Hindawi Publishing Corporation

EURASIP Journal on Embedded Systems

Volume 2009, Article ID 161373, 10 pages
doi:10.1155/2009/161373

Research Article
Traction Control System for Motorcycles

Pascal Cardinale, Camillo D’Angelo, and Massimo Conti

Dipartimento di Ingegneria Biomedica, Elettronica e Telecomunicazioni, Università Politecnica delle Marche,
Via Brecce Bianche, 60121 Ancona, Italy

Correspondence should be addressed to Massimo Conti, m.conti@univpm.it

Received 31 August 2008; Accepted 23 October 2008

Recommended by Markus Kucera

Traction control is a widely used control system to increase stability and safety of four wheel vehicles. Automatic stability control is
used in the BMW K1200R motorcycle and in motoGP competition, but not in other motorcycles. This paper presents an algorithm
and a low-cost real-time hardware implementation for motorcycles. A prototype has been developed, applied on a commercial
motorcycle, and tested in a real track. The control system that can be tuned by the driver during the race has been appreciated by
the test driver.

Copyright © 2009 Pascal Cardinale et al. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.

1. Introduction surface [1–8]. Such control schemes are motivated by the fact
that the system is nonlinear and uncertain.
Traction control is a widely used control system in automo- Recently, a lot of work in the definition of traction control
tive applications to increase stability and safety of vehicles. algorithms for electric vehicles (EV) has been developed [9–
Well-known vehicle control systems such as antilock brake 15]. In EV, the torque generation is very quick and accurate,
system (ABS), antiSlip regulation (ASR), and electronic both for accelerating and decelerating. The torque control
stability program (ESP) are used in internal combustion of each wheel is ensured by the inverter, and it does not
engine vehicles (ICVs). require a mechanical differential gear. The electronic control
Traction control prevents the vehicle from swerving of the torque and of the speed of each one of the four
when accelerating on a loose surface, reduces engine output independent wheels allows the EV to operate more efficiently
until the vehicle can move without the wheels skidding, and avoiding slippage. Furthermore, an efficient control of the
produces maximum stability when cornering especially in torque allows an increment of the energy efficiency of the
wet or icy roads. vehicle.
A conventional differential does not usefully distribute The application of traction control to motorcycles is not
the torque to the wheels when a wheel is skidding. All the so widely used as to four wheel vehicles, probably because of
power is applied to the skidding wheel and not to the wheel the high cost of the control system.
that has more traction. An electronic traction control system BMW and Kawasaky were the first companies that
prevents a wheel from skidding by applying a brake to that applied ABS to motorcycles. BMW is the unique company
wheel, enabling the differential to apply power to the other that is using an automatic stability control (ASC) system
wheel. in top high-torque BMW K1200R commercial model from
The control scheme is composed by a device that 2007. BMW ASC prevents the rear wheel from skidding
estimates the road surface condition and a traction controller uncontrolled when accelerating, and thus it avoids any loss
that regulates the wheel slip at desired values. Several of side forces and stability [16, 17].
control strategies have been proposed in the literature mainly Additional sensors have been inserted to the BMW
based on sliding mode controllers, fuzzy logic, and adaptive K1200R motorcycle in order to determine the speed at which
schemes to control four wheels vehicles moving in sliding each wheel is turning, as shown in Figure 1. A high number
2 EURASIP Journal on Embedded Systems

Figure 1: Particular of BWM K1200R. Figure 3: Hall sensor and bolts in the MotoGP Yamaha M1.

