ch, the voltage command switcher SW1 for the output from the speed sensor-less vector controller CB vector control switching command remains off, SW2 in FIG As shown, SW1 is on, SW2 is off, and the three-phase voltage command generated by the speed sensorless vector controller CB is not input to the PWM inverter 3.

Therefore, the locomotive is accelerated under the control of the vector controller CA with speed sensor until the switching speed V _ch is reached. Incidentally, if the estimated speed V _est calculated by the speed sensorless vector controller CB becomes switching speed V _ch or more, the speed sensorless vector control unit CB has a voltage command switcher SW1, SW2 and turns on the vector control switching command SW1 is turned off, SW2 is turned on, the three-phase voltage command from the vector controller CA with speed sensor that has been input to the PWM inverter 3 until then is released, and the three-phase voltage from the speed sensorless vector controller CB is released. The command is input to the PWM inverter 3. Thereafter, the speed sensorless vector controller CB calculates the estimated speed V _est from the output voltage / current of the PWM inverter 3, and uses this speed to generate a torque according to the input torque command value. A voltage command V ^* is generated and output to the PWM inverter 3. Further, the speed sensorless vector controller CB outputs the estimated moving wheel shaft acceleration α ^ _d calculated based on the estimated speed V _est to the idling detector 6.

The speed V _PG calculated by the vector controller CA with speed sensor and the estimated speed V _est calculated by the speed sensorless vector controller CB are both input to the idling speed detecting calculator 5. The idling detection speed V _cmb calculator 5 calculates the idling detection speed V _cmbj of the j-axis driving wheel from the input speed V _PG and the estimated speed V _{est according} to the following equation (5).

V _cmbj = V _est × k _est + V _pg × k _pg (5)
The configuration of the idling detection speed calculator 5 is shown in FIG. As shown in the figure, the idling speed calculator 5 includes a first function generator 21 that outputs a coefficient k _pg , a second function generator 22 that outputs a coefficient k _est , 2 multipliers Mp1 and Mp2 and an adder A1. The speed V _PG calculated by the input vector controller CA with speed sensor and the coefficient k _pg are multiplied by the multiplier Mp1, and the input estimated speed V _est and the coefficient k _est are multiplied by the multiplier Mp1. Then, the sum is obtained by the adder A1 and output as the idling detection speed V _cmbj .
Here, as shown in FIG. 7, the coefficient k _est has a value of zero at zero speed, increases in a linear function as the speed increases, and becomes 1 when the switching speed V _ch is reached. Become. Similarly, as shown in FIG. 7, k _pg has a value of 1 at zero speed, and decreases to a linear function as the speed increases and becomes zero when the switching speed V _ch is reached.
Therefore, since the speed V _pg is dominant near zero speed, the delay for calculating the idling detection speed V _cmb is large, but the influence of the speed V _pg on the calculation of the idling detection speed V _{cmbj as} the speed increases. The speed decreases, the influence of the estimated speed V _{est with} a small estimated delay becomes dominant, the calculation delay of the idling detection speed V _cmbj decreases, and when the switching speed V _ch is reached, the idling detection speed The calculation delay of V _cmb is the same as the estimated speed V _est, and the idling detection speed V _cmbj is calculated with a small calculation delay.

The slipping detection speed V _cmbj calculated in this way is _output to the slipping detector 6, the reference speed calculator 7 and the traction mass estimator 9. In addition, since the idling speed V _{cmbj of the} j-axis driving wheel is necessary for estimating the traction mass also in other electric vehicle control devices, it is also output to the other electric vehicle control devices.
The traction mass estimator 9 estimates the traction mass pulled by the locomotive by the method described later using the idling detection speed V _cmbj, and uses this as the estimated traction mass M _{estj to} detect the idling detection by the wheel axle acceleration. Output for. The threshold calculator for idling detection based on the driving wheel axis acceleration that has received the estimated traction mass calculates the idling detection threshold value α _slip based on the driving wheel axis acceleration by the method described later, and outputs this to the idling detector 6.
_Further , in the reference speed calculator 7 that has received the idling detection speed V _cmbj , as shown in FIG. 14, the other moving wheel speed V _cmbi (where i is a value from 1 to the number of _moving wheels Nd). , I ≠ j), and the lowest value of the idling speed V _cmbj for the idling detection is calculated by the minimum value computing unit 24 and this is used as the reference speed _Vref for the idling detector 6. Output.

