April 8, 2025 • 24 mins
Welcome to this episode of the NXP EdgeVerse Techcast! Join hosts Kyle and Bridgette as they dive into the world of motor control with expert Daniel Hou from NXP. Explore the significance of motor control in various Industrial and IoT applications, the latest advancements in the field, and how NXP’s comprehensive solutions—including the MCAT tuning tool, FreeMASTER real-time debugging tool, and Application Code Hub—help developers get their motors running efficiently.
Whether you’re a developer, engineer, or just curious about motor control technologies, this episode is packed with insights you won’t want to miss. Tune in to learn about the future of automated systems, the role of AI in predictive maintenance, and much more!
Additional resources:
MCUXpresso SDK for Motor Control | NXP Semiconductors.css-j9qmi7{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;font-weight:700;margin-bottom:1rem;margin-top:2.8rem;width:100%;-webkit-box-pack:start;-ms-flex-pack:start;-webkit-justify-content:start;justify-content:start;padding-left:5rem;}@media only screen and (max-width: 599px){.css-j9qmi7{padding-left:0;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;}}.css-j9qmi7 svg{fill:#27292D;}.css-j9qmi7 .eagfbvw0{-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;color:#27292D;}Mark as PlayedTranscript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Bridgette Stone (00:10):
Welcome everyone to the NXP EdgeVerse Techcast, where
we talk about software, tools andtechnologies that help bring NXP's,
processors and microcontrollers to life.
Whether you're deep intodevelopment or just exploring what's
possible, we've got you covered.
Kyle Dando (00:27):
Get your motor running.
Head out on the highway.
Looking for adventure.
In whatever comes our way.
Bridgette Stone (00:37):
You've clearly been waiting for this moment.
Was it everything that you dreamed of?
Kyle Dando (00:43):
Oh, come on, Bridgette.
I've been waiting my whole life just tosing SteppenWolf to a big crowd like this.
But seriously, today's topic mademe think about this popular lyric,
"Getting your motor running".
This has long been the pursuitof most of the embedded design
engineers that we work with at NXP.
Bridgette Stone (01:00):
All right, Kyle, I'll definitely give you points for creativity.
Terrible singing aside, we reallydo have a great episode lined up.
We're joined by Daniel Hou, a truemotor control expert who can actually
back up the Steppenwolf reference.
Kyle Dando (01:16):
All right.
Well Daniel, thanks for joiningus today on the TechCast.
Can you explain how youcame to be involved in all
things motor control at NXP?
Daniel Hou (01:23):
Sure.
Thanks Kyle.
By the way, great singing I'm not sureif I can totally back up that beautiful
singing, I'm the podcast today.
My name is Daniel Hou.
I'm, a product marketer from NXPwho's looking over our Industrial
and IoT applications, forMicrocontrollers and Microprocessors.
So that's your typical, I wouldsay, brain of your control system.
(01:44):
also involved in motor control.
And, motor control is oneof my focus, for my team.
Kyle Dando (01:49):
Great.
Bridgette Stone (01:50):
We're so happy to have you, Daniel.
Thanks for being here today.
And, motor control is a big dealacross so many industries, but
what does it mean in the NXP world?
Daniel Hou (02:00):
Well, in short it means a lot, but let me elaborate on that.
So basically, within the Industrialand IOT segments, NXP as a company,
we have identified several emergingapplications and market segments to
invest more technology into, becausethose are fast growing segments.
I'll give you some examples.
(02:20):
For example, Smart Factory.
Factory automation is one of themajor trend in the industry right now.
A lot of investment going on there.
Healthcare, right?
This is also a mega trend driven by thetotal health condition of the population
here and how do we make it smarter?
And then also things like SmartHome Control or Building Control.
(02:40):
So if you look at motor control asa technology is more of a horizontal
technology versus a vertical technology.
So for vertical, we're talking aboutfactories, buildings, medicals, right?
So motor control is a horizontaltechnology that has shared a lot of,
similar feature needed or similartechnology, similar platforms
(03:02):
across different vertical segments.
So that's how, motor control isreally a important, Technology
Pillar towards all the differentsegments that NXP is investing in.
Bridgette Stone (03:13):
Thanks for breaking that down, Daniel.
And as you mentioned, Motor Controlplays a role in many applications from
industrial to intelligent buildings.
Does that mean the same solutionscan scale across different use cases?
Daniel Hou (03:26):
To some extent, as a company, we provide, one of the, largest range
of processing platforms for real-timecontrol and motor control is, one of the
essence of the real-time control aspect.
If you look at our product portfolio,there is just such a breadth to it.
we just announced and, launchedthe new MCU platform called MCX.
(03:48):
Among the MCX, there are a lot of devicesthat's built for motor control, and
we also have the i.MX RT family, whichis our high performance, high speed
lane for MCUs and they also do reallywell with, high dynamic motor control.
I'm really excited about thenext product called i.MX94.
(04:10):
This is gonna be, one of the firstMicroprocessors or Application Processors
that we added to our portfolio that canactually do a real-time motor control
with this powerful real-time capability.
I'm really excited about the, productbreadth and scalability that we
provide when it comes to motor control.
And it's not only aboutthe hardware here, right?
(04:31):
If you talk about Motor Control,it's a lot of algorithms.
It's a lot of software.
So we also have a, unified offering ofsoftware tools to help our customers,
to help the users to identify,the characteristics of the motor.
To fine tune the motor, you'llhear a lot of, terms like
fine tuning or motor tuning.
This is one of the most commonlyused, terminology and, techniques in
(04:55):
terms of motor control system design.
So we have dedicated tools to help ourcustomers to fine tune the motors, to do
a real time visualized debugging, and alsodeliver a software library based on that.