This paper presents a new algorithm and its hard-

ware implementation on low-cost real-time embedded sys-
tem implementing traction control for supermotard or
motocross motorcycles. A key innovative feature, proposed
in this work, is that the control of the torque is obtained
introducing a cut in the ignition spark using a switch
in parallel to the switch used to turn off the engine.
Blot Therefore, the torque control is obtained without modifying
the ignition controller and it can be applied to every existing
commercial motorcycle.
Hall sensor Furthermore, supermotard or motocross motorcycles do
not move always on asphalt, and the condition of the ground
Figure 2: Hall sensor and bolts in the MotoGP Ducati racing. can change very rapidly. Therefore, the driver must tune the
traction control on the fly.
Therefore, the driver must tune the traction control on
the fly. This is allowed by the algorithm and architecture
of pick-up points for the wheel speed sensor give a high proposed in this work.
resolution to the data, enabling a traction control system Section 2 reports a brief description of problems related
to react faster. The BMW K1200R uses about 100 pick-up to the traction control of motorcycles. The proposed archi-
points in the wheel, the holes evidenced by the arrow in the tecture, the control algorithm, and the performance analysis
particular of Figure 1, in order to have an accurate precision of the system are presented in Section 3. Section 4 reports
in the speed estimation required for the ABS, and the same some experimental results obtained in a race track.
information is used by the ASC system.
Registering any sudden change in the difference in speed
front-to-rear, the electronic control unit is able to detect 2. Traction Control for Motorcycles
any risk of the rear wheel skidding, engine management
responding immediately by intervening in the ignition angle Critical conditions in driving a motorcycle are the rearing
to take back engine power [16, 17]. up or when the motorcycle is in bend. The objective of the
Traction control systems are used in motoGP (e.g., proposed control system is to help the driver in maintaining
Yamaha and Ducati), to improve the ability in driving the a secure control of the motorcycle in rearing up and in bend.
motorcycle during competitions [18]. In Ducati motoGP, the In both cases, the excessive torque of the engine on the rear
wheel speed is measured using hall effect gear tooth sensors, wheel may cause the loss of control of the motorcycle.
see Figure 2, in a way similar to the one used in this work. Figure 4 shows an example of a rearing up, it happens
The Ducati motoGP uses 8 pick-up points (the bolts). when the motorcycle is not in bend and the torque is too
The motoGP Yamaha M1 has sensors on each side of high. In this case, the speed of the rear wheel is greater than
the wheel, for redundancy. The solid disc used, as shown the speed of the front wheel.
in Figure 3, is a magnetic ring element, into which a strip The driver can avoid rearing up, reducing the opening of
of small magnets is embedded for more data points and the butterfly valve controlling the accelerator.
accuracy than a toothed ring. Figure 5 shows an example of a motorcycle in a critical
The details on the traction control systems used in situation in bend. In this case, the front wheel is closer to
motoGP and by BMW, in our knowledge, are not available. the centre of the bend with respect to the rear wheel that is
Traction control systems are not used in other commercial going faster and more and more far from the centre of the
motorcycles or in supermotard or motocross motorcycles. bend. In this situation, the driver can loose the control of the
EURASIP Journal on Embedded Systems 3

Engine turn off

manual switch

Sparking
controller

Sparking
coil
Sparking
pulse
Figure 4: Rearing up.
generator
Spark
coil
plug
Alternator

Figure 6: General scheme of a sparking controller.