The idling detector 6 that has received the idling detection speed V _cmbj , the reference speed V _ref , and the idling detection threshold value α _slip based on the driving wheel shaft acceleration operates as shown in the flowchart of FIG. 15. First, in step S101, a comparison between the idling detection speed V _cmbj and the switching speed V _ch is performed. If V _cmbj <V _ch , vector control with a speed sensor is in progress, so the process goes to step S102. In step S102, The difference speed between the idling detection speed V _cmbj and the reference speed V _ref is calculated. If this difference speed is the difference speed ≧ ΔV _slip with respect to the slippage detection threshold ΔV _{slip due} to the difference speed, it is in the slip detection state due to the difference speed, so the process goes to step S103 and the slip detection signal Slipz Is turned on and output to the torque command value generator 4.
On the other hand, if the differential speed <ΔV _slip, the process goes to step S104 to turn off the idling detection signal Slipz and output it to the torque command value generator 4.
In step S101, if V _cmbj ≧ V _ch , the speed sensorless vector control is being performed, so the process goes to step S105, where the magnitude of the estimated driving wheel axis acceleration α ^ _d and the threshold value α _slip for detecting slipping by the driving wheel axis acceleration is larger or smaller. Comparison is made, and when α ^ _d ≥ α _slip , the idling state is detected by the driving wheel shaft acceleration, so the process goes to step S103 to turn on the idling detection signal Slipz and output it to the torque command value generator. If α ^ _d <α _slip , it is not the idling detection state due to the driving wheel shaft acceleration, so the process goes to step S104 to turn off the idling detection signal Slipz and output it to the torque command value generator 4.

The torque command value generator 4 outputs a torque command value corresponding to the notch command when the idling detection signal Slipz is off. When the idling detection signal Slipz is turned on and the occurrence of idling is detected, the torque command value is controlled as shown in FIG. 17 so that the idling wheels are re-adhered.
That is, the torque on the main motor shaft corresponding to the tangential force between the wheel and the rail is always estimated by the minimum dimension disturbance observer as described in Patent Document 1 and Non-Patent Document 1, and slipping is detected. In this case, _a command is issued during the re-adhesion period so that the torque reduction amount δτ (= τ _est −τ _a ) is as small as possible from the estimated torque τ _est corresponding to the tangential force at the time of idling detection. setting the torque command value tau _a for. Then, the torque command value τa is commanded for _a certain period T1 to re-adhere the driving wheel. When the period T1 elapses, the torque τ _c slightly smaller than the estimated torque τ _est corresponding to the tangential force at the time of idling is detected. In a short time, and this torque command value is held for the period T2. The reason why the torque τ _c slightly smaller than the estimated torque τ _est is commanded in this way is to avoid the occurrence of re-spinning immediately when τ _c is commanded. Then, even if the torque τ _c is commanded only during the period T2, the torque command value is gradually increased if there is no re-spinning. When re- idling eventually occurs, the same control as the torque command value control when the idling is detected is repeated.

