26th International Conference
ENGINEERING MECHANICS 2020
Brno, Czech Republic, November 24 – 25, 2020
MEASUREMENT AND ANALYSIS OF DYNAMIC RIDING BEHAVIOR
OF A MOTORCYCLE
Tobiáš M.*, Porteš P.**, Zháňal L.***, Fojtášek J.****
Abstract: A long-term project at the Institute of automotive engineering at FME BUT, aims to analyze
a motorcycle’s dynamic riding behavior using in-house developed methods, originally intended for cars.
A multi-body model of a motorcycle based on the measured parameters of a motorcycle and a system
for measuring multiple physical quantities during a test ride were created. The necessary motorcycle
parameters were measured using a 3D scanner and through experiments aided by computer technology
and CAD software. Presented method is based on connecting measured data during test ride with an inverted
multibody model. This enables the processing of data and analysis of measured dynamic states of motorcycle,
while the details of output quantities are comparable with outputs from simulation calculations. Presented
work has laid a foundation for a follow-up research and development work.
Keywords: Motorcycle, Dynamics, Simulation, Measurement, Multi-body.
1. Introduction
An in-house developed SADT (System of Automotive Development Tools) is used to support
the mechanical design of a vehicle, analysis of its dynamic states (calculated and measured) and optimize
kinematic and dynamic characteristics of wheel suspensions as well as vehicle subsystems that affect
driving characteristics of a car. Using SADT tools requires a precise mathematical model of studied
mechanical system, along with a range of input information gathered during an actual ride. These tools can
be applied both before the prototype is created and during fine-tuning of the vehicle’s driving characteristics
based on test rides as stated at (Research, Vehicle Dynamics, SADT, IAE FME BUT: SADT - System
of Automotive Development Tools, 2020). This notion is especially appetizing for those interested
in studying motorcycle’s dynamic behavior as they are inherently unstable vehicles.
Experimental motorcycle
For the purposes of this project, a KTM RC 390 motorcycle has been used as shown in Fig. 1. It is a modern,
lightweight, sport-touring, single-cylinder motorcycle with a moderate engine size and power. Front wheel
is suspended by an upside-down telescopic fork, rear wheel is pivoted on a swingarm with a single shock
absorber.
2. Methods
From the viewpoint of vehicle dynamics multi-body simulations are very progressive, but results are
heavily dependent on the accuracy of the model, fidelity of load conditions, tire models, etc. These
characteristics are even more pronounced with motorcycles, whose dynamic riding behavior depends
heavily on a rider’s motion relative to the vehicle as stated by (Cossalter, 2006). All these shortcomings are
Ing. Martin Tobiáš: Institute of Automotive Engineering, Brno University of Technology, Technicka 2896/2; 616 69, Brno;
CZ, martin.tobias@vut.cz
**
Assoc. Prof. Ing. Petr Porteš, PhD.: Institute of Automotive Engineering, Brno University of Technology, Technicka 2896/2;
616 69, Brno; CZ, portes@fme.vutbr.cz
***
Ing. Lubor Zháňal, PhD.: Institute of Automotive Engineering, Brno University of Technology, Technicka 2896/2; 616 69,
Brno; CZ, lubor.zhanal@vut.cz
****
Ing. Jan Fojtášek, PhD.: Institute of Automotive Engineering, Brno University of Technology, Technicka 2896/2; 616 69,
Brno; CZ, jan.fojtasek@vutbr.cz
*
doi: 10.21495/5896-3-488
488
possible to avoid, by compiling reverse multi-body simulations, where all the inputs for the simulation
come from measured test ride. This is the core idea behind SADT system, which has been successfully used
and proven on two-track vehicles by (Porteš, 2014 and Porteš et al., 2018).
For a study of a dynamic behavior of any land vehicle, the most prized information is arguably forces and
their vectors in contact between the tires and a road, which the SADT tools mentioned in the introductory
section allow to calculate. Precision of these calculations depends proportionately on accuracy and number
of parameters that are measured during a test ride. This method can yield very accurate information
independent of the type of road or road conditions, completely bypassing all shortcomings of mathematical
tire models.
Fig. 1: Experimental motorcycle KTM RC 390 during a test ride.
2.1. KTM RC 390 parameters
As stated by (Tobiáš, 2019), to create virtual model, following parameters had to be measured:
•
•
•
•
Kinematics, precise location of key points in a determinate coordinate system;
Center of mass location within this coordinate system, without wheels;
Moments of inertia along coordinate system axes, without wheels;
Weights and moments of inertia of wheels.
Kinematics
To determine the location of key points an in-house 3D scanner GOM Atos Compact Scan 2M was used.
Center of mass location
To determine the center of mass (CM for short) location, the motorcycle was suspended freely above level
ground two times in different positions and scanned. In each scan an intersection of a line normal to the
ground with hinge point was found, intersection of these lines gave the CM location.
Moments of inertia of the motorcycle and wheels
To determine the values of moments of inertia along coordinate system axes, a simple gravity pendulum
model was employed. Motorcycle was pivoted along set axes and the swinging motion was measured by
a digital gyroscope. This was done multiple times for each axis in order to average-out inaccuracies
and to guarantee excellent repeatability. Then by solving slightly modified, but still rather simple
mathematical equations of mathematical pendulum and Steiner’s theorem a final value for moments
of inertia were calculated.
