Stall detection
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Welcome to the 10th chapter in the TI Precision Lab series on stepper motors. My name is Pablo Armet, and today I will discuss the fundamentals of stall detection.
Let's begin by discussing what is stall and what the main causes of stall are in a motor system. A stall condition occurs when the load torque on the motor exceeds the motor pull-out torque. The pull-out out torque is the maximum torque that the motor can produce at a given speed before the rotor becomes out of sync with the magnetic field.
When the rotor becomes out of sync with the magnetic field, the motor will stall. Motor manufacturers will provide torque or pull-out curves similar to the one shown here. This curve shows the motors pull-out torque for a range of speeds.
The pull-out curve profile will be different from motor to motor. Designers use this curve to ensure that the motor's torque capability can meet the mechanical torque requirement of the system. The pull-out torque decreases as the speed increases. It is also proportional to the mode of current. So the pull-out torque curve will be specified for a particular mode of current.
There are many ways that a motor can experience a stall event. Some of these causes include, physical jamming in the rotor, overloading the motor, and any physical obstructions, such as a fixed mechanical stop that prevents the motor from spinning. The need for sensor-less stall detection is due to the lack of feedback in open-loop motor systems, which can make it difficult for the system to know if the motor has stalled.
Stall detection allows the system to work in a closed loop operation, making it possible for the system to determine if the motor is spinning. Additionally, stall detection can be helpful for applications or required sensing when the motor has reached end-of-line or a fixed mechanical stop.
Furthermore, stall detection can reduce potential mechanical failures and audible noise that can occur if the motor continues to be driven through an obstacle. Sensor-less stall detection can replace expensive motor position modules like Hall sensors and encoders.
Examples of applications that can benefit from stall detection include, ATMs, surveillance cameras, automatic headlight leveling and swivel systems, and industrial textile machines.
Many motor systems use precision encoders to monitor the rotor movement and detect stall. The encoder as shown in this animation is an optical encoder.
An optical encoder has two different patterns of alternating opaque and transparent segments. When the LED emits light onto the rotor plate, the photo detector will only capture the light passing into the transparent segments on the plate. Then, as the rotor plate begins to rotate, the photo detector output generates square wave pulses. These pulses correspond to the route of movement. By monitoring both the number of pulses and the relative phase of signals A and B, it is possible to track both the position and direction of rotation.
The indexer pulse, which is generated one time for every revolution helps the controller determine the absolute position of the encoder. Depending on the encoder resolution and the chosen step mode-- either full-step or macro stepping-- the number of encoder outputs for each input step interval will be different.
Under normal driving conditions, the number of encoder outputs per step signal should remain constant. However, if the encoder accounts per step or less than the expected counts, the motor might be experiencing a stall event.
While an encoder can monitor position and detect stall, it adds an extra component to the system, which can increase the overall system cost and size. In some cases, the system only needs stall detection, but not position sensing. When this is the case, many designers will sense the motor's back-emf to detect stall in order to eliminate the cost of an encoder.
The back-emf is the voltage induced by the rotor's magnetic field moving past the starter coils. The back-emf in a stepper motor can be expressed as a form of expression where p is the number of pole pairs, Si m is the motor's maximum magnetic flux, and omega is the motor's angular speed. p and Si m will be constants and specific to each motor. Therefore, the back-emf will be seen as solo in nature and directly proportional to the motor speed.
To better visualize this, let's take a look at the back-emf wave form of a stepper motor for two different speeds. At 200 RPM, the back-emf amplitude is 3.95 volts and its frequency is 181 Hertz.
As the speed is increased by a factor of 4 to 800 RPM, the back-emf amplitude increases to 17.2 volts, which is almost four times larger than the back-emf amplitude at 200 RPM. The frequency also increases by a factor of four to 683 Hertz, as expected.
When the motor stall, the back-emf goes to 0 volts since the motor speed is zero RPM in a stall condition. Therefore, a drop of back-emf is a good indication that the motor is stalling.
A benefit of sensor-less stall detection solutions is that it can be implemented without any sensors, eliminating the need for any additional external components and reducing the design cost and system size.
A fundamental limit on the performance of back-emf stall detection methods is the minimum back-emf voltage they can detect. This corresponds to a minimum motor speed for the algorithm to properly detect a stall condition. The minimum speed for successful back-emf stall detection will change for various motors, depending on the number of pulse and the maximum magnetic flux.
Sensor-less back-emf stall detection solutions can either be implemented by directly or indirectly measuring the back-emf as described in the following slides.
TI implement a direct back-emf measuring scheme where the back-emf is measured and sampled during the zero current step to detect a stall condition.