In the electric vehicle control apparatus shown in FIG. 5 that operates as described above, the estimation of the traction mass in the first embodiment is performed as shown in FIGS.
FIG. 1 shows an example of an inverter locomotive in which the number of moving wheels _Nd is 4 axes. However, the number of moving wheels is not limited to 4 axes, and 6 axes, 8 axes, and the like are also assumed. .
As shown in FIG. 1, the average traction force Favi of each driving wheel is obtained from the torque command value of each driving wheel for a period ΔT1 from time T _a1 to time T _b1 set in advance. Here, i = 1 to 4.
In the case of FIG. 1, since the idling of each driving wheel occurred during the period ΔT1, the average traction force F _avi obtained from the torque command value does not _accurately reflect the tangential force between the wheels and the rails. Since there is no difference, it is different from the actual average traction force, but if it can be re-adhered during a minute idling, it can be considered that even if the average traction force is calculated from the torque command value, a large error is not included.
Details of the control operation will be described with reference to FIGS. In FIG. 8, it is determined whether the locomotive is immediately after the start of acceleration control in step S101. If it is immediately after the start of control, the process goes to step S102 to reset the average traction force Favk of all the driving wheels (k = 1,... , J,... Nd). Further, the estimated traction mass M _estj calculated on the j axis is also reset.

Next, in step S103, the average acceleration α _b1 (t) of the driving wheel j-axis and the average value calculation counter (representing the number of acceleration data used for average acceleration calculation) are reset. Then, the process goes to step S104. Note that if the result of determination in step S101 is not immediately after the start of acceleration control, the locomotive goes directly to step S104.
In step S104, V _cmbj input from the idling detection speed V _cmb calculator is _set to the locomotive speed V (t). Next, in step S105, from the locomotive speed V _-1 (t) one control cycle (δTc) ago and the current locomotive speed V (t), the locomotive acceleration α (t) is calculated as {V (t ) −V ₋₁ (t)} / δTc.
In step S106, it is determined whether or not the elapsed time t from the start of control is equal to or longer than the first set time _Ta1 shown in FIG. 1, and has not yet reached the first set time _Ta1. If so, return and wait for the next control cycle.

If it is not less than the first set time _Ta1, it is determined in step S107 whether or not the first set time _Ta1 has just been reached. If it has just become, the locomotive speed V is determined in step S108. (T) is set to V _a1 . Here, V _a1 is first speed data for calculating the average acceleration of the locomotive from the speed data, as shown in FIG. Then, the process proceeds to step S109, and the torque command value T _cmdk is converted into traction force and added for the average traction force Favk of all the driving wheels (k = 1,..., J,... Nd). Also, the locomotive acceleration α (t) is added to the average acceleration α _b1 (t). Next, in step S110, 1 is added to the average value calculation counter _Mcount and the process returns to wait for the next control cycle.
If it is determined in step S107 that the first set time _Ta1 has not just been reached, the condition determination in step S111 is performed, and the elapsed time t from the start of control is the second setting shown in FIG. If it is not the time T _a2 or more, go to step S109 described above. If the elapsed time t is the second set time T _a2 or goes to step S112, if the elapsed time t is not immediately after it becomes the second set time T _a2 (already estimated traction mass M _Estj is obtained ) waits for the next control cycle in return, set the elapsed time t is go to the step S113, if it is immediately after became the second of the set time t _a2, the speed of the locomotive V (t) to V _a2 To do.

In step S114, the average acceleration α _b1 (t) obtained by dividing the average acceleration α _b1 (t) by M _count representing the number of data is set. Alternatively, (V _a1 −V _a2 ) / ΔT1 is set to the average acceleration α _b1 (t) using the speed data V _a1 and V _a2 . In step S115 of FIG. 9, it sets what the Favk of each wheel divided by M _count the average traction Favk. In step S116, the average traction force F _L of the locomotive during the period ΔT1 is obtained by the following equation (6) using the average traction force Favk thus obtained.
In step S117, an average acceleration of the locomotive during the period ΔT1 is α _b1 , and an estimated traction mass M _estj is obtained from Equation (7) (train running resistance is ignored).
In the equation (7), instead of using the average acceleration α _b1 of the locomotive during the period ΔT1, the equation (8) obtained from the locomotive speeds V _a1 and V _a1 at the times T _a1 and T _b1 is 114. An average acceleration α _av expressed by the following may be used.