Engine turn off Sensors

manual switch
Traction
control

Sparking
Figure 5: Motorcycle in bend. controller

Sparking
motorcycle. To avoid this, the driver should reduce the torque coil
in order to reduce the speed of the rear wheel. Sparking
In both cases, the objective of the traction control is to pulse
reduce the torque on the rear wheel in order to keep equal generator
Spark
the speed of the two wheels. To do this, an estimation of the coil
plug
speed of both the wheels must be performed using specific Alternator
sensors.
Figure 7: Proposed modification of sparking controller with
traction control.
3. Traction Controller Architecture
The main specification of the proposed system is its simple
applicability to existing motorcycle independently on the This switch is controlled by a microcontroller on the basis of
different ignition control system. the output of some additional sensors, as shown in Figure 7.
The torque applied to the rear wheel can be controlled The effect of the traction controller is shown in Figure 8.
reducing the gasoline injected closing the butterfly valve In the top of the figure, the voltage applied to the spark plug
or reducing the electrical current to the sparking plug. during a normal sparking is reported, in the bottom, a cut in
The former cannot be easily obtained without changing the pulse, introduced by the traction controller, can be seen.
the injection controller, while the latter has been simply The cut on the electrical current of the spark plug is
obtained, as it will be shown in this section. obtained in two ways: defining the cut off delay between the
Figure 6 shows a general scheme that gives the electrical start of the ignition spark and the intervention of the traction
current to the sparking plug. Every motorcycle has a manual control, as shown in Figure 8, and defining the number of
switch used to turn off the engine; the switch simply bypasses consecutive ignition sparks for which the traction control
to ground the electrical current flowing in the sparking coil. takes action, an example is shown in Figure 9. The ignition
The proposed system modifies the sparking scheme inserting spark cut off, imposed by the traction controller, modifies
an additional switch in parallel to the manual turn off switch. the torque applied to the wheel.
4 EURASIP Journal on Embedded Systems

Front wheel Interrupt

speed sensor Flash
RAM
15
Rear wheel Interrupt
speed sensor RS232
Voltage applied
(kV)

10 to the spark plug

Interrupt

Microcontroller
Sparking
Display

PIC18F6527
5
Rolling angle
sensor Sensitivity
and
Butterfly valve duty cicle
10 20 30 40 50 opening sensor manual
settings
Time (μs)
Engine r.p.m.
sensor

15

Ignition
Voltage applied current cut
(kV)

10 to the spark plug

with traction control
Figure 10: Architecture of the traction controller.
5
Cut off delay
controller. An RS232 interface is used to communicate with
an external PC when the motorcycle is parking.
10 20 30 40 50
Time (μs)
3.1. Wheel Speed Sensors. The wheel speed is measured using
Figure 8: Voltage applied to the sparking plug (top) without hall effect gear tooth sensors. The sensor output voltage
traction control and (bottom) with traction control. is 5 V when the sensor is in proximity to a ferromagnetic
material, otherwise the output voltage is 0.2 V. The hall
sensor is placed close to the 4 ferromagnetic bolts of the
Low traction control intervention wheel of our motorcycle, as shown in Figure 11. During
wheel rotation, the sensor sends a pulse when the bolt is
close to the sensor. The time interval between two pulses is
Time inversely proportional to the angular speed of the wheel. The
High traction control intervention wheel speed is estimated knowing the time interval between
the pulses, the effective diameter of the tyre, and the number
of bolts in each wheel. Figure 11 shows the sensor applied to
Time the front and rear wheels in our prototype.
Figure 9: Examples of low and high traction control intervention
The same principle is applied in the BMW K1200R.
on the ignition spark.
3.2. Rolling Angle Sensors. The wheel speed estimation
depends on the rolling angle of the motorcycle and other
parameters like tyre, pressure, and temperature. Figure 12
The complete architecture of the traction control system shows the effect of the rolling angle on the effective
is reported in Figure 10. tyre diameter. An increment in the rolling angle causes a
The core of the control algorithm is implemented in a reduction of the effective diameter of the wheel and therefore
40 MHz Microchip PIC18F6527 microcontroller. a reduction in the wheel speed.
Six sensors are added to give information on the situation The difference between the nominal and effective tyre
of the motorcycle to the controller: front wheel speed diameter in bend can be higher than 10% considering that
sensor, real wheel speed sensor, sparking signal, rolling the motorcycle in bend can have a rolling angle higher
angle sensor, butterfly valve opening sensor, and engine than 60◦ and the distortion of the part of the wheel that
r.p.m. sensor. The driver can modify the parameters of the touches the ground during the bend. Furthermore, this
controller pushing few buttons even driving the motorcycle. difference depends on the tyre pressure, temperature, and
The microcontroller stores information on a 1 Mbyte flash consumption. The error on the wheel speed estimation due
memory with the purpose of monitoring the performances to this effect is not negligible, therefore, a rolling sensor of
of the control system. A display is placed in the motorcycle the VTI technologies has been inserted and the information
to allow the driver to verify in real time the status of the are used in the algorithm for the wheel speed estimation.
EURASIP Journal on Embedded Systems 5