So these are all unified across the wholeplatform for our Motor Control offering.
Kyle Dando (05:13):
So when I came to NXP, it's that breadth, right?
Yeah.
As you mentioned, lots of differentproducts at scale, for the complexity
of the motor controller or the motioncontrol, and then the software.
And we're gonna touch on that in a coupleother questions that we're gonna ask you.
But before we jump into that,motor control has come a long
way since, I graduated college.
In the past motor applicationswere focused more on running
(05:35):
industrial pumps and fans.
Back then, complex motion controlwas found in automation of
different manufacturing processes.
Today I've started to see more andmore advanced applications for motors.
Just this last weekend, my familyand I were out at the shopping
mall and we went to a showroom andwe saw this new, Tesla Bot called
Optimus, and it looked really scary.
(05:57):
But, it shows you these huge advancementsthat are being made in motor control.
It's much more than just the sillyRoomba that we had 10 years ago.
Daniel Hou (06:06):
Exactly.
Yep.
Kyle Dando (06:06):
So Daniel, what's driving this evolution in motor control
and where do you see it going next?
Daniel Hou (06:12):
Yeah, and you're exactly on point, Kyle, you mentioned Roomba
and you used the silly Roomba nowadays.
So back then we were thinkingRoomba is a very advanced mobile
robotic application, right?
Now it becomes more basic.
So this is what we are seeingin the industry as well.
So it becomes more, highlydynamic control systems.
You are seeing more and moreautonomous systems in our industry now.
(06:35):
Not only limited to factory today.
if you go to your home, there isautonomous systems everywhere.
There is some autonomous systemthat involves more basic motor
controls like pumps, but there aremore, that involves robotics today.
We're talking about evenlike the, the co-bot.
That's another concept to the robotwhere it basically work collaboratively
(06:57):
with a human, by the side.
So all kinds of trend and allkinds of advancement in terms of
robotic applications in there.
And when it comes to robotic, there's alsoanother concept that's kind of, people
kind of get confused sometimes with MotorControl, which is called Motion Control.
So Motion Control is more of adifferent or a higher level of
(07:19):
control on top of Motor Control.
If you think about motorcontrol, it's controlling the
precise spinning of one motor.
And motion control is about coordinationtypically for several motors.
If you look at an example will be arobotic arm in the factory, right?
It has multiple axis and you need tocoordinate all those different motors that
(07:39):
control different axis and to actuallyachieve a motion at the end of the day.
So that's motion control.
And frankly speaking, we're seeinga blend of involvement in terms
of both Motor Control and MotionControl in the industry today.
Kyle Dando (07:53):
Okay.
Well that's interesting.
I don't think I've thought of it asmuch about Motion Control as I've always
thought of Motor Control, so that's great.
So with motion control, is this openingthe door for these more advanced
applications, like you talked aboutmore than just including motors, right?
Yeah, so it's, it's complex,uh, industrial communication,
it's synchronization oftime and things like that.
(08:14):
it's far more than just the motorthat I've thought about in the past.
So what are some of those technologiesthat the developers require to go from
just motor control to motion control tosome of these more advanced, solutions?
Daniel Hou (08:26):
Definitely.
So in terms of motion control, likeyou mentioned, Kyle, it not only
needs the, essence of motor control,which is more of a real time closed
loop system, but also it includes acentral brain of your whole system.
To look over all those differentmotor controllers in real time
and coordinate with them with areal time communication method.
(08:46):
Usually we're seeing today things likeEtherCAT, we might have heard of it.
Mm-hmm.
things like, time sense networkthat developed for real-time
communication through the ethernet.
So there are different technologiesthat we use to make the
advancement for motion control.
And then, in terms of motorcontrol itself, we're also seeing
(09:07):
a lot of involvement today.
for example, more efficient drive.
So we're seeing more and more, lessuse the term brushless DC motors
in the market today than before.
Before you'll see things likeBrush DC motors, Stepper motors
for a lot of basic applications.
Today we're seeing more of thoseapplications being replaced, the
motor types, to be more BrushlessDC or PMSM motors, in this case
(09:33):
because people are looking for moreefficient drive and looking for less
energy consumption, if you will.
Another big trend that's drivingthat is we are seeing more and more
systems that needs motor by runningoff the battery at the same time.
think of it as your smart Roomba, right?
Kyle Dando (09:48):
Yeah, yeah.
Daniel Hou (09:48):
or anything that's moving, it's going towards cordless.
Like your power tools,your gardening tools today.
So the requirement is to have a batterymanagement system at the same time,
to control the motor more efficientlyso the device base will last longer.
So that's another trend.
Kyle Dando (10:04):
Okay.
now that I'm seeing thismotion control aspect, what
about Artificial Intelligence?
We have a whole group at NXP.
Daniel Hou (10:10):
Absolutely.
Kyle Dando (10:10):
How are they using the machine learning?
I've heard about anomaly detection,I think in motion control, that's
probably pretty, pretty important.
Can you talk a little bitabout where you see that?
Daniel Hou (10:20):
Oh, yeah.
Artificial Intelligence, predictivemaintenance, this is something we heavily
invest our engineering forces on nowadays.
If you look at, a typical factorytoday with all the, we're talking
about automatic factories, right?
With all the robotic systems in there,we're seeing, roughly around $1.5
trillion cost by an unexpected downtime.
(10:42):
Cost by maybe just a loosebearing in the system.
Where people will need time to realize,"hey, the motor is going wrong" and they
need to shut the whole building downbasically, or shut the whole assembly
line down and to maintain or to fix theproblem and turn the system back on.
So that's causing today at $1.5 trillionand that number is not going lower.
