Renesas Sensorless Vector Control (Pag 13)

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

Sensorless Vector Control and Implementation: Why and How

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

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

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Industrial, 90nm 1mA/MHz, 100µA standby

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2010 2013

32

-bit

8/16

-bit


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 λλ ×=Γ .

X

A

A’

XB

B’C’

XC

A B C

θ


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 FrameThree-phase Statorui

wi

vi

0120


Current Transformation to 2-ph Rotor Frame

Step 1 : 3-ph to 2-ph conversion

−

−−=

c

b

a

iii

ii

23

230

21

211

β

α

−

=

β

α

ii

II

q

d

cosθsinθsinθcosθ

ui

wi vi

F

Clarke Transformation

ω

uvwstationary frame

αi

βi

Fω

αβstationary frame

dIqI

Fq-axis

d-axis

Park Transformation

ω

dqrotatory 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

PIController

PIController

ω*

ω

i* i

θ

Position Estimation

i


dtdiRv s

ααα

λ+= αα θλ Lirm +Λ= cos

ββ θλ Lirm +Λ= sin

ααλθ Lirm −=Λ cos ββλθ Lirm −=Λ sin

is the rotor flux linkedmΛ

is the rotor positionrθ

Flux LinkageVoltage Equation

=0=0

Motor Model in αβ Frame

dtd

iRv sβ

ββ

λ+=

Potential Inaccuracy: If full load or large motor


Rotor Position and Speed Estimation

αλθ =Λ rm cos βλθ =Λ rm sin

)arctan(α

β

λλ

θ =r

dtdθω =

Bottleneck: arctan implementation takes several CPU cycles


Renesas Flux Observer Model

dtiRv s

t

)(0

0 αααα λλ −+= ∫

dtd

iRv sβα

βαβα

λ ,,, +=

αePotential inaccuracy: Noise in measuring current and voltage

Potential inaccuracy: Effect of temperature on resistance


βα ,e

nnn d+∗= − )1(,)(, 10241023

βαβα λλ1−−= nnn yyd

Low pass filteryn

Derivativedn

dtd

Low pass filter

βα ,110241023 eyy nn +∗= −

)(, nβαλ

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

abctoαβ

ia

ib

dqToαβ

vα

vβ

αβto

abc

Speed Estimation

θ

ωr

ω*r

id Regulatorid*=0

idiq

iqRegulatorSpeed

Regulator

Iq*

3-phInverter

6Sine PWM

DC BUS

αβtodq

iα

iβ

θ

Flux and Position Observer

ClarkePark

Park-1 Clarke-1


Implementation Challenges


High performance CPU, FPU

Implementation Challenges

1. Computation intensive routines

12Bit Simultaneous Sampling ADC2. Multiple current/voltage measurement

Noise immunity, PWM shut off3. Robust performance

On-chip analog, data flash, dual motor4. 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

PerformanceWide 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 Q11.21Single Precision Floating Point

..0..

-1038 +1038Range

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 ImplementationFixed-Point Implementation

SHIFT


No Saturation Check

Fixed-Point Implementation

Check for Saturation


Reduced Code Size

FPU ImplementationFixed-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

Multip

lexe

r

ADC Set 1

A/D

Register 2

Register CH1

Register CH2

Register CH3

ch0

PGA S/H

S/H

S/HS/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/PU,V,W

ch6

ch7

3 Input Captures

3-phase cPWM O/PU,V,W

Quadrature Encoder1A,B,Z

Quadrature Encoder2A,B,Z


Hardware Implementation

Motor Current

6PWM Generation

PWM Shut Off

PGAS/H

12-bit ADC

Analog Unit 0

RX62T

RX600CORE

x3Comparator 3

3-phase inverter

Gate Driver

MTU CH3/4

3

3-phase BLDC Motor


Software Implementation

Initialization

PWM Interrupt

Current Reconstruction

Speed PILast 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

RenesasInverter Board

RX62T Starter Kit


CPU Bandwidth Usage

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

Sine,Cosine,Atan Functions

Look-up Table

Floating PointFixed point

CPU BW


CPU Bandwidth Usage

0 10 20 30 40

PI Loop

Clarke and Park

Position Estimation

Current Measurement

Overall


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 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.CH3/410KHz

MTU.CH6/710KHz

Software Implementation 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.CH3/410KHz

MTU.CH6/720KHz

Control Loop 2

Control Loop 1


Software Implementation

Initialization

PWM Interrupt

Current Reconstruction

Speed PILast 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 DSPRX62T

16us18us

+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

Spee

d (r

pm)

time

High-end DSP

RX62T


Renesas Motor Control Solutions


Motor Control MCUs

RX600 Family-Dual motor vector control-Floating point-RX600 Motor Kit

RX62T100MHz, 165DMIPs64KB – 256KB

RX22032MHz,50DMIPs32KB-256KB

RX200 Family-Single motor vector control-Entry level RX core

Timeline

Performance

RL78/G1432MHz, 44DMIPs

32KB – 256KB

RL78/G14-Scalar control (low-end vector control)-RL78 Motor Kit

RX Core

RX63TL100MHz, 165DMIPs32KB – 64KB

RX63TH100MHz, 165DMIPs

256KB – 512KB

R8C/3xM20MHz

8KB – 128KBOct.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)

IGBTsRJH60D5DPQ-A0

Interleaved PFC

AC to DC rectifier

Line AC 85-265V

CPU Board

Gat

e D

rive

r

PWM

Hall and EncoderCurrent Sense

In-circuit Scope

LCD

Potentiometer and Push Buttons

Set RPMRPMIsIqVdc


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 sensorlessvector control and how to implement it using Renesas microcontrollers

Do you agree that we accomplished the above statement?

‘Enabling The Smart Society’

MCU

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

Renesas Sensorless Vector Control (Pag 13)

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