Sensorless Vector Control and Implementation: Why · PDF fileChallenges in implementing sensorless vector control RX62T MCU family for sensorless vector control Renesas motor control

Renesas Electronics America Inc. © 2012 Renesas Electronics America Inc. All rights reserved.

Sensorless Vector Control and Implementation: Why and How Shalabh Goyal, Marketing Manager

© 2012 Renesas Electronics America Inc. All rights reserved. 2

Shalabh Goyal

Focus : Motor control and Appliances

Title: Sr. Marketing Manager, Renesas

Experience: Mixed-signal electronics and microcontrollers for consumer and industrial markets.

Education: Ph.D. degree in EE from Georgia Institute of Technology (2002-2006)


Renesas Technology & Solution Portfolio


Microcontroller and Microprocessor Line-up

Wide Format LCDs Industrial & Automotive, 130nm

350µA/MHz, 1µA standby

44 DMIPS, True Low Power

Embedded Security, ASSP

165 DMIPS, FPU, DSC

1200 DMIPS, Performance 1200 DMIPS, Superscalar

500 DMIPS, Low Power

165 DMIPS, FPU, DSC

25 DMIPS, Low Power

10 DMIPS, Capacitive Touch

Industrial & Automotive, 150nm

190µA/MHz, 0.3µA standby

Industrial, 90nm


Automotive & Industrial, 90nm


Automotive & Industrial, 65nm

600µA/MHz, 1.5µA standby Automotive, 40nm

500µA/MHz, 35µA deep standby

Industrial, 40nm


Industrial, 90nm

1mA/MHz, 100µA standby

Industrial & Automotive, 130nm


2010 2013

32

-bit

8

/1

6-b

it


Challenge: Sensorless vector control increases the energy efficiency of motor control systems that drive the smart society. However, understanding and implementing sensorless vector control is a herculean task.

Solution:

This class will help you understand key challenges associated with sensorless vector control and how to implement it using Renesas microcontrollers

‘Enabling The Smart Society’

MCU


Agenda

Need for vector control

Theory behind vector control

Challenges in implementing sensorless vector control

RX62T MCU family for sensorless vector control

Renesas motor control solutions


Macro Factors Driving Need for Energy Efficiency

Global Environmental Concerns

Energy Efficiency Policies

New Initiatives


Realizing Energy Efficiency in Motor Control

Industrial 44% Residential 26% Others 30%

Energy Efficient Motors

Electronic Control

Variable speed drives

Vector control

Direct torque control

Power factor correction

Motor Design

Motor Type

Up to ~30% savings

15% 20%

Motors (45%)


Sensorless Vector Control Theory


Permanent Magnet AC Motor

Complex Control

Sinusoidal stator current produces rotating field

Rotor mounted magnetic field is rotating

Maintain stator field orthogonal to rotor field

rsk .

X

A

A’

X B

B’ C’

X C

A B C


Vector Control Challenge

Maintain orthogonality

Error correction feedback loop

– In-phase current = 0

– Orthogonal current set per torque requirements

What parameters to adjust

Voltage magnitude (PWM duty cycle)

Need to transform current vectors to rotor frame

Rotor Field

Stator Field

900

ωr


Reference Frame Transformation

Vector control advantages

Maximizing torque (efficiency)

Independent control of flux and torque

Snappy torque control for load variation

Mapping

qi

di

2-phase Rotor Frame Three-phase Stator

u i

w i

v i

0 120


Current Transformation to 2-ph Rotor Frame

Step 1 : 3-ph to 2-ph conversion

c

b

a

i

i

i

i

i

2

3

2

30

2

1

2

11

i

i

I

I

q

d

cosθsinθ

sinθcosθ

u i

w i v i

F

Clarke Transformation

w

uvw

stationary frame

i

i

F w

αβ

stationary frame

d I

q I F q -

axis

d - axis

Park Transformation

w

dq

rotatory frame

Step 2 : 2-ph stationary frame to 2-ph rotor frame (rotating)