.... (6)
.... (7)
(8)

When the estimated traction mass M _estj is obtained by the above-described method, as shown in FIG. 13, the estimated traction mass M _estj input to the threshold calculator for idling detection by the wheel axle acceleration and the maximum of the locomotive are obtained. From the tractive force characteristic, the calculator 23 _obtains the speed / acceleration α _Z characteristic of the train when the locomotive _having the estimated tractive mass M _estj accelerates with the maximum tractive force. Then, the adder A2 adds the idling detection threshold value setting constant Δα _mar due to the axial acceleration to this α _Z to obtain the idling detection threshold value α _slip due to the driving wheel shaft acceleration and outputs it to the idling detector. .
Here, the idling detection threshold setting constant Δα _mar has a margin in the threshold so that false detection of idling does not occur even if the train acceleration changes due to the gravitational component due to the maximum gradient of the line section where the locomotive travels. It is a constant used for holding. The threshold value α _slip obtained in this way represents the threshold value (A) for the idling detection shown in FIG. The threshold value (A) for detecting idling due to the wheel axle acceleration has a speed range that continuously changes according to the speed. However, in reality, since it is not necessary to actually change the threshold value with a slight speed change, a method of changing the threshold value for each of several speed bands as shown in the threshold value (B) shown in FIG.

In the electric vehicle control apparatus that operates as described above, the estimation of the traction mass in the second embodiment is performed as shown in FIG. A detailed flowchart of the estimation operation is shown in FIG.
FIG. 2 is a diagram showing a method of estimating the traction mass according to the present embodiment, in which the horizontal axis represents time, FIG. 2A shows the traction force of the moving wheel j first detected as idle and the idling detection signal, and FIG. (C) shows the locomotive speed, and (d) shows the locomotive acceleration and average acceleration.
2, the first wheel j at time T ₀₂ is shifted to idling detection and re-adhesion control. The average pulling force generated in the wheels j between the period ΔT2 further back from the time T ₀₂ from the time T _b2 retroactive by δT and Favj. And let Favj be the average traction force of a moving wheel that is not idling. However, i ≠ j (i = 1 to Nd, Nd: number of moving wheels of the locomotive).
Also, let the average acceleration of the locomotive during the period ΔT2 be α _b2 . Then, the average tractive force F _L of the locomotive during the period ΔT2, since given by the equation (6), the estimated traction mass M _Estj is be determined from the equation obtained by replacing the alpha _b1 of (7) to the alpha _b2 Yes (ignoring train resistance).
Incidentally, the period for calculating the average traction, to the starting point time T _b2 retroactive by δT during the period δT towing force generated by wheel there driving wheel idly state becomes smaller than the pulling force as shown in FIG. 2 This is because (a period during which the tangential force during idling cannot be accurately grasped), a more accurate traction force can be grasped by avoiding this period.

Next, a detailed estimation operation will be described with reference to FIG. First, in step S101, it is determined whether the locomotive is immediately after acceleration control. Since this condition is satisfied at the start of activation, in step S102, the average traction force Favj of the j-axis driving wheel and the average traction force Favi of driving wheels other than the j-axis are reset (i = 1,..., Nd and i ≠ j). In step S103, the idling detection speed V _cmbj is _set to the locomotive speed V (t).
If it is determined in step S101 that it is not immediately after acceleration control, the process directly proceeds to step S103. Next, in step S104, the locomotive acceleration α (t) is determined as {V (t) from the locomotive speed V ₋₁ (t) one control cycle (δTc) ago and the current locomotive speed V (t). ) −V ₋₁ (t)} / δTc. Then, at 105, it is determined whether or not the idling detection signal Slipz input from the idling detector output, that is, the idling detection signal Slipj of the j-axis driving wheel is ON.
If the idling detection signal Slipj is not on, that is, if idling has not occurred, go to the condition determination in step S107, and whether the elapsed time since activation is equal to or greater than the traction mass estimation operation upper limit time T _end shown in FIG. Check for no. When it does not reach the estimation operation limit time T _end is saved in step S108, the torque command value of the j-axis wheels T _Cmdj, the torque command value T _CMDI of i axis wheels other than the j-axis data save area SaveTcmdj, the SaveTcmdi To do. Similarly, the locomotive speed V (t) and acceleration α (t) are stored in the save areas SaveV and SaveA.