(11:06):
It's going to only go higher, as we havemore automatic factories in the world.
So, what the predictive maintenanceor the artificial intelligence brings
onto the table is that by looking atcertain data, for example, vibration
of the motor temperature, the currentor voltage feedback of the motor.
(11:26):
You could identify or you can predictif the motor is going to be down.
If you predict that ahead of time,what that brings to the table is your
technician or your maintenance people orcrew can go in ahead of time, as a plan,
during the factory planned downtime.
So you're not causing anyunexpected downtime in the factory.
(11:47):
So that plays a very important role, notonly towards, creating, more economic
growth, but more more about going greener.
Kyle Dando (11:57):
Okay.
That's interesting, because itwould also probably reduce defects.
Yes.
So I'm assuming they have to fixthe equipment, but they have to look
back and see how many of the productsthat they've produced have defects
because of lack of calibration inthe motors and things like that.
Daniel Hou (12:10):
Right, Right on.
Kyle Dando (12:11):
What's the product that, NXP provides for AI/ML?
It might be interesting for Bridgetteand I to have them on the podcast.
What solution does NXP have for that?
Daniel Hou (12:19):
Right.
So, we have a combination of different,product plus software as solutions.
So if you think about predictivemaintenance or AI, it is what we
call Time Series Data Analysis.
It's different from, let's say amachine vision or facial recognition,
which is more, I would say,straightforward for people to understand.
So time series data analysis require youto firstly sense and collect the data.
(12:42):
So we have, analog front end fromNXP that's used as, for example,
remote iOS in the factories, that cancollect, different, dimensions of data.
We also have a broad portfolioof sensors that can collect data
like vibrations, for example.
Then there is your thinking partwhere you have the model on the edge
(13:02):
and you train that model usuallyfrom the cloud first, and then you
deploy that model to your edge device.
The edge device really is yourmicrocontrollers and microprocessors.
So nowadays for our controllers andprocessors, we start to put in, what we
call Neural Processing Unit, that's aspecific IP, onto our device to accelerate
(13:24):
the model inferencing for your AI/ML.
So that's what we do froma hardware perspective.
Software perspective, we also have acomplete tool chain called eIQ Toolkit
that basically help you acceleratethe development of your model.
Kyle Dando (13:37):
That's terrific.
Bridgette Stone (13:39):
Thanks for sharing all that, Daniel, and looking at the stats
and those numbers and the opportunitycosts, we have engineers all over the
globe trying to work to correct that.
And I think a good segway into thenext question is: When it comes to
designing motor control systems,what are the must have features and
capabilities that make all the difference?
Daniel Hou (14:00):
Definitely, that's a great segway and, I kind of touched a little
bit before on that, but really, if youlook at a motor control system, the
motor really speaks to analog, It,it takes some analog signal in and
it bursts out some analog signal out.
regardless of how you wanna drive themotor, usually you need to sense what's
happening in the motor by sensingsomething, what we call the Back EMF.
(14:21):
It's a magnetic field, created bythe motor, and based on that, you
determine the rotation status or likethe position of, the actual motor.
And then you're, building aclosed loop control system where
essentially you're, outputting asignal, that's usually a PWM and.
You're, you're changing the duecycle of the PWM two to manipulate
(14:42):
and control the motor precisely.
And that PWM eventually goes intolike a analog voltage or a voltage
plus current that goes into the motor.
So that's essentiallywhat the motor control is.
In terms of requirement for a system, yourmicrocontrollers needs to have peripherals
and IPs that can sense the data fromthe motor and then output the right
(15:05):
precise control waveform into the motor.
So, we have a unified platformor a unified control subsystem
in our most MCUs and also someMPUs, to do the motor control.
Another very important pieceof that is Real-time control.
Motor control is one of the most, Iwould say, precise and real-time control
(15:26):
category, other than digital powerconversion, that's another monster there.
It requires your system toreact the fastest as it can
with some synchronization.
So not only you need to have a efficientprocessing for your, let's say, your CPU
or your core of your microcontroller, butyou also need some additional features.
(15:47):
For example, if you trigger an ADC, atevery single timestamp of your PWM period.
It's going to give you the benefit ofsensing the, current at exactly the
same time and to eliminate the currentripple error that you could have.
So all those kind of featuresrequire your peripherals to
(16:07):
actually work together autonomouslywithout the core interference.
So that's another feature we provide.
On top of that, if you're doing someof the precise, position control like
your servo motor or your robotic,usually it will have additional
encoders to tell you exactly wherethe position of the motor is.
(16:28):
So you'll use that data and you needto decode that data into your whole
system, to determine how do you wannacontrol the motor, and how precise you
wanna put the motor into its rotation.
So that's another feature you need isto have a interface inside the MCU,
to decode whatever information youget from the motor on the positioning.
Bridgette Stone (16:48):
I'm not an engineer by trade, but I think I just
took a Motor Control 101 class,so I appreciate the education.
Kyle Dando (16:54):
So Daniel, those all sound challenging to Bridgette and me, but what
is the biggest challenge that you see whenyou go talk to the customers about this?
What is it that when they're designingmotor control solutions, what do
they communicate to you as theirbiggest concern and where do you
think that NXP helps them the most?
Daniel Hou (17:11):
Definitely.
It's hard for, most peopleto do motor control.
I would say it is.
For me to do motor control, I'll say I'mjust a student of motor control today.
Um, but usually what I get when Italk to our customers who's actually,
doing motor control, they usually areexperiencing a very steep learning curve.
You probably need a very deepknowledge on the control theory.
(17:33):
If you remember any of the classes,if you take, electric engineering,
degrees back at school, there is thiskind of like boring class, I would say,
talking about all the control series.
motor control is where that actuallycomes into the real world and you
have to actually utilize that.