Rotor position (θ) needed


Sensorless Vector Control

Lower cost but more complex implementation

Current and motor parameters to estimate rotor position

Increased reliability

Reduced cost of sensor ($3-$20)

Less physical space needed

Need to estimate θ without sensors

Speed

/position

sensor

Speed

Calculation

Motor

PWM

Generation PI

Controller

PI

Controller

ω*

ω

i* i

θ

Position

Estimation

i


dt

diRv s

Lirm cos

Lirm sin

Lirm cos Lirm sin

is the rotor flux linked m

is the rotor position r

Flux Linkage Voltage Equation

=0 =0

Motor Model in Frame

dt

diRv s

Potential Inaccuracy: If full load or large motor


Rotor Position and Speed Estimation

rm cos rm sin

)arctan(

r

dt

dw

Bottleneck: arctan implementation takes several CPU cycles


Renesas Flux Observer Model

dtiRv s

t

)(0

0

dt

diRv s

,

,,

e

Potential inaccuracy: Noise in measuring current and voltage

Potential inaccuracy: Effect of temperature on resistance


,e

nnn d )1(,)(,1024

1023 1 nnn yyd

Low pass filter

yn

Derivative

dn

dt

d

Low pass filter

,11024

1023eyy nn

)(, n

Cascaded low pass filters rather than direct integration

First low pass filter

Derivative

Second low pass filter

Negate the effect of DC offset in measured current/voltage

Flux Observer Implementation


Sensorless Vector Control Loop

abc to αβ

ia

ib

dq To αβ

vα

vβ

αβ to

abc

Speed Estimation

θ

ωr

ω*r

id Regulator id*=0

id iq

iq Regulator

Speed Regulator

Iq*

3-ph Inverter

6 Sine PWM

DC

BUS

αβ to dq

iα

iβ

θ

Flux and Position Observer

Clarke Park

Park-1 Clarke-1


Implementation Challenges


High performance CPU, FPU

Implementation Challenges

1. Computation intensive routines

12Bit Simultaneous Sampling ADC

2. Multiple current/voltage measurement

Noise immunity, PWM shut off

3. Robust performance

On-chip analog, data flash, dual motor

4. Cost effective design

Requirements MCU Considerations


1. Computation Intensive

High-performance RX600 Core

100MHz CPU

1-cycle flash access

32x32 H/W multiplier

32/32 H/W divider

32bit Barrel Shifter

Floating point unit

• Clarke/Park Transformations

• Flux Estimation

• Rotor position and speed


Floating Point Unit Advantages

Performance

Wide range and high resolution

No scaling, overflow or saturation

Reduced code size

Ease of Use

Ease of coding, reading, debugging

Compatible with the C/Matlab simulation code


Floating Point : Range and Resolution

-210

-103

+210

+103

Range

Resolution 2-21

10-7

..0..

Fixed Point Q11.21 Single Precision

Floating Point

..0..

-1038 +1038 Range

Resolution 10-39

∫ or ∑


Fixed-point Calculations Requires Scaling

X(n) = X(n-1) + A1 * E(n)

(16b, Q12.4) (16b, Q8.8) (32b,Q14.18)

(32b,Q20.12)

(32b,Q14.18)

MULT

SHIFT

(32b,Q14.18)