If it is determined in step S107 that the traction mass estimated operation upper limit time T _end is reached, the condition determination in step S109 is performed to check whether the estimated traction mass M _estj is in a reset state.
If it is in the reset state, that is, if the estimation calculation of M _estj has not yet been completed, the estimation calculation process of M _estj after step S110 is performed. The processing in step S110 is performed after the condition determination in step S107 and step S109 is when the tractive mass estimation operation upper limit time T _end has passed without detecting slipping once.
In step S110, the average traction force of each driving wheel is obtained from the save areas SaveTcmdj and SaveTcmdi from time T _a2 that is δT + ΔT2 backward from the current time to time T _b2 that is δT backward by the same method as described in FIGS. Favi is calculated (i = 1,... Nd). Then, it calculates the average tractive force F _L of the locomotive by (6). Next, in step S111, the average acceleration α _b2 of the locomotive is calculated from the data in the save area SaveA. The computed average acceleration alpha _av in it (9) with a locomotive speed V _b2 of the locomotive speed V _a2 and time T _b2 time T _a2. In step S112, the estimated traction mass M _estj is calculated using the average acceleration α _b2 or α _av instead of α _{b1 in} the equation (7).

If the idling detection signal Slipj is turned on in step S105, that is, if idling is detected, and if idling is detected for the first time in the determination in step S106, the process proceeds to step S110 described above, and the traction mass estimation operation is performed. If it is not the first idling detection, the estimated pulling mass M _estj has already been set, so nothing is returned.

(9)

When the estimated traction mass M _estj is obtained by the method described above, the threshold value (A) for detecting slipping by the axial acceleration or the axial acceleration is obtained by the same method as that described in the first embodiment with reference to FIGS. A threshold value (B) for detecting slipping can be obtained.

In the electric vehicle control apparatus shown in FIG. 5 that operates as described above, the traction mass in the third embodiment is estimated as shown in FIG.
FIG. 3 is a diagram showing a method for estimating the traction mass according to the present embodiment. In the present embodiment, as shown in FIG. 3, an operation mode in which as much torque as possible is generated within a range where idling is not generated in order to estimate the traction mass. , And then the operation of estimating the traction mass from the torque command value and the average acceleration of the locomotive is performed. The horizontal axis is time, and (a) in the figure shows the traction force (torque command value) of the driving wheel and idling detection. (B) shows the sliding speed of the driving wheel, (c) shows the speed of the locomotive, and (d) shows the acceleration and average acceleration of the locomotive. A detailed flowchart of the estimation operation is shown in FIG.
As shown in FIG. 3, at time T _a3 after starting, making the state where the traction mass can be estimated so as to generate during the period ΔT3 large torque tau _c as much as possible within a range which does not generate idling (i.e., traction mass Is inserted), and thereafter, the operation mode is shifted to an operation mode in which a normal torque command value is commanded.
Then, the estimated traction mass M _estj is _obtained from the torque command value τ _c and the average acceleration α _{b3 of the} locomotive during the operation mode period ΔT3 in which the traction mass can be estimated (Equation 10) _Nd ). Here, k _f is a constant for converting the torque into traction.

.... (10)

After _obtaining the estimated traction mass M _estj in this manner, the threshold for detecting slipping due to the axial acceleration can be obtained by the method described in the first embodiment.
The detailed estimation operation is shown in FIG. In FIG. 11, it is determined whether or not acceleration control has just started in step S101, and this condition is satisfied at the start of startup. Therefore, the process goes to step S102 to reset the average traction force Favj and estimated traction mass M _estj of the j-axis driving wheel. Then, control goes to a step S103. If it is not at the start of activation, the process proceeds directly to step S103. In step S103, the idling detection speed V _cmbj is _set to the locomotive speed V (t).
In step S104, the locomotive acceleration α (t) is calculated from the locomotive speed V ₋₁ (t) one control cycle (δTc) ago and the current locomotive speed V (t) by {V (t) It calculates by -V < _-1 > (t)} / (delta) Tc.

