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Dynamic Tire Load Acquisition for Ground Vehicle Handling Analysis with NI CompactRIO

Contact Information

University and Department: Missouri University of Science and Technology

Team Members: Brandon Doherty

Faculty Advisors: Dr. Hank Pernicka

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Project Information

Project Title: Dynamic Tire Load Acquisition for Ground Vehicle Handling Analysis with NI CompactRIO

List all parts (hardware, software, etc.) you used to design and complete your project:

CompactRIO  Real-time embedded controller with data storage

FPGA Backplane for  I/O Modules

8-channel, 24-bit quarter bridge analog input module for strain gauges


The necessity to understand the real world suspension loads in ground based  vehicles has led to the creation of an electronic strain gage instrumentation  system. A method developed to dynamically record the normal loads delivered by  the tires of an open-wheel racecar was tested on track and discussed. The forces  transmitted by each of the vehicle’s four tires were recorded during a series of  forward acceleration, braking, and skidpad exercises to determine the highest  instantaneous lateral and longitudinal suspension loading. These data were used  to verify the calculations and assumptions of a physics-based analytical model  that was concerned with the effects of lateral and longitudinal vehicular load  transfer under acceleration. -Brandon Doherty (Missouri S&T)


The typical analysis of load transfer from the tires to the chassis of a  ground based vehicle often incurs many approximations and assumptions that lead  to a high degree of result uncertainty. Concerns including transient  longitudinal and lateral load transfers under unpredictable accelerations,  non-ideal track surfaces, and unaccounted aerodynamic forces reduce the accuracy  of analytical solutions.

In an effort to reduce these uncertainties, actual load data were collected  to verify models. This paper outlines a technique to dynamically collect the  normal loads from the four wheels of a test vehicle. It is the author’s opinion  that the use of strain gages attached to the suspension components of a vehicle  can offer results of sufficient accuracy at a reasonable cost.

These force data form the foundation of a vehicle suspension and related  support structures design. The accuracy of the calculations and assumptions are  of great importance to driver safety as a failure of the suspension or related  structures could lead to injury. In addition to avoiding the obvious concerns of  component failure, lower load uncertainty can indirectly lead to higher vehicle  performance; the required factor of safety for each part can be reduced allowing  for less conservative designs with lower mass figures. Designers eager to  decrease vehicle mass and increase passenger safety will find value in the load  analysis strategy presented in this paper.

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Experimental Procedure

A test vehicle was instrumented to determine the forces within the structures  that carry the loads from the tires to the chassis. The car used in this study  featured an all-around double wishbone suspension and pushrod activated springs  as illustrated in Figure 1. The pushrods, pictured in red, coupled with the  springs carry the normal load of the wheels to the chassis as guided by the  sweeping motions of the wishbone control arms. This study focuses primarily on  the normal loads experienced by the individual wheels. After a brief discussion  of system theory, an explanation of how the individual components of the strain  gage monitoring system were specified, installed, interpreted, and calibrated is  given.

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Figure 1. Test vehicle with the pushrods  highlighted in red and the normal forces highlighted in yellow.

System Theory

To determine the normal load transmitted from the contact patch of the tire  to the chassis, an investigation of force induced strain in the pushrod was  conducted. The strain present in these structures is proportional to the stress  experienced as described by Hooke’s law. No suspension component of any vehicle  should surpass its yield strength under normal operating conditions; therefore,  the linear relationship described in eq. 1 is reasonable. Rearranging the  definition of stress in eq. 2 with eq. 1 leads to the relationship used for  strain gage analysis shown in eq. 3.

Eq. 1 Stress = (Modulus of elasticity)*(Strain)
Eq. 2 Stress =  (Force)/(Area)
Eq. 3 Force = (Area)*(Modulus of elasticity)*(Strain)

Strain within an axially loaded tube is ideally consistent across its  cross-section. This is only true if there are no bending loads present and the  tube is loaded along its axis. The pushrods of the test vehicle meet these  conditions as they are loaded at their ends with spherical joints. The force  transferred by the pushrods can be correlated to measured strain. The  relationship of pushrod force and the normal force transferred at the contact  patch of each tire is discussed below.

Specification of Components

The current state of the art in strain monitoring generally involves  electronically measuring the change of resistance in a thin conductor attached  to the strained object. The strain gage is usually wired into a Wheatstone  bridge to evaluate resistance as a function of voltage. A particular setup  called a quarter-bridge was used in all four Wheatstone bridges for its  simplicity and low cost. Refer to Figure 2 for layout details.