No Scaling Needed

FPU Implementation Fixed-Point Implementation

SHIFT


No Saturation Check

Fixed-Point Implementation

Check for

Saturation


Reduced Code Size

FPU Implementation Fixed-Point Implementation

FPU instructions make code and the execution time smaller


Readability

Fixed-Point Implementation FPU Implementation

Parameters Parameters

Park Transformation Code Park Transformation Code


FPU Brings Ease of Simulation

•Portable to FPU

•Bidirectional

•Time-consuming

•Unidirectional

Simulation Platform

Inherently

floating point

Floating Point Algorithm

Fixed Point CPU

Fixed Point Algorithm

Floating Point CPU


FPU Implementations

No Load/Store Instructions

Renesas RX FPU

Floating-Point Unit

Dedicated Data Registers

General Registers

Traditional FPU

Load/Store

General Registers

Floating-Point Unit


2. Accurate Analog Signal Measurement

Simultaneous sampling ADC

Oversampling current waveform

Filtering to mitigate noise

Dual registers for 1-shunt

U

V

W

50us

5us

4 ADC Samples

• Estimates based on current and voltage

• Integration for flux estimation

• Multiple simultaneous measurements


Current Measurement Techniques

3-shunt

U

V

W

IW IW+IV

1-Shunt Advantages

Cost reduction (Res, PGA)

No need for 3-ph calibration

Reliability

1-shunt Challenges

ADC samples twice quickly

Reconstruction of current

1-shunt

IW,V,U


Support for 3-shunt and 1-shunt Detection

AN0

AN1

AN2

Mul

tipl

exer

ADC Set 1

A/D

Register 2

Register CH1

Register CH2

Register CH3

ch0

PGA S/H

S/H

S/H S/H

External Reference

3 S/H for 3 shunt current detection

AN03/CVref L

Register 1

Double register for 1-shunt

12-bit ADCs with 1us conversion time

Double register for 2 samples

3S/H for one-shot sampling of three phase currents

Self-diagnostic capability for UL/IEC safety requirements

PGA

PGA

Window Comparators

CPU Interrupt

PWM Shut off (POE)


3. Robust Performance

Noise immune MCU design

Careful power/ground layout

Pin noise filtering

5V option

On-chip hardware

POE circuit

Fast window comparators

• Susceptibility to noise

• Hardware shut off


4. Cost Effectiveness

Complete solution for driving two 3-ph

motors

6 programmable gain amplifiers

6 window comparators

2 x 3ph cPWM timers

2 x quadrature encoder inputs

Data flash

Scalability

RX6xT – package, ROM

RX200 - performance

• On-chip integration

• Scalability

48-144 pins

32-512KB

63TL

62T

63TH

Scalability


Implementing Sensorless Vector Control Using RX62T


RX62T Motor Timer Set (MTU3)

100MHz, 16bit Timers

Protection Features PWM shut down (Ext, Comparator,

Clock)

Mode registers inaccessible during operation

ch0

ch1

ch2

ch3

ch4

ch5

MTU3

3-phase cPWM O/P U,V,W

ch6

ch7

3 Input Captures

3-phase cPWM O/P U,V,W

Quadrature Encoder1 A,B,Z

Quadrature Encoder2 A,B,Z


Hardware Implementation

Motor

Current

6

PWM Generation

PWM Shut Off

PGA S/H

12-bit ADC

Analog Unit 0

RX62T

RX600 CORE

x3 Comparator 3

3-phase inverter

Gate Driver

MTU CH3/4

3

3-phase BLDC

Motor


Software Implementation

Initialization

PWM Interrupt

Current Reconstruction

Speed PI Last ω &

Reference ω

V(u,v,w) -> PWM Duty

New θ Estimation

New Speed Estimation

Current PI

Voltage (d,q)

VBUS/Current Measurement

(u,v,w) -> (α,β) ->(d,q)