The DRV8711 uses this solution for its stall detection algorithm. The following animation will demonstrate how the algorithm functions. Once the motor is running and the winding current approaches the zero current step, once out of the edge bridge, is placed on high repeating state in the opposite side to low side fit. It's turned on for a brief amount of time. Also known as a back-emf simple threshold.
This allows the current to quickly decay to the low side fet and the body diode of the opposite high side fet. Then, the bulk-emf is sampled on the high-Z output at the end of the back-emf simple threshold. During normal motor operation, the simple back-emf should be greater than zero. However, simple back-emf should decrease to zero when the motor stalls.
Since the back-emf is only monitor during the zero current step, this method will not work when the stepper motor is running in full-step mode. The reason is because in full-step mode, the coil current switches between positive and negative maximum current set by the user and does not approach a zero current step. Therefore, the back-emf measurement cannot be made.
Indirect back-emf measurement utilizes the relationship between the winding current, back-emf, and the mechanical torque load of the motor to detect a stall condition. As shown in the figure, the back-emf is 90 degrees out of phase with the winding current for an unloaded motor. The back-emf phase shift will start to decrease as the load increases. Finally, as the load approaches the motor's pull-out torque at a given winding current, the back-emf will move in phase with the winding current.
When the load work exceeds the pull-out torque, the motor stalls and the back-emf goes to 0 volts. But being able to detect the back-emf phase shift between rising and falling quadrants of the motor current, it is possible to detect a motor stall condition or end-of-line travel.
This stall detection solution estimates the back-emf phase shift by constantly monitoring the effect of the back-emf on the current regulation wave form. The current regulation wave form is observed in both rising and falling quadrants to estimate the back-emf phase shift between both quadrants and determine if the motor is unloaded, fully loaded, or has reached a stall condition.
The constant current regulation way for monitoring allows the algorithm to work for all micro step settings, including full-step, which is an advantage that indirect back-emf measurement has over direct back-emf measurement.
However, a drawback of this solution is that the current regulation wave form can have heavy dependencies on supply voltage, motor current, motor resistance, which can make it difficult to properly monitor the back-emf.
The following slide will show how TI implements this solution for it's stall detection algorithm and how it overcomes its drawbacks. TI implements a fixed current ripple algorithm to detect stall. This stall detection algorithm monitors the back-emf phase shift between rising and falling quadrants by measuring the PWM off time for both quadrants to determine if the motor is stalling.
Measuring, typically in off time eliminates any dependencies on supply voltage, as the supply voltage is disconnected during the off time. The T of time also gives a good indication on how much back-emf is present. Usually, the more back-emf present, the longer the T of time will be.
This algorithm uses the delta of the T of reciprocal between the rising and falling quadrants to estimate the change in back-emf. During normal motor operation, there will be more back-emf present in the falling quadrant than in the rising quadrant due to the back-emf EMF being out of phase with the current.
Therefore, the change in back-emf should be positive and greater than zero when the motor is not stalling. As the motor approaches a fully loaded condition, the back-emf will become in phase with the current. This causes the back-emf to evenly balance out between both quadrants.
As the motor fully stalls, the back-emf disappears completely. In the case of fully loaded, in stall conditions, the T of time would be the same in both quadrants. The algorithm can detect a stall condition when the change in T of time equals to zero, which also means that the change in back-emf is also zero, since the motor inductance and current ripple are constants.
To look at a device which implements this stall detection algorithm, search for the DRV8889-Q1 on the TI.com website.
Detecting when a motor stalls, or reaches a fixed mechanical stop, or end-of-line travel can greatly benefit many industrial and automotive systems. Stall detection helps prevent potential mechanical failures that can occur when a motor is over driven past an obstacle.
In this presentation I have discussed three methods for detecting a stall condition on a motor. This table summarizes the advantages and disadvantages of the three stall detection methods.
The encoder method can precisely monitor the motor position and can work at very low speeds if the encoder resolution is high enough. However, using an encoder will increase the system cost and size. Direct and indirect back-emf measurement methods are both sensor-less solutions, which help reduce design cost and system size. Both methods also require a minimum motor running speed in order to properly detect a stall condition.
The indirect back-emf measurement method will be able to detect stall for all macro-step settings, including full-step. On the other hand, the direct back-emf measurement method will now work in full-step.
The indirect back-emf method will not work properly if there are large supply voltage, motor current, and motor resistance variations. However, there are many ways to minimize the effect of those parameters when detecting stall. For example, TI solves this issue by measuring the current regulation PWM off time to determine if motor has stalled. For more information on stepper motors and TI- integrated stepper drivers, please visit the stepper travel page on TI. Com.
This video is part of a series
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Precision labs series: Stepper motors
video-playlist (10 videos)