Next, in the condition determination in step S105, it is determined whether the elapsed time since the start is _{equal to} or greater than the traction mass estimation operation start time _Ta3 . If the elapsed time does not reach the traction mass estimation operation start time _Ta3 , the process returns and waits for this time to elapse. If it is equal to or greater than T _a3 , it is determined in step S106 whether the elapsed time is equal to or greater than the traction mass estimation operation end time T _b3 , and if it has not yet reached the end time T _b3 , in step S107 the locomotive speed V ( t), the locomotive acceleration α (t) is stored in the save areas SaveV and SaveA, respectively.
Operation ends when the time T _b3 becomes above goes to step S108, a judgment M _Estj of whether the reset state, when a reset state, it has not yet been calculated estimated traction mass, to step S109 migrated, locomotive acceleration data SaveA, time T from _a3 to time T _b3 data calculates the average acceleration alpha _b3 locomotive from, and the data V _a3 and time T of the time T _a3 in save area SaveV data from the data V _b3 of _b3, (9) the V _a3 instead of formula V _a2, calculates the average acceleration alpha _av3 another locomotive using V _b3 instead of V _b2. In step S110, the estimated traction mass M _estj is calculated from equation (10) or using α _av3 instead of α _b3 in equation (10).
When the estimated traction mass M _estj is obtained by the method described above, the threshold value (A) for detecting slipping by the axial acceleration or the axial acceleration is obtained by the same method as that described in the first embodiment with reference to FIGS. A threshold value (B) for detecting slipping can be obtained.

In the electric vehicle control apparatus shown in FIG. 5 that operates as described above, the traction mass in the fourth embodiment is estimated as shown in FIG.
FIG. 4 is a diagram showing a method for estimating the traction mass according to the present embodiment. In this embodiment, the traction force is larger than the starting resistance of the entire train when the estimated maximum traction mass is pulled, as shown in FIG. To the time T _z and the fluctuation of the locomotive acceleration due to the coupling gap is settled, and then the traction mass estimation operation is performed. The horizontal axis represents time, and FIG. (Torque command value) and idling detection signal, (b) shows the sliding speed of the driving wheel, (c) shows the locomotive speed, and (d) shows the locomotive acceleration and average acceleration. A detailed flowchart of the estimation operation is shown in FIG.

In general, when a freight train is towed by a locomotive, a freight train that has stopped in a state where there is a gap between the automatic coupler between the locomotive and the freight car or between the freight cars generates traction on the locomotive. As shown in FIG. 4, the acceleration of the locomotive may vibrate greatly due to the minute relative movement between the locomotive, the freight car, and the freight car (automatic connection between the locomotive and the freight car). If there is no free space between automatic units and freight cars, that is, if the entire train is stopped in a rod-like state, the locomotive acceleration will not vibrate, but such an event will occur. Probability is not high). It is necessary to prevent the calculation accuracy of the average acceleration of the locomotive from being lowered by such acceleration vibration.
Therefore, as shown in FIG. 4, a traction force larger than the starting resistance when the maximum traction mass assumed in the locomotive is to be pulled is commanded until time T _z, and the locomotive acceleration fluctuation due to the coupling gap is sufficient. To fit in. After that, the torque command value is increased in order to generate a torque corresponding to the notch command from the master controller operated by the engineer. Therefore, from this point onward, the first embodiment, the second embodiment, or the second embodiment is performed. The traction mass estimation operation is performed by the third method. FIG. 4 shows a case where the traction mass is estimated by the method of Example 2 after time T _z .

