Motorcycle stability: riding safety improvement via ADAS and - - PowerPoint PPT Presentation

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Motorcycle stability: riding safety improvement via ADAS and semi-active applications

F.Cheli1, E.Leo2, M.E.Pezzola2, Niccolò Taroni2,

1Department of Mechanic, Politecnico di Milano (www.mecsys.mecc.polimi.it) 2Soluzioni Ingegneria, start-up of technological innovation (www.si-ita.it)

Apply & Innovate 2016 September 20-21, 2016 Karlsruhe

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MOTIVATIONS

What does stability mean? All road drive

Turist trophy

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MOTIVATIONS

Stability problems with Crossover vehicles…

Motorcycles Manufacturer Critical riding stability!

Crossover category...

Powerfull engine

More than 100 cv

Load capacity High confort level Sporting drive All road drive Off-road

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• 4.5
• 4
• 3.5
• 3
• 2.5
• 2
• 1.5
• 1
• 0.5

0.5 2 4 6 8 10 12 Real part (1/s) Imaginary part (1/s)

STATE OF ART Weave mode

Root-locus Weave is a low frequency oscillation of the entire motorcycle.

• 0.9
• 0.8
• 0.7
• 0.6
• 0.5
• 0.4
• 0.3
• 0.2
• 0.1

0.1 1 1.5 2 2.5 3 3.5 4 4.5 Real part (1/s) Imaginary part (1/s)

Speed + 50% 25% 10% 5%

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• 4.5
• 4
• 3.5
• 3
• 2.5
• 2
• 1.5
• 1
• 0.5

0.5 2 4 6 8 10 12 Real part (1/s) Imaginary part (1/s)

Wobble mode

Root-locus Wobble is a higher frequency oscillation of the steering handle around its axis.

• 3.5
• 3
• 2.5
• 2
• 1.5
• 1
• 0.5

5 6 7 8 9 10 Real part (1/s) Imaginary part (1/s)

Speed + 50% 25% 10% 5%

STATE OF ART

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MOTORCYCLE ACCIDENT CAUSE FACTORS AND IDENTIFICATION OF COUNTERMEASURES VOLUME I: TECHNICAL REPORT Traffic Safety Center University of Southern California

Accident with single-vehicle involved (25% of total accident) Weave Wobble Capsize Wide on turn Slide out Causes Young rider Experienced rider Weave and wobble DO NOT depend on rider capabilities but only on Motorcycle features. Weave Wobble

MOTIVATIONS

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• Development of Multibody model
• f motorcycle.
• Sensitivity

analysis both in straight running and steady state curve.

“Passive strategy” “Active strategy“

• algorithms

aimed to instability identification.

• semi-active

control logics to increase riding safety.

Target: Increase riding safety

MOTIVATIONS

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INDEX OF CONTENTS

ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experimental test and instability identification 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.2: Control logic 5: Conclusions

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ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experimental test and instability identification 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.2: Control logic 5: Conclusions

INDEX OF CONTENTS

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Phenomenal identification and misurability

Linear potentiometer

• n front

suspension Gyro on steering axis Accelerometer

• n handlebar

Linear potentiometer

• n rear suspension

Acquisition system Based on NI hardware GPS and IMU

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Driver shakes his hips

F

20 40 60 80 100 120 140 160 180 40 60 80 100 120 140 160 180 200 220 time [s] speed [km/h]

Speed profile Nardò Circuit

Phenomenal identification and misurability

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75 80 85 90 95 50 100 150 time [s] Speed [km/h] 75 80 85 90 95

• 40
• 20

20 40 time [s] Gyro [°/s] Channel: Gyro.

1 2 3 Damping calculation through Hilbert trasform

how is possible to evaluate an index of instability?

Motorcycles Manufacturer

Gyro on steering axis

Phenomenal identification and misurability

90 100 110

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40 60 80 100 120 140 160 180 200 220 240 5 10 15 20 25 30 Damping factor [%] speed [km/h] moto A moto B moto C

Damping factor

Is this problem generalized to whole crossover category?

Motorcycles Manufacturer

 

drivers feedback: below 5% riding can be very dangerous.

• Crossover 1
• Crossover 2
• Crossover 3

VS

• Super sport

Phenomenal identification and misurability

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60 80 100 120 140 160 180 200 220 240 5 10 15 20 25 Damping factor [%] speed [km/h] No load Full load

Damping factor

 

Is this problem related to load conditions?