Start

Sensitivity ε setting

Cut step δ setting

Tyre diameter setting

Wheel bolt number setting

Err = 0; prev err = 0; c = δ

Sensor Front wheel speed estimation

Blot

Rear wheel speed estimation

Engime r.p.m. acquisition

Rolling angle estimation

Err = front speed − rear speed

Blot
No
Sensor Err>ε ?

Yes
Figure 11: Hall sensor and one of the bolt in the front and rear
wheels. Prev err≤err ?
Yes No

c = max(c − δ, 0) c = min(c + δ, 10 ∗ δ)
Vertical tyre Tyre deformation
Rolling angle
Ignition spark cut of c steps

Tyre Prev err = err

diameter
Effective
tyre
diameter Figure 13: Control algorithm implemented in the microcontroller.

Figure 12: Dependence of the rolling angle on the effective tyre.

the minimum increment or decrement of the cut off delay
represented in Figure 8. When the ignition cut c is higher
3.3. Butterfly Opening Sensor and Engine r.p.m. Sensor. The than a fixed value, the ignition spark is completely eliminated
opening of the butterfly has been measured with a precision and the width of the successive ignition spark is reduced,
potentiometer of Vishay company connected to the accelera- as shown in Figure 9. The complete elimination up to three
tor cable. The r.p.m. of the engine is indispensable to measure successive sparks does not have effect on the driving, as it has
the torque and the power of the engine. been verified by experimental results in a real track.
The parameter ε defines the value of difference between
front wheel speed and rear wheel speed for which the traction
3.4. Electrical Current Switch. Different solutions have been control system takes action. This parameter depends on the
studied to obtain a cut in the electric current of the sparking driver style of drive and on the ground conditions (asphalt or
plug. An electromechanic relay of multicomp was not fast ground, wet or dry). The front wheel speed and rear wheel
enough to obtain a shape similar to the one shown in speed are estimated, as reported in subsections 3.1 and 3.2,
Figure 8. The solution chosen is an IGBT. and their difference is used to calculate the width of the
cut on the electrical current of the spark plug. When the
3.5. Microcontroller and Control Algorithm. The control microcontroller receives an interrupt from the wheel speed
algorithm used is shown in Figure 13. The parameter settings sensors, it evaluates if the ignition spark cut must be done
are stored in the memory, but they can be modified by and the cut off delay. When it receives the interrupt from
the driver during the race using push-buttons to increment the sparking signal that indicates that the ignition spark
or decrement the values of ε and δ. The parameter δ is started, it eventually waits for a time equivalent to the cut off
6 EURASIP Journal on Embedded Systems

(ms)

(ms)

(ms)
Number of Number of Number of
bolts: 3 150 bolts: 4 150 bolts: 8 150

spikes of the wh between two

spikes of the wh between two

spikes of the wh between two

eel speed sensor

eel speed sensor

eel speed sensor

100 100 100

Time interval

Time interval

Time interval
4 50 4 50 4 50
8 8 8
12 12 12
a(

a(

a(
0 0 0
m/

m/

m/
16 5 16 5 16 5
s2 )

s2 )

s2 )
20 15 20 15 20 15
25 s) 25 s) 25 s)
V0 (m/ V0(m/ V0 (m/

(a) (b) (c)

Figure 14: Time interval between two spikes of the wheel speed sensor.