The outline of the estimation operation of the fourth embodiment is shown in the flowchart of FIG.
In FIG. 12, when the elapsed time from the activation in step S101 is equal to or less than T _z shown in FIG. 4, it is not yet the time to start the estimation operation, so return and wait for the time to elapse. When the elapsed time is equal to or greater than T _z , the conditions for performing the estimation operation are ready. Therefore, in the case of the traction mass estimator (A), the traction mass estimator (A) shown in FIGS. The traction mass is estimated by movement. In the case of the traction mass estimator (B), the traction mass is estimated by the operation of the traction mass estimator (B) shown in FIGS. In the case of the traction mass estimator (C), the traction mass is estimated by the operation of the traction mass estimator (C) shown in FIGS.
When the estimated traction mass M _estj is obtained by the method described above, the threshold value (A) for detecting slipping by the axial acceleration or the axial acceleration is obtained by the same method as that described in the first embodiment with reference to FIGS. A threshold value (B) for detecting slipping can be obtained.

1 Main motor 2 Speed sensor (PG)
3 PWM inverter 4 Torque command value generator 5 Slope detection speed calculator 6 Slope detector 7 Reference speed calculator 8 Calculator 9 that calculates the threshold of slip detection by axis acceleration Traction mass estimators 21 and 22 Function generator 23 Calculator 24 Minimum value calculator CA Vector controller with speed sensor CB Speed sensorless vector controller SW1, SW2 Voltage command switcher Mp1, Mp2 Multiplier A1, A2 Adder

Claims (4)

A vector controller with a speed sensor that vector-controls the main motor based on speed information from a speed sensor attached to the main motor of the inverter-controlled electric locomotive;
A speed sensorless vector controller that vector-controls the main motor based on the estimated speed calculated from the voltage and current of the main motor;
When starting from the stop state of the vehicle, the vector controller with speed sensor is started and accelerated based on the speed information of the main motor, and the inverter-controlled electric locomotive is started and accelerated by the vector controller with speed sensor. The speed sensorless vector controller is operated simultaneously with acceleration,
After the speed of the inverter-controlled electric locomotive reaches the switching speed, the electric vehicle control device controls acceleration of the main motor by the speed sensorless vector controller,
A speed calculator for idling detection that computes a speed used for idling detection from the estimated speed of the main motor estimated by the speed sensorless vector controller and the speed information from the speed sensor until the switching speed is reached;
A traction mass estimator for calculating an estimated traction mass from an average acceleration and an average traction force of the inverter control electric locomotive during a predetermined period after the inverter control electric locomotive shifts from zero speed to start acceleration control; ,
From the estimated estimated traction mass, find the speed / acceleration characteristics of the train when the locomotive is accelerating with the maximum traction force, and set the slip detection threshold obtained by adding this and the slip detection threshold setting constant. A threshold value calculator,
The speed used for the idling detection is regarded as each wheel speed, and until the switching speed is reached, the minimum value of the wheel speed is set as a reference speed, and the difference speed of each wheel speed with respect to the reference speed is determined. The idling detection is performed by detecting idling based on the idling detection threshold value of the wheel and detecting the idling based on the driving wheel shaft acceleration calculated by the speed sensorless vector controller and the threshold value obtained by the threshold value calculator after reaching the switching speed. An electric vehicle control device comprising: The traction mass estimator according to claim 1,
After the inverter-controlled electric locomotive shifts from zero speed to start acceleration control, when a first idling is detected in each driving wheel of the inverter-controlled electric locomotive, a period that goes back for a certain time from the first idling detection time An electric vehicle control device comprising a traction mass estimator for calculating a traction mass from an average acceleration and an average traction force of the inverter-controlled electric locomotive. The traction mass estimator according to claim 1,
From the time when starting acceleration is started by commanding a set torque command value τc that is as large as possible within a range in which each driving wheel of the inverter-controlled electric locomotive does not idle, during a past period from a preset time T0 to δT The traction mass estimator for calculating the traction mass of the inverter controlled electric locomotive from the average acceleration of the inverter controlled electric locomotive and the torque command value τc. The traction mass estimator according to claim 1, 2 or 3,
Electricity that operates after generating and starting a traction force in the inverter-controlled electric locomotive that is larger than the starting resistance of the entire train when the maximum traction mass assumed in the inverter-controlled electric locomotive is towed Car control device.