And then there is also, requiring,you know, rich experience
of the real world tuning.
(17:53):
In school or in college you usuallyintroduce the control theory by
using, for example MATLAB, Simulink.
It is a lot of simulation.
It's not of ideal situation wherein the real world you actually
need to tinker a little bitsometimes to fine tune the motor.
And that needs actually quitea bit of, just experience,
by tuning the motor yourself.
Kyle Dando (18:14):
And patience.
Daniel Hou (18:14):
Exactly.
Exactly.
And therefore, it's really a combinationof hardware design complexity, plus
the software design complexity.
It is a very embedded,real-time system design.
So you're looking for thingslike isolation, things like ESD.
Usually your motor goes into avery high noise environments.
(18:35):
Think of your, washer dryer, your HVAC.
Those ones also have you really high EMIs.
So your system needs to be considerablefor those kind of robust performance MCUs
or other ICs in your motor control system.
So that's the whole considerationand this is really what NXP
provide, is, a combination ofrobust hardware, driven by our MCUs.
(18:58):
And also, moreover, it'sthe software that provide.
We have a very dedicated, talentedteam in Europe who are, frankly
speaking, just a team of eight PhDs.
That's control theory and motor control.
And they produce, the libraryand tooling tool, for our users,
based on their experience.
So the hope is to get our userto, fine tune their motor faster.
(19:21):
I.
Bridgette Stone (19:22):
Thanks for that, Daniel.
I wanna pivot just a littlebit on the last question here.
Something very near and dear to theEdgeVerse Techcast theme is tools
and getting motor control, right?
Must have to require the right tools.
So can, you walk through whatNXP offers to help developers
simplify their design, speed updevelopment, and optimize performance.
Daniel Hou (19:47):
Of course.
Yes.
So we have a very streamlined developerexperience when it comes to motor control.
so basically, what we offer are someessential needs when you are trying
to tune a motor, system or you'retrying to develop a motor system.
So the first step isto identify the motor.
It is called motor characterization.
So we have tools, called MCAT orthe motor control, tuning tool.
(20:10):
Basically, what it does is to, look at themotor, by injecting some pulses into the
motor and figure out a rough estimationof the characteristics of the motor.
The next step is also usingthe MCAT together with.
Our, realtime visualizationdebugging tool called FreeMASTER.
So the FreeMASTER is basically arealtime debugging tool that you can
(20:31):
use that to interact with your motorand your control software, and you
can fine tune your motor that way.
So everything's visualized, everythingis real time, and that's very important.
I've heard multiple feedbacksfrom our customers how important
that is for us to have the tool.
Because, if you look at a traditionaldebugger, you need to, set up like
(20:53):
a break point in the system andif you are doing a motor tuning,
that basically breaks the system.
so you need your system to keeprunning while you have a visualized.
View on what's going onto your whole system.
So that's where, FreeMASTER really shines.
And in terms of code delivery, we alsohave a real time control, library.
that's basically under the hood.
(21:13):
That's our secret sauce, I would say,to help you get to your final, tuning
over your final software faster.
Those warrants are typicallysupporting the field oriented control.
This is one of the most advancedcontrol algorithm, that.
Industry is using today.
So in terms of code delivery,finally we have the SDK, to deliver,
(21:34):
the motor control library there.
Another thing we have, is calledapplication code hub, right?
Kyle Dando (21:39):
Mm-hmm.
Daniel Hou (21:40):
So that's.
Just like an easier, more straightforwardway for us to deliver code.
It's a GitHub basedRepo, uh, that NXP owns.
Bridgette Stone (21:48):
One of our favorite topics on the Techcast
Daniel Hou (21:51):
I just wanna highlight that, you know, we do have several motor control
examples on the Application Code Hub todaythat you could directly download the code.
It has a very, precise and detailedREADME file that you can go through.
And then, you can download whateverthe tools like FreeMASTER for your real
time tuning according to the README.
And then, you can get your motorstart running in, I'll say,
(22:13):
10 minutes or to half an hour.
So that's a really powerful codedelivery method we have right now.
Bridgette Stone (22:20):
Amazing.
And would you say for developersthat are just getting started, that's
one of the best places to begin?
Or what would you recommend?
Daniel Hou (22:28):
Exactly.
That's absolutely the best place to begin.
I'll say, if you follow the Readme filein a lot of motor control examples.
For example, there is one calledIndustrial Control Panel Example,
where it's a combination of motorcontrol plus a HMI aspect, where
you can control it through a LCDscreen, by the speed and everything.
That application, you could go in there.
(22:50):
It has instructions for you to downloadFreeMASTER, and to fine tune your
motor in real time . So I would saystart with Application Code Hub.
That will get your motor running in10 minutes and then you can look into,
FreeMASTER to fine tune your own motor.
Bring your own motor to your bench and,spend some time looking to the SDK code
examples or libraries, once you havea better understanding of your system.
Bridgette Stone (23:13):
Thank you so much for sharing all your wisdom with us today.
This has been super educational.
I've learned a ton.
I don't know about you, Kyle.
Hopefully you have, but maybeyou're singing in the background.
But we appreciate youbeing on today, Daniel.
Let's do a quick recap.
Today we explored what motor controlmeans in the NXP world, how it's evolving
(23:35):
with robotics and automation, and the keyfeatures that make all the difference.
If you're ready to dive deeper, be sureto check out our motor control solutions,
tools like FreeMASTER and MCAT, andexamples in our application Code Hub.
Kyle Dando (23:49):
And remember everybody, if you enjoyed this conversation, don't forget to
take the time to Like, Subscribe, and turnon Notifications so that you won't miss
our next episode, which is every Tuesday.