Number of Number of Number of

bolts: 3 16 bolts: 4 16 bolts: 8 16
imation (%)

imation (%)

imation (%)
12 12 12
Error on speed est

Error on speed est

Error on speed est

8 8 8
4 4 4
8 4 8 4 8 4
12 12 12
a(

a(

a(
0 0 0
m/

m/

m/
16 5 16 5 16 5
s2 )

s2 )

s2 )
20 15 20 15 20 15
25 s) 25 s) 25 s)
V0(m/ V0 (m/ V0 (m/

(a) (b) (c)

Figure 15: Relative error on speed estimation.

delay and operates the ignition spark cut. The algorithm has 14
been translated in assembly code and implemented in the 12
Microchip PIC18F6527 microcontroller with 40 MHz clock, 10 Effective
10 MHz bus clock, and 100 nanoseconds instruction time. Estimated wheel speed (m/s)
The maximum time required to generate the cut has been 8
wheel speed (m/s)
estimated. 6
4
(i) Front wheel speed estimation 4.7 microseconds
2
(ii) Rear wheel speed estimation 4.7 microseconds.
0
(iii) Rolling angle estimation 38.0 microseconds. 0 0.5 1 1.5 2
(iv) Butterfly opening estimation 10.0 microseconds. Time (s)

(v) Engine r.p.m. estimation 4.7 microseconds. Figure 16: Effective and estimated wheel speed in a simulation of a
curve with 8 bolts for wheel.
(vi) Err calculus 118.8 microseconds.
(vii) Total time 176.7 microseconds.
The time required for the traction control by the microcon- The critical aspect of the traction control system is the
troller is, therefore, negligible compared with the minimum number of bolts in each wheel and not the computation time
time between two consecutive ignition sparks (180 millisec- of the microcontroller. The distance Δx covered by the wheel
onds for 20000 r.p.m.) and with the average time interval in the time interval Δt between two pulses of the hall effect
between two pulses coming from the hall sensor used to sensor is
estimate the wheel speed (about 20 milliseconds for a speed
of 20 m/s). Therefore, the digital controller implemented is πd
Δx = , (1)
able to control in real time the traction of the motorcycle. n
EURASIP Journal on Embedded Systems 7

80
Time interval between two spikes

Absolute value of the error on

of the wheel speed sensor (m/s)

250

speed estimation (%)

Number of bolts = 3
200 60
Number of bolts = 3 n=4
150 40
n=4
100 n=8
20
n=8
50
0
0 0 0.5 1 1.5 2
0 0.5 1 1.5 2
Time (s)
Time (s)
Figure 18: Absolute value of the relative error between estimated
Figure 17: Time interval between two spikes of the wheel speed and effective speed for different number of bolts in the simulation
sensor for different number of bolts in the simulation example of example of Figure 16.
Figure 16.

where n is the number of bolts, and d is the effective

diameter of the wheel, considering the rolling angle effect. As
an example, let us consider the case of a constant acceleration
a starting from an initial speed vo . In this case, the following
relationship is valid:
1
Δx = aΔt 2 + vo Δt. (2)
2
Therefore, using (1) and (2), it results

vo 2 πd vo
2
+2 − . Δt = (3)
a na a
The value of Δt in (3) is the sampling time of the speed Figure 19: Traction control board applied in a supermotard
estimate and it is the delay with which the control system motorcycle.
knows the wheel speed.
Figure 14 reports the value of Δt in milliseconds as
a function of the acceleration and of the velocity vo for where
different values of the number of bolts of the wheel for a 
wheel diameter of 60 cm. πd
v(Δt) = vo 2 + 2a . (7)
It can be seen that the delay of the control system (177 n
microseconds) is three-order of magnitude less than Δt.
Conversely Δt is of the same order of magnitude of the The error is reduced by increasing the number of bolts
time interval between two consecutive ignition sparks, which (4 is the minimum acceptable), it increases for strong
depends on the engine r.p.m. acceleration and low values of speed. Figure 15 reports the
A reduction of Δt can be obtained increasing the number value of Δv(%) as a function of the acceleration and of
of bolts, but this solution is expensive. The BMW K1200R the velocity vo for different values of the number of bolts
motorcycle uses 100 of pick-up points for wheel speed of the wheel for a wheel diameter of 60 cm. This error
estimation, while the Ducati motoGP uses 8 pick-up points depends on speed and acceleration; therefore it reduces the
(the bolts). efficiency of the traction control system since it can be
The speed estimation vE performed by the microcon- only partially compensated by an appropriate tuning of the
troller is control parameters.
To verify the error on speed estimation in practical
Δx cases, a simple numerical simulator has been developed.
vE = . (4)
Δt Figure 16 reports the effective and estimated wheel speed in
Using (3), we obtain a simulation example of a curve with 8 bolts for wheel.
πd /n Figure 17 reports the time interval between two spikes of
vE =    . (5) the wheel speed sensor for different number of bolts in the
vo 2 /a2 + 2 πd /na − vo /a same example, while Figure 18 shows the absolute value of
The maximum relative error between the speed estimation the relative error between estimated and effective speed for
vE and the effective speed is different number of bolts.
When the motorcycle is exiting from the curve, the speed
v(Δt) − vE is low and the acceleration is high and the error due to a
Δv(%) = 100, (6)
v(Δt) reduced number of bolts is critical.
8 EURASIP Journal on Embedded Systems

