Project

Final Report

Prepared for:

Dr. Marco Tacca and Dr. Leo Estevez

Prepared by:

Heather Thomas

Team Ψ

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TABLE OF CONTENTS

ABSTRACT…………………………………………………………….. (2)

BACKGROUND/INTRODUCTION……………………………. (2)

UTDESIGN 1………………………………………………………… (3-4)

UTDESIGN 2………………………………………………………… (5-6)

Introduction…….. (5)

Goals……………….. (6)

PROJECT DEVELOPMENT…………………………………….. (7-8)

Dual Motor Control…………… (7)

E-Bike……………………………….. (7)

Bluetooth/Drone………………. (8)

JTAG…………………………………. (9)

HFI/eSMO Integration………. (9)

RESULTS……………………………………………………………. (10)

SOFTWARE FLOWCHART…... (11)

CONCLUSION…………………………………………..…………… (12)

SPECIAL THANKS………………………………………..………… (12)

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Abstract

An integrated control algorithm and hardware solution for brushless DC (BLDC) motors is presented. The

increasing market for electric vehicles utilizing BLDC motors makes new and innovative control

techniques important to future applications. Based on TI products, the solution incorporates two control

methods to better govern the starting angle and operation at low RPMs while maintaining performance

at higher RPMs. The various microcontrollers and motor driver chips considered for the control system

will be discussed. Factors such as the relationship between speed and voltage as well as current and

torque were weighed with regard to the expected load on the vehicle, an electric bike (E-Bike).

Background & Introduction

The increased sales and utilization of electric vehicles worldwide is driving a demand for better power

efficiency and more precise control methods. The BLDC motors commonly utilized in E-Bike applications

make use of Hall sensors to track rotor position. Hall sensors can be unreliable in the physically

demanding system of an E-Bike. If one sensor fails many issues with the control of the motor, such as

jittering and rotor lock, can occur. Sensorless control achieved with field oriented algorithms has the

possibility to replace the sensored tracking system.

BLDC motors are generally more efficient in converting electrical into mechanical power, making them

an excellent solution for the energy minded consumer. However, controlling BLDC motors is much more

complicated. Increasing the power efficiency of the control system as well as utilization of lithium

polymer batteries will increase longevity of the power supply.

Modern consumers use their wireless devices for everything from simple communication to complex

tracking of activities. Integrating the wireless capabilities of mobile devices with the E-Bike control

system would add a new interactive dimension to the rider’s experience. Bluetooth wireless

communication could be used to provide the following: speed control, inputting motor parameters,

speed tracking, distance traveled, and remaining battery power.

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UTDesign 1: Fall 2013

During UTDesign 1, the team decided to distribute the various areas of knowledge covered by the

project and assign them to each member the team. Self-study was required to obtain the information

necessary to design and implement the BLDC control system.

Goals

Understand the theory behind motor control and be able to spin a BLDC motor.

Determine available control parameters in TI’s MotorWare development kit API.

Learn how to develop circuit schematics and implement custom circuit designs.

Be able to interface a microcontroller and smartphone via Bluetooth (user control).

Understand the power requirements of the system and their impact on implementation.

Develop a test-bench for real world conditions and acquisition of experimental data.

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Deliverables

Understanding the theory behind Rotor Flux Oriented Control, and Back EMF Zero Crossing

Detection.

Understanding the proper hardware configuration required to spin a BLDC motor using two

different control theory implementations.

Identified control parameters required for user input and system setup.

Developed a test-bench for characterization and comparison between hardware

implementations.

Successfully interfaced Bluetooth and the microcontroller to enable the motor and control its

speed using an Android phone.

Learned how to identify the parameters of various BLDC motors, such as the number of poles,

inductance, commutation time, and resistance.

At the UTDesign 1 Expo day the team was able to demonstrate Bluetooth control of a BLDC motor on

the test-bench. This was done utilizing an interface PCB that the team designed specifically for this

purpose. It included the BlueRadio chip to facilitate communication.

Team Psi was ranked first among all of the teams at the Senior Expo in December.