And hey, if you have a topic thatyou'd like us to cover similar
to Motor Control today, drop itin the comments and let us know.
(24:09):
And until next time, keep innovatingeverybody and we'll catch you
on the next EdgeVerse TechCast.
Born to be wild.
Born to be wild.
Head out on the highway,
(24:33):
In whatever comes our way.
Welcome everyone to the NXP EdgeVerse Techcast, where
we talk about software, tools andtechnologies that help bring NXP's,
processors and microcontrollers to life.
Whether you're deep intodevelopment or just exploring what's
possible, we've got you covered.
Kyle Dando (00:27):
Get your motor running.
Head out on the highway.
Looking for adventure.
In whatever comes our way.
Bridgette Stone (00:37):
You've clearly been waiting for this moment.
Was it everything that you dreamed of?
Kyle Dando (00:43):
Oh, come on, Bridgette.
I've been waiting my whole life just tosing SteppenWolf to a big crowd like this.
But seriously, today's topic mademe think about this popular lyric,
"Getting your motor running".
This has long been the pursuitof most of the embedded design
engineers that we work with at NXP.
Bridgette Stone (01:00):
All right, Kyle, I'll definitely give you points for creativity.
Terrible singing aside, we reallydo have a great episode lined up.
We're joined by Daniel Hou, a truemotor control expert who can actually
back up the Steppenwolf reference.
Kyle Dando (01:16):
All right.
Well Daniel, thanks for joiningus today on the TechCast.
Can you explain how youcame to be involved in all
things motor control at NXP?
Daniel Hou (01:23):
Sure.
Thanks Kyle.
By the way, great singing I'm not sureif I can totally back up that beautiful
singing, I'm the podcast today.
My name is Daniel Hou.
I'm, a product marketer from NXPwho's looking over our Industrial
and IoT applications, forMicrocontrollers and Microprocessors.
So that's your typical, I wouldsay, brain of your control system.
(01:44):
also involved in motor control.
And, motor control is oneof my focus, for my team.
Kyle Dando (01:49):
Great.
Bridgette Stone (01:50):
We're so happy to have you, Daniel.
Thanks for being here today.
And, motor control is a big dealacross so many industries, but
what does it mean in the NXP world?
Daniel Hou (02:00):
Well, in short it means a lot, but let me elaborate on that.
So basically, within the Industrialand IOT segments, NXP as a company,
we have identified several emergingapplications and market segments to
invest more technology into, becausethose are fast growing segments.
I'll give you some examples.
(02:20):
For example, Smart Factory.
Factory automation is one of themajor trend in the industry right now.
A lot of investment going on there.
Healthcare, right?
This is also a mega trend driven by thetotal health condition of the population
here and how do we make it smarter?
And then also things like SmartHome Control or Building Control.
(02:40):
So if you look at motor control asa technology is more of a horizontal
technology versus a vertical technology.
So for vertical, we're talking aboutfactories, buildings, medicals, right?
So motor control is a horizontaltechnology that has shared a lot of,
similar feature needed or similartechnology, similar platforms
(03:02):
across different vertical segments.
So that's how, motor control isreally a important, Technology
Pillar towards all the differentsegments that NXP is investing in.
Bridgette Stone (03:13):
Thanks for breaking that down, Daniel.
And as you mentioned, Motor Controlplays a role in many applications from
industrial to intelligent buildings.
Does that mean the same solutionscan scale across different use cases?
Daniel Hou (03:26):
To some extent, as a company, we provide, one of the, largest range
of processing platforms for real-timecontrol and motor control is, one of the
essence of the real-time control aspect.
If you look at our product portfolio,there is just such a breadth to it.
we just announced and, launchedthe new MCU platform called MCX.
(03:48):
Among the MCX, there are a lot of devicesthat's built for motor control, and
we also have the i.MX RT family, whichis our high performance, high speed
lane for MCUs and they also do reallywell with, high dynamic motor control.
I'm really excited about thenext product called i.MX94.
(04:10):
This is gonna be, one of the firstMicroprocessors or Application Processors
that we added to our portfolio that canactually do a real-time motor control
with this powerful real-time capability.
I'm really excited about the, productbreadth and scalability that we
provide when it comes to motor control.
And it's not only aboutthe hardware here, right?
(04:31):
If you talk about Motor Control,it's a lot of algorithms.
It's a lot of software.
So we also have a, unified offering ofsoftware tools to help our customers,
to help the users to identify,the characteristics of the motor.
To fine tune the motor, you'llhear a lot of, terms like
fine tuning or motor tuning.
This is one of the most commonlyused, terminology and, techniques in
(04:55):
terms of motor control system design.
So we have dedicated tools to help ourcustomers to fine tune the motors, to do
a real time visualized debugging, and alsodeliver a software library based on that.
So these are all unified across the wholeplatform for our Motor Control offering.
Kyle Dando (05:13):
So when I came to NXP, it's that breadth, right?
Yeah.
As you mentioned, lots of differentproducts at scale, for the complexity
of the motor controller or the motioncontrol, and then the software.
And we're gonna touch on that in a coupleother questions that we're gonna ask you.
But before we jump into that,motor control has come a long
way since, I graduated college.
In the past motor applicationswere focused more on running
(05:35):
industrial pumps and fans.
Back then, complex motion controlwas found in automation of
different manufacturing processes.
Today I've started to see more andmore advanced applications for motors.
Just this last weekend, my familyand I were out at the shopping
mall and we went to a showroom andwe saw this new, Tesla Bot called
Optimus, and it looked really scary.
(05:57):
But, it shows you these huge advancementsthat are being made in motor control.