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2.2. Ride-measuring system
The heart of the measuring system is IMC CRONOSflex 400 datalogger. Fig. 2 shows a schematic
arrangement of sensor used to gather necessary information. Suspension forces were measured directly by
strain gauges glued to the piston rods of shock absorbers. Other sensors were mounted on tailor-made
brackets, some 3D printed from ABS plastic. Following is the list of main measured physical quantities.
•
•
•
•
•
•
•
Location and orientation of motorcycle in space:
o 3 translational coordinates,
o 3 angles (roll – X, pitch – Y, Yaw – Z);
Speed and acceleration of the motorcycle:
o 3 translational velocities + 3 angular velocities,
o 3 translational accelerations + 3 angular accelerations;
Wheels angular rotation speed;
Suspension travel, suspension forces;
Steering angle;
Roadway position relative to the motorcycle;
Riders position.
SF
AF
RT
SB
BR
CR
AR
FCWH
RCWH
GCS
3x Potentiometers – suspension travel, steering angle
2x ABS sensors – wheels rotation
3x LED distance sensors RHS 50-400 – relative roadway position
OxTS RT3002 inertial navigation system – position, speed and acceleration
imc CRONOSflex 400 data acquisition system
strain gauges – suspension forces
2x GoPRO camera – riders’ position
OBD II diagnostic connection – throttle position, engine rpm
Fig. 2: Kinematical model, sensors arrangement.
2.2. Multibody model
Using the measured parameters, a multi-body model of the experimental motorcycle was created within
SADT system and interconnected with the measured data using Telematrix software. The dynamic model
of the motorcycle is built on top of the kinematical model and in addition includes elements with known
(measured; such as forces acting from spring damper units) and unknown force effects, the magnitude
of which is calculated from the movement of the vehicle (tire forces, drive torque or brake moments, chain
forces, aerodynamic drag and lift forces, steering torque). See Fig. 2 and Tab. 1 for schematic description.
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Tab. 1: Topology of the dynamical model.
Description of connection
GCS
ARM (auxiliary body) to GCS (global coordinate system)
RT
BODY to ARM (auxiliary body)
AF
FORK to BODY
AF
TUBE to FORK
FCWH
FWH (front wheel) to TUBE
AR
RARM (rear arm) to BODY
RCWH
RWH (rear wheel) to RARM (rear arm)
CR
RDM (rear damper) to RARM (rear arm)
CR
RPR (rear damper piston rod) to RDM (rear damper)
BR
RPR (rear damper piston rod) to BODY
SB
SPOT (steering potentiometer) to BODY
SB
SPR (steering pot. piston rod) to SPOT (steering pot.)
SF
SPR (steering potentiometer piston rod) to FORK
DOF
+3
+3
+1
+1
+1
+1
+1
+1
+1
-2
+2
+1
-3
Type of joint or constraint
Translational joint
Spherical joint
Cylindrical (only rotation)
Cylindrical (only translation)
Cylindrical (only rotation)
Cylindrical (only rotation)
Cylindrical (only rotation)
Spherical (only one rotation)
Translat. (only one translation)
Constraint – point (x z)
Spherical (only two rotation)
Translat. (only one translation)
Constraint – point (x y z)
3. Measured test ride
A test ride was realized on a relatively flat concrete surface. It comprised of a rapid acceleration in straight
line followed by intensive braking, steady state circular test in both directions and an obstacle course
in form of a slalom. Ride measurement system proved to be functional, all the necessary data were
collected.
Fig. 3: Example of measured data during a test ride.
4. Conclusion
Methods presented in this paper show promise in being able to calculate parameters, which were not directly
measured. Despite the satisfactory results from the first stage of testing, both the ride measurement system
and virtual dynamic model are currently subject of further development focused mainly on a detailed
analysis of the driver's influence in more complex driving contiditions.
Acknowledgement
The authors gratefully acknowledge funding from the Specific research on BUT FSI-S-20-6267, and also
funding from the internal FME BUT program Fund of Science, project name Measuring system
of motorcycles dynamic states, Reg. No. FV 20-32.
References
Cossalter, V. (2006). Motorcycle dynamics (2nd English ed.), Lulu.
Porteš, P. (2014) Utilisation of mathematical vehicle models in analysis of measured data. Habilitation Thesis, Brno
University of Technology (in Czech).
Porteš, P., Zháňal L. and Fojtášek, J. (2018) Complex approach to computations and analysis of vehicle dynamics. In
Vibroengineering Procedia. Vibroengineering Procedia. Lithuania: JVE International, pp. 132-137. ISSN: 23450533.
Research, Vehicle Dynamics, SADT, IAE FME BUT: SADT - System of Automotive Development Tools. (2020).
Institute of Automotive Engineering. Retrieved 15 Sep. 2020, from http://www.iae.fme.vutbr.cz/research-vehicledynamics-sadt-2j.
Tobiáš, M. (2019) Analysis of dynamic measured states of motorcycles. Diploma Thesis. Brno University of
Technology, Faculty of Mechanical Engineering, 68 p., (in Czech).
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