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UTDesign 2: Spring 2014

Due to the team’s successful completion of the UTDesign 1 goals, the TI mentor, Dr. Leo Estevez, revised

the overall project objectives. The team was asked to develop a dual BLDC motor control system in

addition to the E-Bike. The system would be used to control an unmanned electric vehicle via Bluetooth.

Each team member continued working in the same area of knowledge as UTDesign 1 with modified

goals for the final product.

During the course of the semester Team Ψ had the opportunity to work with Tim Adcock on two

occasions. Both of these were very fruitful and provided great insight into the operation of HFI. As the

Director of TI’s R&D Motor Lab, Dr. Adcock was able to bring in Shih-chin Yang, who helped develop HFI.

From the beginning of the E-bike project, Team Ψ only had limited access to the internal workings of the

program. This effectively made HFI a black box. Dr. Adcock described the team’s work on the E-bike as a

graduate level project.

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UTDesign 2: Goals

Software\Microcontroller Programming: Casio Travesi and Carlos Caicedo

Utilize HFI (high frequency injection)algorithm developed by TI to determine the initial location

of the rotor

Utilize SMO (sliding mode observer) to run the motor at higher RPMs.

Create program integrating HFI and SMO to control the motor at all speeds

Bias analog to digital converters to accept input from controllers and route the signals properly

in code

Implement differential steering for dual motor applications

Hardware: Heather Thomas and Xukai Sun

Creation of an interface PCB from a CC28035 microcontroller to run two BOOSTXL8301 boards

Implementation of a boost converter to provide a 5V reference from the 3.3V reference voltage

on the BOOSTXL

Altium schematic design for fully integrated board

JTAG communication board for programming microcontroller

Revise BOOSTXL schematic to achieve 36-48V input

Bluetooth Application/Integration: James Smiley

Use a mobile device’s GPS to control a drone vehicle

Collect data via Bluetooth

Display data for user

Enter motor parameters for use in microcontroller

Each of the above groups worked separately but also came together for many of the larger parts of the

project. Beyond the goals listed above, the team was also creating its own unique vehicle to

test/demonstrate the dual motor control. Dubbed the E-Chariot, this vehicle was a culmination of many

ideas incorporated from all team members. The team hoped to bring a viable product to market via

Kickstarter. The E-Chariot seemed like the unique product that could create a buzz.

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Development/Results

Dual Wheel Control

First the hardware group confirmed that the CC28035 microcontroller had enough dedicated PWM and

ADC (analog to digital converters) lines to facilitate communications with two BOOSTXL motor driver

boards. The software group began researching and testing the ADCs for voltage range, which they

determined to be 1.3V to 3.3V. Once the proper connections between the DRVs and the microcontroller

were determined and the ADC range was set in code, the team tested the theory by reconfiguring an

older version of the communication board with the new dual control connections. Operation was

confirmed, and testing for proper parameters, PI controller gains and current reference values, began in

earnest.

The hardware group began designing a new Interface Communications PCB Board (ICB) for dual motor

control. An Altium PCB design for our dual motor was also started at this time. Walt Culpepper at TI was

instrumental in the team’s hardware development and testing. He populated many of our PCB board

iterations and created Altuim models for the components on our final board design. We have completed

the design but it has not been manufactured for testing.

Two iterations of the dual ICB were created and tested over the course of the semester. The team

accomplished communications between the boards and basic control of each motor separately.

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E-Bike

Team Ψ used the dual ICB for the single wheel E-bike application by not populating the second DRV

location. The hybrid HFI/eSMO algorithm was placed on the microcontroller. We tested the bike with 1

22.2V, 5000mAH and were able to go 41 minutes on one charge. With two batteries in parallel, the bike

went for 1 hour and 36 minutes on one charge. The maximum speed was 11mph in both cases. When

we put the two batteries in series to increase the speed, the team came very close to the 20mph an E-

Bike is limited to by law.

Bluetooth/Drone

The Bluetooth developer worked on drone control using the GPS on an Android phone. The idea of Geo-

fencing was explored. The motors on the test drone were not matched well and that made basic control

of the vehicle difficult to begin with. Once that was addressed, the team discovered that the GPS on

many smart phones did not have enough resolution for such fine control.