Motorcycles Manufacturer

Phenomenal identification and misurability

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INDEX OF CONTENTS

ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experimental test 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.2: Control logic 5: Conclusions

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Non linear model with 12 degress of freedom 1 2 3 1 2

NUMERICAL MODEL

• 6 d.o.f. for the main frame
• 1 d.o.f. for steering rotation
• 2 d.o.f. for structural compliances

1 2 3

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• 1 d.o.f. for the rider rotation

4 5 6 4 5 6

• 1 d.o.f. for the swing arm rotation
• 1 d.o.f. for the front suspenion travel

Non linear model with 12 degress of freedom 4 5 6

NUMERICAL MODEL

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TIRE MODEL

Resulting forces:

Features... Fz Fy ϕ V α Fx

Where: ϕ = roll angle α = Slip angle

• 1° order dynamic response for Fy force
• The vertical load Fz
• The lateral force Fy
• The longitudinal force Fx

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Resulting moments:

Features... Mx Mz V α

Where: ϕ = roll angle α = Slip angle

ϕ

• 1° order dynamic response for Mz torque
• The aligning torque Mz
• The overturning moment Mx

TIRE MODEL

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INDEX OF CONTENTS

ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experimental test 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.2: Control logic 5: Conclusions

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• 20
• 15
• 10
• 5

5 10 20 30 40 50 60 Real part (1/s)

R.S. Sharp and D. Limebeer in 2001 My model

MODEL VERIFICATION

Very good corrispondence can be evidenced.

[Rad/s] [Rad/s]

wobble weave wobble weave

Straight running

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R.S. Sharp and D. Limebeer in 2001 My model

Very good corrispondence can be evidenced.

• 20
• 15
• 10
• 5

5 10 20 30 40 50 60 Real part (1/s)

[Rad/s] [Rad/s]

wobble weave wobble weave

Steady-state curve

MODEL VERIFICATION

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Experimental

• Numerical

Vehicle used for experimental test has been implemeted in the numerical model

d

Experimental

• Numerical

MODEL VERIFICATION

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INDEX OF CONTENTS

ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experimental test 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.2: Control logic 5: Conclusions

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• 3
• 2.5
• 2
• 1.5
• 1
• 0.5

4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 Real part (1/s) Imaginary part (1/s)

SENSITIVITY ANALYSIS

Legend

• +10%
• Neutral
• -10%

wobble

60 km/h 150 km/h 250 km/h

Tire pressure

• 0.8
• 0.6
• 0.4
• 0.2

0.2 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Real part (1/s) Imaginary part (1/s)

weave

+P +P

50% 25% 10% 5% 50% 25% 10% 5%

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INDEX OF CONTENTS

ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experimental test 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.2: Control logic 5: Conclusions

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CONTROLLABILITY ANALYSIS

In order to create a control logic, sensitivity analysis can evaluate the influence

• n stability of the main

tunable parameter?

How do they affect stability? Steering damper Rear suspension system Front suspension system In particular:

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Action: Which delta par. to achieve +1% of h (from initial 5% value) Increasing the value Weave Wobble Weave Wobble

Rear suspension damping Front suspension damping Steering damper

CONTROLLABILITY ANALYSIS

• 10%

+10% +60%

• 50%
• 15%

+7% none none

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INDEX OF CONTENTS

ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experiemental test 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.3: Control logic 5: Conclusions

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CONTROL LOGIC

Constant damping curves for weave and wobble At fixed speed, varying steering damping is possible to increase stability

safe

80 100 120 140 160 180 200 2 4 6 8 10 12 14 16 5% 3% 5% 3% Weave instability Wobble instability Speed[km/h] Steering damper[Nm°/s]

safe

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CONTROL LOGIC

Constant damping curves for weave and wobble adaptive steering damper Criteria:

• Low speed maneuvreability
• both weave and wobble modal damping always ≥ 5%

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80 100 120 140 160 180 200 2 4 6 8 10 12 14 16 5% 3% 5% 3% Weave instability Wobble instability Speed[km/h] Steering damper[Nm°/s]

Increasing the roll angle the safety area reduces... safe

CONTROL LOGIC

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60 80 100 120 140 160 180 20 40 2 4 6 8 10 12 14 16 Speed [km/h] Roll angle [°] steering damper [Nms/°]

Roll angle [°] Speed [km/h]

CONTROL LOGIC

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80 100 120 140 160 180 200 2 4 6 8 10 12 14 16 5% 3% 5% 3% Weave instability Wobble instability Speed[km/h] Steering damper[Nm°/s]

Optimal curve for standard vehicle is not suitable for this condition! Low tire pressure Tires condition

80 100 120 140 160 180 200 2 4 6 8 10 12 14 16 5% 3% 5% 3% Weave instability Wobble instability Speed[km/h] Steering damper[Nm°/s]

CONTROL LOGIC

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Motorcycle model

Steering damper

Gyro signal

Weave/wobble damping identificator

+

• K(Δh)

Rif (5%) H = Actual damping factor Speed (v) Roll angle (ρ)

Control MAP

Speed (v) Roll angle (ρ)

1±K(Rif - H%)

x

CONTROL LOGIC

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80 100 120 140 160 180 200 2 4 6 8 10 12 14 16 5% 3% 5% 3% Weave instability Wobble instability Speed[km/h] Steering damper[Nm°/s]