It's much more than just the sillyRoomba that we had 10 years ago.
Daniel Hou (06:06):
Exactly.
Yep.
Kyle Dando (06:06):
So Daniel, what's driving this evolution in motor control
and where do you see it going next?
Daniel Hou (06:12):
Yeah, and you're exactly on point, Kyle, you mentioned Roomba
and you used the silly Roomba nowadays.
So back then we were thinkingRoomba is a very advanced mobile
robotic application, right?
Now it becomes more basic.
So this is what we are seeingin the industry as well.
So it becomes more, highlydynamic control systems.
You are seeing more and moreautonomous systems in our industry now.
(06:35):
Not only limited to factory today.
if you go to your home, there isautonomous systems everywhere.
There is some autonomous systemthat involves more basic motor
controls like pumps, but there aremore, that involves robotics today.
We're talking about evenlike the, the co-bot.
That's another concept to the robotwhere it basically work collaboratively
(06:57):
with a human, by the side.
So all kinds of trend and allkinds of advancement in terms of
robotic applications in there.
And when it comes to robotic, there's alsoanother concept that's kind of, people
kind of get confused sometimes with MotorControl, which is called Motion Control.
So Motion Control is more of adifferent or a higher level of
(07:19):
control on top of Motor Control.
If you think about motorcontrol, it's controlling the
precise spinning of one motor.
And motion control is about coordinationtypically for several motors.
If you look at an example will be arobotic arm in the factory, right?
It has multiple axis and you need tocoordinate all those different motors that
(07:39):
control different axis and to actuallyachieve a motion at the end of the day.
So that's motion control.
And frankly speaking, we're seeinga blend of involvement in terms
of both Motor Control and MotionControl in the industry today.
Kyle Dando (07:53):
Okay.
Well that's interesting.
I don't think I've thought of it asmuch about Motion Control as I've always
thought of Motor Control, so that's great.
So with motion control, is this openingthe door for these more advanced
applications, like you talked aboutmore than just including motors, right?
Yeah, so it's, it's complex,uh, industrial communication,
it's synchronization oftime and things like that.
(08:14):
it's far more than just the motorthat I've thought about in the past.
So what are some of those technologiesthat the developers require to go from
just motor control to motion control tosome of these more advanced, solutions?
Daniel Hou (08:26):
Definitely.
So in terms of motion control, likeyou mentioned, Kyle, it not only
needs the, essence of motor control,which is more of a real time closed
loop system, but also it includes acentral brain of your whole system.
To look over all those differentmotor controllers in real time
and coordinate with them with areal time communication method.
(08:46):
Usually we're seeing today things likeEtherCAT, we might have heard of it.
Mm-hmm.
things like, time sense networkthat developed for real-time
communication through the ethernet.
So there are different technologiesthat we use to make the
advancement for motion control.
And then, in terms of motorcontrol itself, we're also seeing
(09:07):
a lot of involvement today.
for example, more efficient drive.
So we're seeing more and more, lessuse the term brushless DC motors
in the market today than before.
Before you'll see things likeBrush DC motors, Stepper motors
for a lot of basic applications.
Today we're seeing more of thoseapplications being replaced, the
motor types, to be more BrushlessDC or PMSM motors, in this case
(09:33):
because people are looking for moreefficient drive and looking for less
energy consumption, if you will.
Another big trend that's drivingthat is we are seeing more and more
systems that needs motor by runningoff the battery at the same time.
think of it as your smart Roomba, right?
Kyle Dando (09:48):
Yeah, yeah.
Daniel Hou (09:48):
or anything that's moving, it's going towards cordless.
Like your power tools,your gardening tools today.
So the requirement is to have a batterymanagement system at the same time,
to control the motor more efficientlyso the device base will last longer.
So that's another trend.
Kyle Dando (10:04):
Okay.
now that I'm seeing thismotion control aspect, what
about Artificial Intelligence?
We have a whole group at NXP.
Daniel Hou (10:10):
Absolutely.
Kyle Dando (10:10):
How are they using the machine learning?
I've heard about anomaly detection,I think in motion control, that's
probably pretty, pretty important.
Can you talk a little bitabout where you see that?
Daniel Hou (10:20):
Oh, yeah.
Artificial Intelligence, predictivemaintenance, this is something we heavily
invest our engineering forces on nowadays.
If you look at, a typical factorytoday with all the, we're talking
about automatic factories, right?
With all the robotic systems in there,we're seeing, roughly around $1.5
trillion cost by an unexpected downtime.
(10:42):
Cost by maybe just a loosebearing in the system.
Where people will need time to realize,"hey, the motor is going wrong" and they
need to shut the whole building downbasically, or shut the whole assembly
line down and to maintain or to fix theproblem and turn the system back on.
So that's causing today at $1.5 trillionand that number is not going lower.
(11:06):
It's going to only go higher, as we havemore automatic factories in the world.
So, what the predictive maintenanceor the artificial intelligence brings
onto the table is that by looking atcertain data, for example, vibration
of the motor temperature, the currentor voltage feedback of the motor.
(11:26):
You could identify or you can predictif the motor is going to be down.
If you predict that ahead of time,what that brings to the table is your
technician or your maintenance people orcrew can go in ahead of time, as a plan,
during the factory planned downtime.
So you're not causing anyunexpected downtime in the factory.
(11:47):
So that plays a very important role, notonly towards, creating, more economic
growth, but more more about going greener.
Kyle Dando (11:57):
Okay.
That's interesting, because itwould also probably reduce defects.
Yes.
So I'm assuming they have to fixthe equipment, but they have to look
back and see how many of the productsthat they've produced have defects
because of lack of calibration inthe motors and things like that.