After the drone application was discarded, the Bluetooth developer turned back to collecting

information from the microcontroller to be displayed on the phone. A speedometer was developed,

tested and confirmed fairly accurate. Further development and refinement would be necessary, but

application of the method could be used to track and display many different parameters for users.

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We were informed by TI that if we put our design into production, we would need to eliminate access to

the microcontroller in order to protect TI's proprietary software. This poses a problem for entering new

parameters for different motors. Therefore, we developed code that asked for motor parameters via

Bluetooth every time it is powered on. A smartphone can then link up using a terminal type program or

a custom made app that allows user entry. This method proved that it could be done, however a

finished product would require motor parameters only when necessary, not every time it is turned

on. This we believe can be achieved by using a static memory chip that would store these parameters

until a set switch alerts the microcontroller to ask for new parameters from the user. In this way, the

microcontroller can always look to that memory location for initialization.

JTAG

Early on the team was still considering the CC28027 controller for the dual ICB. This microcontroller did

not have a JTAG (or any other) communication interface on-board. The hardware group added a JTAG

communication circuit on the last iteration of the single motor ICB designed at the end of UTDesign 1.

Unfortunately communication was never achieved. A second attempt at designing this circuit was made

but time ran out and testing was never accomplished.

HFI & eSMO

During UTDesign 1 the team was handed a new algorithm called HFI (high frequency injection). This

software was supposed to help address the initial angle issue with 3 phase BLDC motors by extracting

the initial angle of the rotor with regard to the stator. The program was already incorporated into

another control algorithm (Field Oriented Control) and the software team spent many hours

understanding FOC so they could extract HFI. This was a large part of the research done last semester.

After spending several months on the dual control system, Team Ψ returned to the original project.

With a much better understanding of the various motor control software available from TI, the team

was able to implement HFI in both the single and dual wheel applications.

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Figure 1: E-Chariot

The team found many issues using the HFI algorithm on the BLDC hub motors. HFI was created for

internal permanent magnet motors while ours is an external magnet motor. This has made

implementation of the hybrid HFI/eSMO program difficult. A couple of issues with the algorithms,

mainly in this application, were discovered and reported to TI for further investigation.

Results

Team Ψ was able to make both an E-bike and the E-chariot. These represent the culmination of our

UTDesign effort. Both vehicles utilize our ICB board and the hybrid HFI/eSMO program we developed.

The chariot, shown below, was designed and built by our team with the help of Ben Lardas, Josh

Cummings of Precision Powder, and Ryan Wensel.

We are still developing the differential steering

and other additions for this vehicle. It is joystick

operated, which was in the plan all along. The E-

bike was the original goal of the project.

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This is a flowchart of the hybrid HFI/eSMO program that was put together from TI software.

Figure 2: Software flowchart for dual motor control

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Team Photo 1: left to right Carlos Caicedo, Xukai Sun, Casio Travesi, Heather Thomas, and James Smiley

Created in Altium with the help of Walt Culpepper, this is the final

PCB design incorporating both BOOSTXL DRVs and the CC28035. Dr.

Estevez had a source at TI price construction of this board and found

it would cost just under $100 per unit for manufacture and

population.

Conclusion

As a team we have met or exceeded the expectations of our mentors. At the time that I write this, we

have been awarded 1st place in the Senior Design Expo for the second time. But the hard thing to say is,

we did not reach our own goal of bringing a product to market at the conclusion of senior design. There

was so much more each team member wanted to do, but was unable to complete. UTDesign has been

an amazing experience. As a team, we still want to start a company together one day. Perhaps with a bit

more research and development our first product will somehow be related to the E-Bike. Or, to any of

the plethora of topics this project pushed us to learn.

Special thanks to…

Nancy Finch, Dr. Rod Wetterskog, Ben Lardas, Gene Woten, Josh Cummings of Precision Powder

Coating, Dr. Babak Fahimi, Dr. Tim Adcock, Dr. Walt Culpepper, Shih-chin Yang, Ryan Wensel