CONTROL LOGIC

Whole mass > 500 kg

145 150 155 160 165 170 175 180 3 4 5 6 7 8 5% 3% Weave instability Speed[km/h] Steering damper[Nm°/s]

k K+

Steering damper =𝑻𝟏 (1 - K (𝒊𝒔𝒋𝒈 – h))

5% 3%



Desiderable condition Both weave and wobble are in stable area

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80 100 120 140 160 180 200 2 4 6 8 10 12 14 16 5% 3% 5% 3% Weave instability Wobble instability Speed[km/h] Steering damper[Nm°/s]

CONTROL LOGIC

145 150 155 160 165 170 175 180 3 4 5 6 7 8 5% 3% Weave instability Speed[km/h] Steering damper[Nm°/s]

k K++

Steering damper =𝑻𝟏 (1 - K (𝑰𝒔𝒋𝒈 – H))

5% 3%



Critical condition Weave in more stable but wobble is critical !!

Whole mass > 500 kg

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Time-Based multibody code

• Time-based simulation
• Real-time simulation
• Simulink interface for development of control logics
• Hardware-in-the-loop testing
• Graphical user interface

CONTROL LOGIC

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CONTROL LOGIC

• 0.2
• 0.18
• 0.16
• 0.14
• 0.12
• 0.1

2.6 2.8 3 3.2 3.4 3.6 3.8 Real part [Hz] Immaginary part [Hz] 5% 3% Control OFF K=2 K=6

• 0.75
• 0.7
• 0.65
• 0.6
• 0.55
• 0.5
• 0.45
• 0.4
• 0.35
• 0.3

10.6 10.7 10.8 10.9 11 11.1 11.2 11.3 11.4 Real part [Hz] Immaginary part [Hz] 5% 3% Control OFF K=2 K=6

Weave Wobble Speed = 145km/h For an high value of the control gain, Weave damping is above 5% but wobble damping is under 3%.

K = 0 K =0.2 K = 1 K = 0.2 K = 1

+K +K 40

K = 0 K =0.2 K = 1

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CONTROL LOGIC

Weave Wobble Speed = 120km/h

• 0.9
• 0.8
• 0.7
• 0.6
• 0.5
• 0.4
• 0.3
• 0.2

9.8 10 10.2 10.4 10.6 10.8 5% 3% Real part [Hz] Immaginary part [Hz]

• 0.17
• 0.16
• 0.15
• 0.14
• 0.13
• 0.12
• 0.11
• 0.1
• 0.09
• 0.08

2.45 2.5 2.55 2.6 2.65 2.7 2.75 2.8 2.85 5% 3% Real part [Hz] Immaginary part [Hz]

During a curve the situation is more critical. For an high value of the control gain, Weave damping is above 5% but wobble damping is near 2%.

Control OFF K=2 K=6 Control OFF K=2 K=6

K = 0.2 K = 1 K = 0.2 K = 1

+K +K 41

K = 0 K =0.2 K = 1 K = 0 K =0.2 K = 1

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Speed = 155km/h

Gyro signal

Control logic with K = 0.2 is able to reduce weave instability

CONTROL LOGIC

10 12 14 16 18 20 22 24 26 28 30

• 5
• 4
• 3
• 2
• 1

1 2 3 4 5 x 10

• 4

TIme[s] [Rad/s] NO Control 10 12 14 16 18 20 22 24 26 28 30

• 5
• 4
• 3
• 2
• 1

1 2 3 4 5 x 10

• 4

TIme[s] [Rad/s] NO Control Adaptive Control K=0 10 12 14 16 18 20 22 24 26 28 30

• 5
• 4
• 3
• 2
• 1

1 2 3 4 5 x 10

• 4

TIme[s] [Rad/s] NO Control Adaptive Control K=0 Adaptive Control K=0.2

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Speed = 145km/h

10 12 14 16 18 20 22 24 26 28 30

• 1
• 0.8
• 0.6
• 0.4
• 0.2

0.2 0.4 0.6 0.8 1 x 10

• 3

TIme[s] [Rad/s] NO control K = 0 K = 1

Gyro signal

Control logic with K = 1 is NOT able to reduce weave instability and also makes wobble instable. A C B

CONTROL LOGIC

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CONTROL LOGIC

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INDEX OF CONTENTS

ACTIVE STRATEGY PASSIVE STRATEGY

1: Motivation 2 : Experimental test 3.1: Numerical model 3.2: model verification 3.3: Sensitivity analysis 4.1: controllability 4.3: Control logic 5: Conclusions

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• multibody model
• sensitivity analysis

“Passive strategy” “Active strategy“

• identify and quantify instability
• semi-active control logic

Target: Increase riding safety

CONCLUSIONS

semi-active steering damper can improve riding stability BUT a good design is foundamental in order to have a stable vehicle.

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Tires pressure Load condition

Deviation from nominal condition

Control logic is able to self recognize and be adaptative. To be investigated: what about tire wear

• r loss of efficacy of

suspension system?

FUTURE DEVELOPMENT

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Research partnership in technology innovation

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