Daniel Hou (12:10):
Right, Right on.
Kyle Dando (12:11):
What's the product that, NXP provides for AI/ML?
It might be interesting for Bridgetteand I to have them on the podcast.
What solution does NXP have for that?
Daniel Hou (12:19):
Right.
So, we have a combination of different,product plus software as solutions.
So if you think about predictivemaintenance or AI, it is what we
call Time Series Data Analysis.
It's different from, let's say amachine vision or facial recognition,
which is more, I would say,straightforward for people to understand.
So time series data analysis require youto firstly sense and collect the data.
(12:42):
So we have, analog front end fromNXP that's used as, for example,
remote iOS in the factories, that cancollect, different, dimensions of data.
We also have a broad portfolioof sensors that can collect data
like vibrations, for example.
Then there is your thinking partwhere you have the model on the edge
(13:02):
and you train that model usuallyfrom the cloud first, and then you
deploy that model to your edge device.
The edge device really is yourmicrocontrollers and microprocessors.
So nowadays for our controllers andprocessors, we start to put in, what we
call Neural Processing Unit, that's aspecific IP, onto our device to accelerate
(13:24):
the model inferencing for your AI/ML.
So that's what we do froma hardware perspective.
Software perspective, we also have acomplete tool chain called eIQ Toolkit
that basically help you acceleratethe development of your model.
Kyle Dando (13:37):
That's terrific.
Bridgette Stone (13:39):
Thanks for sharing all that, Daniel, and looking at the stats
and those numbers and the opportunitycosts, we have engineers all over the
globe trying to work to correct that.
And I think a good segway into thenext question is: When it comes to
designing motor control systems,what are the must have features and
capabilities that make all the difference?
Daniel Hou (14:00):
Definitely, that's a great segway and, I kind of touched a little
bit before on that, but really, if youlook at a motor control system, the
motor really speaks to analog, It,it takes some analog signal in and
it bursts out some analog signal out.
regardless of how you wanna drive themotor, usually you need to sense what's
happening in the motor by sensingsomething, what we call the Back EMF.
(14:21):
It's a magnetic field, created bythe motor, and based on that, you
determine the rotation status or likethe position of, the actual motor.
And then you're, building aclosed loop control system where
essentially you're, outputting asignal, that's usually a PWM and.
You're, you're changing the duecycle of the PWM two to manipulate
(14:42):
and control the motor precisely.
And that PWM eventually goes intolike a analog voltage or a voltage
plus current that goes into the motor.
So that's essentiallywhat the motor control is.
In terms of requirement for a system, yourmicrocontrollers needs to have peripherals
and IPs that can sense the data fromthe motor and then output the right
(15:05):
precise control waveform into the motor.
So, we have a unified platformor a unified control subsystem
in our most MCUs and also someMPUs, to do the motor control.
Another very important pieceof that is Real-time control.
Motor control is one of the most, Iwould say, precise and real-time control
(15:26):
category, other than digital powerconversion, that's another monster there.
It requires your system toreact the fastest as it can
with some synchronization.
So not only you need to have a efficientprocessing for your, let's say, your CPU
or your core of your microcontroller, butyou also need some additional features.
(15:47):
For example, if you trigger an ADC, atevery single timestamp of your PWM period.
It's going to give you the benefit ofsensing the, current at exactly the
same time and to eliminate the currentripple error that you could have.
So all those kind of featuresrequire your peripherals to
(16:07):
actually work together autonomouslywithout the core interference.
So that's another feature we provide.
On top of that, if you're doing someof the precise, position control like
your servo motor or your robotic,usually it will have additional
encoders to tell you exactly wherethe position of the motor is.
(16:28):
So you'll use that data and you needto decode that data into your whole
system, to determine how do you wannacontrol the motor, and how precise you
wanna put the motor into its rotation.
So that's another feature you need isto have a interface inside the MCU,
to decode whatever information youget from the motor on the positioning.
Bridgette Stone (16:48):
I'm not an engineer by trade, but I think I just
took a Motor Control 101 class,so I appreciate the education.
Kyle Dando (16:54):
So Daniel, those all sound challenging to Bridgette and me, but what
is the biggest challenge that you see whenyou go talk to the customers about this?
What is it that when they're designingmotor control solutions, what do
they communicate to you as theirbiggest concern and where do you
think that NXP helps them the most?
Daniel Hou (17:11):
Definitely.
It's hard for, most peopleto do motor control.
I would say it is.
For me to do motor control, I'll say I'mjust a student of motor control today.
Um, but usually what I get when Italk to our customers who's actually,
doing motor control, they usually areexperiencing a very steep learning curve.
You probably need a very deepknowledge on the control theory.
(17:33):
If you remember any of the classes,if you take, electric engineering,
degrees back at school, there is thiskind of like boring class, I would say,
talking about all the control series.
motor control is where that actuallycomes into the real world and you
have to actually utilize that.
And then there is also, requiring,you know, rich experience
of the real world tuning.
(17:53):
In school or in college you usuallyintroduce the control theory by
using, for example MATLAB, Simulink.
It is a lot of simulation.
It's not of ideal situation wherein the real world you actually
need to tinker a little bitsometimes to fine tune the motor.
And that needs actually quitea bit of, just experience,
by tuning the motor yourself.
Kyle Dando (18:14):
And patience.
Daniel Hou (18:14):
Exactly.
Exactly.
And therefore, it's really a combinationof hardware design complexity, plus
the software design complexity.
It is a very embedded,real-time system design.
So you're looking for thingslike isolation, things like ESD.
Usually your motor goes into avery high noise environments.
(18:35):
Think of your, washer dryer, your HVAC.