40 40

No TCS Soft TCS

30 30
Rear wheel Rear wheel
Wheel speed (m/s)

Wheel speed (m/s)

Front wheel Front wheel
20 20

10 10
Butterfly valve Max Butterfly valve Max

Min Min
0 0
0 1 2 3 4 5 6 0 1 2 3 4 5 6
Time (s) Time (s)
(a) (b)

40

Strong TCS

30
Rear wheel
Wheel speed (m/s)

Front wheel
20

10
Butterfly valve Max

Min
0
0 1 2 3 4 5 6
Time (s)
(c)

Figure 20: Wheel speed and butterfly valve opening for a rearing up test. Without traction control, with traction control “soft control”
setting and “strong control” setting.

4. Experimental Results The system has also been tested by the Supermoto rider
Attilio Pignotti: 2nd in Supermoto S2 World Championship
The system has been implemented and applied to a com- in 2007, 10th in Supermoto S2 World Championship in 2006,
mercial supermotard motorcycle, shown in Figure 19, in and 8th in Supermoto S2 World Championship in 2005.
Figure 4, and in Figure 11. The results in a rearing up and with the motorcycle in
The traction control system has been tested by the bend are reported in this section.
authors in the racing track “Enzo e Dino Ferrari” of Figure 20 shows three cases of rearing up starting from
Fermo, Italy. Some results are shown in this section. The 0 m/s to 40 m/s in a straight track, in a situation similar to
experimental data have been stored in the flash memory the photo in Figure 4. With the accelerator in the maximum
during the test in the racing track and then transferred on position, the motorcycle rears up, and the speed of the rear
a PC using the RS232 interface at the end of the race. wheel is higher with respect to the front wheel.
EURASIP Journal on Embedded Systems 9

40 40

No TCS Soft TCS

30 30
Wheel speed (m/s)

Wheel speed (m/s)

Rear wheel Rear wheel
20 20

Front wheel Front wheel

10 10
Max Max
Butterfly valve Butterfly valve
Min Min
0 0
0 1 2 3 4 5 6 0 1 2 3 4 5 6
Time (s) Time (s)
(a) (b)

40

Strong TCS

30
Wheel speed (m/s)

Rear wheel
20

Front wheel
10

Max
Butterfly valve
Min
0
0 1 2 3 4 5 6
Time (s)
(c)

Figure 21: Wheel speed, butterfly valve opening, and traction control intervention for a bend test. Without traction control, with traction
control “soft control” setting and “strong control” setting.

