GKN Hybrid PowerHybrid Systems : From Motor-sport to Production

Rick Townend | 07/10/14

2

[MATLAB EXPO 2014]

GKN Hybrid Power - Background

We drive the wheels

of hundreds of

millions of cars…

EMPLOYEES MILESTONES

2007 3 Automotive Hybrid Power Ltd Incorporated; Contract with

WF1 for initial flywheel dev.

2008 5 WF1 invests in AHP, renamed WHP Ltd;

F1 system rig tested;

2009 10 Porsche GT3R Hybrid developed

2010 15 Porsche GT3R Hybrid raced

2011 25 Audi eTron Quattro developed; Productionisation

investment (tech, facility)

2012 35 Bus & Tram demonstrator contracts;

TSB Gyrodrive grant awarded;

Audi eTron Quattro wins Le Mans

2013 50 Bus demo trial in London (+20% fuel save); Audi eTron

Quattro wins Le Mans again

2014 50+ GKN acquisition;

Green Bus Certificate achieved;

APC grant awarded: £5.3m, 2 year project

Prototype Proving

Development for

Production

Volume Production

2009 - 2010 2011 - 2014 2015 onwards

3

[MATLAB EXPO 2014]

Hybrid Systems : From Motor-sport to Production

4

[MATLAB EXPO 2014]

Hybrid Systems : From Motor-sport to Production

5

[MATLAB EXPO 2014]

Example Flywheel Hybrid System

6

[MATLAB EXPO 2014]

Flywheel in Le Mans 24 Hr

A Simulated Lap

Flywheel helped power the

AUDI e-tron quattro to win

the Le Mans 24 hr race

three years running (2012 -

2014)

7

[MATLAB EXPO 2014]

Model Development History

Vehicle fuel simulation model of generic SUV

Developed in association with JLR

Evaluation of fuel savings of a flywheel hybrid vehicle.

Gear

box ICE

Flywheel

Motor

Straight-line speed & torque simulation

Components

Differential, Gearbox, Engine,

Drive Motor, Flywheel

Losses

Vehicle level, Mechanical, Electrical

8

[MATLAB EXPO 2014]

Model Development History

“Backward-looking” simulation, from

drive cycle to fuel burn and electrical

energy flow

Predicted NEDC fuel consumption of

base vehicle correlated

Analysis of NEDC and Artemis cycles

9

[MATLAB EXPO 2014]

GUI development

GUI developed to aid quick changing of

simulation parameters, components and

drive cycle

Parameter files can be saved and loaded.

Separate tabs for different components.

Complete parameter file can be manually

used without GUI

10

[MATLAB EXPO 2014]

Strategy Comparisons

Different Hybrid Control Strategies were Investigated

Yellow – Basic Strategy

Purple – Low Torque Strategy

Blue – Pre Spun Basic Strategy

e.g. Basic,

Low Torque,

Engine Loading,

Flywheel Pre-Spin

11

[MATLAB EXPO 2014]

Performance Simulation

Assess hybrid capability for vehicle acceleration enhancement

Non-hybrid Range-Rover acceleration correlated to JLR supplied data

Engine Downsizing

0 – 100 kph

times

Baseline Diesel Non-Hybrid 9.4s

Downsized Engine Non-

Hybrid12.5s

Downsized Hybrid (35kW

motor)10.3s

Downsized Hybrid (70kW

motor)8.7s

3.0L Diesel non-hybrid vs

2.2L Diesel hybrid

35kW & 70kW motor with a

downsized engine &

Flywheel

12

[MATLAB EXPO 2014]

CO2 NEDC HIL Simulation

-20000

-15000

-10000

-5000

0

5000

10000

15000

20000

25000

30000

35000

0 200 400 600 800 1000 1200

Power

Real Data Model Data

0

2500

5000

7500

10000

12500

15000

17500

20000

0 200 400 600 800 1000 1200

Flywheel Speed

Real Data Model Data

0

20

40

60

80

100

120

0 200 400 600 800 1000 1200

NEDC Speed ProfileHardware in the Loop NEDC Simulation

Power input provided by Simulation

Model

Mk III Flywheel run on test dyno

Good correlation achieved

13

[MATLAB EXPO 2014]

Bus Simulation

Car fuel simulation model adapted for bus.

Data logged from CAN on non-hybrid bus.

Analysed to obtain, vehicle specific

parameters; gearbox ratios, driveline

ratios, ancillary loads and engine fuel map

Gear

box ICE

Flywheel

Motor Gearbox

MGU

14

[MATLAB EXPO 2014]

0

10

20

30

40

50

60

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500

Spe

ed

[kp

h]

Time[s]

Marylebone to Putney - light traffic

0

10

20

30

40

50

60

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500

Spe

ed

[kp

h]

Time[s]

Putney to Marylebone - heavy traffic

Bus Correlation

Model calibrated against data logged

from real vehicle and fuel economy

taken from operator’s Telematics.

Correlation work key to gaining

confidence in analysis of hybridisation

schemes

Predicted fuel saving: 19%

Results fed into the design and

specification of the Gyrodrive system.

Av = 9.1 kph

Many different hybridisation schemes and electrical

strategies tested

Not all results were as expected,

Underlined importance of simulation first.

Model predicted fuel savings were key

to Go Ahead partnering for

development of first prototype hybrid

bus.

15

[MATLAB EXPO 2014]

Performance of Gyrodrive System

Initial Gyrodrive Correlation:

Hybrid enabled model simulation

compared against CAN data from

Gyrodrive enabled bus.

Engine Torque (top chart),

Engine Speed (2nd chart)

Flywheel Speed (middle chart)

Fuel Burn (bottom chart).

All show reasonably good correlation

Av = 17.7 kph

Av = 9.1 kph

16

[MATLAB EXPO 2014]

London Bus Fuel Trials

Work is continuing on model

correlation.

Further analysis of bus data to

understand impact of

gradients and passenger load.

Current state of hybrid model

correlation (left), including

gradients.

17

[MATLAB EXPO 2014]

Multi-Flywheel Control

Large applications requiring more than one flywheel gives us scope to control the

charge/discharge cycles of each flywheel in unison and/or independently.

We simulated different methods of sharing the powers between different groupings of flywheels

to see if we could:

Lower losses

Improved availability of requested power

Improved life benefits

18

[MATLAB EXPO 2014]

Flywheel Cycling History

Matlab script was used to scan the data

files and record the cycling history of the

flywheel in a 2-d array and produce

cycling “heat map” plots.

This cycling history is used in flywheel

fatigue life estimations.

19

[MATLAB EXPO 2014]

Flywheel Efficiency Maps

Simulink model used to produce a 3D

map of Flywheel/Inverter efficiency, as a

function of flywheel speed and power.

Calibrated against test rig data

Used to aid understanding of Flywheel

behaviour and influence electrical

machine development trade-offs

20

[MATLAB EXPO 2014]

Mathworks Tool Usage

Matlab : General data analysis

Simulink : System-level models, Vehicle-level models

Future development will use simDriveline,

simPowerSystems & Stateflow

Simulink/Stateflow/Embedded Coder : Gyrodrive

Hybrid Controller, Multi-Flywheel System Controller

GKN Hybrid Power

Thank You