Those ones also have you really high EMIs.
So your system needs to be considerablefor those kind of robust performance MCUs
or other ICs in your motor control system.
So that's the whole considerationand this is really what NXP
provide, is, a combination ofrobust hardware, driven by our MCUs.
(18:58):
And also, moreover, it'sthe software that provide.
We have a very dedicated, talentedteam in Europe who are, frankly
speaking, just a team of eight PhDs.
That's control theory and motor control.
And they produce, the libraryand tooling tool, for our users,
based on their experience.
So the hope is to get our userto, fine tune their motor faster.
(19:21):
I.
Bridgette Stone (19:22):
Thanks for that, Daniel.
I wanna pivot just a littlebit on the last question here.
Something very near and dear to theEdgeVerse Techcast theme is tools
and getting motor control, right?
Must have to require the right tools.
So can, you walk through whatNXP offers to help developers
simplify their design, speed updevelopment, and optimize performance.
Daniel Hou (19:47):
Of course.
Yes.
So we have a very streamlined developerexperience when it comes to motor control.
so basically, what we offer are someessential needs when you are trying
to tune a motor, system or you'retrying to develop a motor system.
So the first step isto identify the motor.
It is called motor characterization.
So we have tools, called MCAT orthe motor control, tuning tool.
(20:10):
Basically, what it does is to, look at themotor, by injecting some pulses into the
motor and figure out a rough estimationof the characteristics of the motor.
The next step is also usingthe MCAT together with.
Our, realtime visualizationdebugging tool called FreeMASTER.
So the FreeMASTER is basically arealtime debugging tool that you can
(20:31):
use that to interact with your motorand your control software, and you
can fine tune your motor that way.
So everything's visualized, everythingis real time, and that's very important.
I've heard multiple feedbacksfrom our customers how important
that is for us to have the tool.
Because, if you look at a traditionaldebugger, you need to, set up like
(20:53):
a break point in the system andif you are doing a motor tuning,
that basically breaks the system.
so you need your system to keeprunning while you have a visualized.
View on what's going onto your whole system.
So that's where, FreeMASTER really shines.
And in terms of code delivery, we alsohave a real time control, library.
that's basically under the hood.
(21:13):
That's our secret sauce, I would say,to help you get to your final, tuning
over your final software faster.
Those warrants are typicallysupporting the field oriented control.
This is one of the most advancedcontrol algorithm, that.
Industry is using today.
So in terms of code delivery,finally we have the SDK, to deliver,
(21:34):
the motor control library there.
Another thing we have, is calledapplication code hub, right?
Kyle Dando (21:39):
Mm-hmm.
Daniel Hou (21:40):
So that's.
Just like an easier, more straightforwardway for us to deliver code.
It's a GitHub basedRepo, uh, that NXP owns.
Bridgette Stone (21:48):
One of our favorite topics on the Techcast
Daniel Hou (21:51):
I just wanna highlight that, you know, we do have several motor control
examples on the Application Code Hub todaythat you could directly download the code.
It has a very, precise and detailedREADME file that you can go through.
And then, you can download whateverthe tools like FreeMASTER for your real
time tuning according to the README.
And then, you can get your motorstart running in, I'll say,
(22:13):
10 minutes or to half an hour.
So that's a really powerful codedelivery method we have right now.
Bridgette Stone (22:20):
Amazing.
And would you say for developersthat are just getting started, that's
one of the best places to begin?
Or what would you recommend?
Daniel Hou (22:28):
Exactly.
That's absolutely the best place to begin.
I'll say, if you follow the Readme filein a lot of motor control examples.
For example, there is one calledIndustrial Control Panel Example,
where it's a combination of motorcontrol plus a HMI aspect, where
you can control it through a LCDscreen, by the speed and everything.
That application, you could go in there.
(22:50):
It has instructions for you to downloadFreeMASTER, and to fine tune your
motor in real time . So I would saystart with Application Code Hub.
That will get your motor running in10 minutes and then you can look into,
FreeMASTER to fine tune your own motor.
Bring your own motor to your bench and,spend some time looking to the SDK code
examples or libraries, once you havea better understanding of your system.
Bridgette Stone (23:13):
Thank you so much for sharing all your wisdom with us today.
This has been super educational.
I've learned a ton.
I don't know about you, Kyle.
Hopefully you have, but maybeyou're singing in the background.
But we appreciate youbeing on today, Daniel.
Let's do a quick recap.
Today we explored what motor controlmeans in the NXP world, how it's evolving
(23:35):
with robotics and automation, and the keyfeatures that make all the difference.
If you're ready to dive deeper, be sureto check out our motor control solutions,
tools like FreeMASTER and MCAT, andexamples in our application Code Hub.
Kyle Dando (23:49):
And remember everybody, if you enjoyed this conversation, don't forget to
take the time to Like, Subscribe, and turnon Notifications so that you won't miss
our next episode, which is every Tuesday.
And hey, if you have a topic thatyou'd like us to cover similar
to Motor Control today, drop itin the comments and let us know.
(24:09):
And until next time, keep innovatingeverybody and we'll catch you
on the next EdgeVerse TechCast.
Born to be wild.
Born to be wild.
Head out on the highway,
(24:33):
In whatever comes our way.
Popular Podcasts
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com
24/7 News: The Latest
The latest news in 4 minutes updated every hour, every day.
Therapy Gecko
An unlicensed lizard psychologist travels the universe talking to strangers about absolutely nothing. TO CALL THE GECKO: follow me on https://www.twitch.tv/lyleforever to get a notification for when I am taking calls. I am usually live Mondays, Wednesdays, and Fridays but lately a lot of other times too. I am a gecko.