Last θ

Reference

Current

Actual

Current

(d,q) -> (α,β) (u,v,w) <-

Last θ


Fixed point vs. FPU Comparison

Algorithm: Sensor less Vector Control with 1-Shunt Current Detection

PWM Carrier Frequency: 20kHz

Current Loop: 10kHz

Renesas

Inverter Board

RX62T

Starter Kit


CPU Bandwidth Usage

0% 5% 10% 15% 20% 25% 30% 35% 40%

Sine,Cosine,Atan Functions

Look-up Table

Floating Point

Fixed point

CPU BW


CPU Bandwidth Usage

0 10 20 30 40

PI Loop

Clarke and Park

Position Estimation

Current Measurement

Overall

Floating Point

Fixed point

us

Floating-point code 40% faster


Code Size

0 50 100 150 200 250

PI Loop

Clarke and Park

Position Estimation

Current Measurement

Floating Point

Fixed point

Floating-point code size is 45% lower

B


Driving Two 3-Phase BLDC Motors

RX600 Motor Kit External Inverter

www.renesas.com/rxmotorkit

Motor #2 Motor #1

Sensorless Vector Control

Floating point math

CPU BW used <50%


Implementation for Two Motor Control

Control

Loop 1

Control

Loop 2

CPU Available

MTU.CH3/4

10KHz

MTU.CH6/7

10KHz


Control loop executed at Timer underflow interrupt

Both interrupts at same priority level

Alternate Implementations

Control loops at different rates

Interrupt at overflow/underflow

MTU.CH3/4

10KHz

MTU.CH6/7

20KHz

Control

Loop 2

Control

Loop 1



Initialization

PWM Interrupt

Current Reconstruction

Speed PI Last ω &

Reference ω

V(u,v,w) -> PWM Duty

New θ Estimation

New Speed Estimation

Current PI

Voltage (d,q)

VBUS/Current Measurement

(u,v,w) -> (α,β) ->(d,q)

Last θ

Reference

Current

Actual

Current

(d,q) -> (α,β) (u,v,w) <-

Last θ

PWM Interrupt2


Performance Comparison with a High-end DSP

RX62T offers tremendous value

Comparable performance

Significantly lower cost

Loop execution

Code size

System Cost

High-end DSP

RX62T

16us

18us

+50%

7.8KB

7.4KB


Response to Step Change in Load

950

960

970

980

990

1000

1010

1020

1030

1040

1050

0.265 6.343 22.906

Sp

ee

d (

rpm

)

time

High-end DSP

RX62T


Renesas Motor Control Solutions


Motor Control MCUs

RX600 Family

-Dual motor vector control

-Floating point

-RX600 Motor Kit RX62T 100MHz, 165DMIPs

64KB – 256KB

RX220 32MHz,50DMIPs

32KB-256KB

RX200 Family

-Single motor vector control

-Entry level RX core

Timeline

Performance

RL78/G14 32MHz, 44DMIPs

32KB – 256KB

RL78/G14

-Scalar control (low-end

vector control)

-RL78 Motor Kit

RX Core

RX63TL 100MHz, 165DMIPs

32KB – 64KB

RX63TH 100MHz, 165DMIPs

256KB – 512KB

R8C/3xM 20MHz

8KB – 128KB Oct.2012


Evaluation Kits for Vector Control

Extensive Code Support

Flexibility to Evaluate and Develop

GUI

External Inverter Connector

RX600 Motor Kit RL78 Motor Kit

http://www.renesas.com/rxmotorkit

http://www.renesas.com/rxmotorkit


High Voltage Demo Platform (2KW)

IGBTs RJH60D5DPQ-A0

Interleaved PFC

AC to DC rectifier

Line AC

85-265V

CPU Board

Gate

D

river

PWM

Hall and Encoder

Current Sense

In-circuit Scope

LCD

Potentiometer and

Push Buttons

Set RPM RPM Is Iq Vdc


2KW Inverter Platform


Summary

Sensorless vector control improves the motor system efficiency

Implementing sensorless vector control requires careful selection of MCU

Renesas provides several motor control MCUs depending on the application requirements

RX600 and RL78 motor control kits are available for an easy evaluation of Renesas solutions

High voltage platforms are also available


Questions?


Challenge: Sensorless vector control increases the energy efficiency of motor control systems that drive the smart society. However, understanding and implementing sensorless vector control is a herculean task

We discussed key challenges associated with sensorless vector control and how to implement it using Renesas microcontrollers

Do you agree that we accomplished the above statement?

‘Enabling The Smart Society’

MCU


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Renesas Electronics America Inc.

© 2012 Renesas Electronics America Inc. All rights reserved.

Documents

Sensorless Vector Control and Implementation: Why · PDF fileChallenges in implementing sensorless vector control RX62T MCU family for sensorless vector control Renesas motor control