The same part of the track has been driven through with Figure 20 reports the opening of the butterfly controlled
different traction control strategies. by the driver, the intervention of the traction controller, the
(A) NO TCS: without traction control. speed of the front wheel, and the speed of the rear wheel. The
effect of the traction control is evident. In case (C), the speed
(B) Soft TCS: with traction control with a high value of of the front wheel is similar to the speed of the rear wheel and
ε, that is the traction control operates only when the consequently, the motorcycle does not rear up.
difference between the speed of the two wheels is Figure 21 shows three cases of a motorcycle in bend, in a
high, giving a “soft control.” situation similar to the photo in Figure 5. In the first part of
(C) Strong TCS: with traction control with a low value of the bend, the driver reduces the accelerator and uses brakes
ε, that is the traction control operates even when the to reduce the speed. In this case, the front wheel speed is
difference between the speed of the two wheels is not higher with respect to the rear wheel, mainly due to the
too high, giving a “strong control.” brake intervention. In the second part of the bend, the driver
10 EURASIP Journal on Embedded Systems

accelerates to increase the speed exiting the bend, but if the [7] H. S. Tan, Adaptive and robust controls with application
torque is too high, the rear wheel tends to go in the extern to vehicle traction control, Ph.D. dissertation, University of
part of the bend, as shown in Figure 5, and the rear wheel California, Berkeley, Calif, USA, 1988.
speed is higher than the front wheel. In this case, the driver [8] H.-S. Tan and M. Tomizuka, “An adaptive sliding mode vehicle
may lose the control of the motorcycle. traction controller design,” in Proceedings of the American
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The same bend has been driven through with different
USA, May 1990.
traction control strategies.
[9] F. Borrelli, A. Bemporad, M. Fodor, and D. Hrovat, “An
(A) NO TCS: without traction control. MPC/hybrid system approach to traction control,” IEEE
Transactions on Control Systems Technology, vol. 14, no. 3, pp.
(B) Soft TCS: with traction control with a high value of 541–552, 2006.
ε, that is the traction control operates only when the [10] K. Fujii and H. Fujimoto, “Traction control based on slip
difference between the speed of the two wheels is ratio estimation without detecting vehicle speed for electric
high, giving a “soft control.” vehicle,” in Proceedings of the 4th Power Conversion Conference
(C) Strong TCS: with traction control with a low value of (PCC ’07), pp. 688–693, Nagoya, Japan, April 2007.
ε, that is the traction control operates even when the [11] M. Jalili-Kharaajoo and F. Besharati, “Sliding mode traction
difference between the speed of the two wheels is not control of an electric vehicle with four separate wheel drives,”
in Proceedings of the IEEE Conference on Emerging Technologies
too high, giving a “strong control.”
and Factory Automation (ETFA ’03), vol. 2, pp. 291–296,
Even in this case, the effect of the traction control is evident. Lisbon, Portugal, September 2003.
In case (C), the speed of the front wheel is similar to the speed [12] J. Zhang, C. Yin, and J. Zhang, “Use of fuzzy controller for
of the rear wheel and consequently, the driver controls the hybrid traction control system in hybrid electric vehicles,” in
motorcycle. Proceedings of the IEEE International Conference on Mecha-
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5. Conclusions [13] V. D. Colli, F. Marignetti, R. Di Stefano, G. Tomassi, and
M. Scarano, “Traction control for a PM axial-flux in-wheel
A new algorithm and its hardware implementation of motor,” in Proceedings of the 12th International Power Electron-
traction control for supermotard or motocross are presented. ics and Motion Control Conference (EPE-PEMC ’07), pp. 1790–
A prototype has been realised and tested in a racing track. 1795, Portoroz, Slovenia, August-September 2007.
The experimental results show good performances of the [14] Z. Ming and G. Ni, “A computationally intelligent methodolo-
system. gies and sliding mode control based traction control system
A more accurate tuning of the parameters of the for in-wheel driven EV,” in Proceedings of the 5th CES/IEEE
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of the driver and on the track and on the ground conditions,
2007.
but the first results are positive.
[15] M. Jalili-Kharaajoo and H. Rouhani, “Robust nonlinear
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Electronics, Circuits and Systems (ICECS ’03), vol. 1, pp. 392–
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