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Figure 2. Quarter Wheatstone bridge  circuit.

For the experiment described in this study, 120-ohm Omega SGD-6/120-LY11  strain gages were used to relate strain to resistance. They were chosen for  their affordability, ruggedness, and pre-soldered leads. The strain gage is  indicated as R4 in Figure 2 while R3, R2, and R1 are precision matched 120-ohm  balancing resistors. Twenty-two gage wires were used for all interconnects as  recommended by Omega. A third lead was connected to the strain gage to help the  bridge balance the effects of wire resistance. A two volt excitation voltage was  supplied to all strain gages. Typically a higher voltage is employed, but a  precision strain gage amplifier was used to minimize ohmic heating induced  error.

The related electronic measurement equipment selection was based on the  ability to resolve and record the minute changes in voltage within the  Wheatstone bridges at a rate sufficient to capture the fastest expected event.  This interpretation is handled by a device known as an analog-to-digital  convertor or ADC. Three main requirements were used to select the ADC: number of  channels, sampling rate, and resolution.

It was estimated that the fastest the test vehicle could react and settle to  driving over a 0.5 inch bump was 0.1 seconds. This bump situation was reasoned  to be the quickest event that the instrumentation would be required to capture.  To make certain the highest possible instantaneous load was captured and  recorded it was decided to sample at a rate of ten times the shortest event time  or 100 samples per second. It is required to monitor each pushrod individually  as all four wheels experience loads uniquely. The desired overall sample rate  was calculated to be 400 samples per second.

The resolution requirement of the device was based on the worst-case load  scenario for the front and rear pushrods. It was estimated that the highest  expected loads for the front and rear pushrods were 750 and 500 pounds,  respectively, during the design phase of the vehicle manufacture. With the  expectation that half-pound increments would be sufficient for structural  analysis, it was reasoned that the strain gage ADC must have at least a 10 bit  resolution (210 steps). Added resolution was deemed desirable as it would allow  for greater sensing of transducer overload, a larger load range, and an ability  to resolve finer detail in the measured strain.

There are several ADC solutions from different manufactures that  satisfactorily meet the project requirements. A National Instruments (NI)  arrangement was chosen due to its onsite availability. The project’s  instrumentation grade power supply, ADCs, processor, and data logger were all  sponsored by NI.

The NI hardware was organized into two components: a CompactRio Real Time Controller chassis (model NI  9002) and an 8-channel, 24-bit quarter bridge analog input module (model NI 9235). The  CompactRio chassis housed the FPGA processor and data memory while the input  module contained eight independent ADCs, eight Wheatstone quarter bridges, eight  differential amplifiers, and a precision regulated 2-volt excitation power  supply. The input module was highly capable. It had the ability to capture  10,000 samples per second per channel and had integrated bridge voltage  amplifiers to improve sensitivity. The NI arrangement provided an ideal solution  to this instrumentation challenge due to its robust packaging and ease of  configuration in the National Instruments LabVIEW software. Figure 3 displays  the test equipment used for the experiment.

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Figure 3. Test equipment: CompactRio  chassis, instrumented pushrods, and input module with test leads.

Installation of Components

Strain gages require careful installation in order to provide satisfactory  results. The pushrods were cleaned of their protective epoxy paint with a wire  wheel abrasive tool, roughened with 400-grit sandpaper, scored with parallel  alignment marks to ease strain gage installation, and then wiped with mineral  spirits to remove any residue debris. One strain gage was affixed to each  pushrod of the test vehicle with a thin layer of cyanoacrylate glue. Insulating  adhesive tape was placed under the uninsulated leads to prevent shorting once  the glue had cured. Three ten-foot wires were then soldered to the uninsulated  leads, wrapped around the pushrods, and epoxied in place to provide protection  from accidental tugging and road vibration (Figure 4). Next, the bundle of three  wires was spliced with weather resistant spade connectors and zip-tied to  prevent tangling.

The pushrods were installed into the suspension after calibration. Once the  suspension had been aligned, the bundles were connected to the NI input module.  The instrumentation chassis was secured under the driver’s legs in the vehicle’s  cockpit. A temporary cardboard enclosure was installed during testing to protect  the equipment from accidental bumps during driver entry and egress (Figure  5).

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Figure 4. Pushrod strain gage  installation.

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Figure 5. Pushrod mounted into  suspension.

Calibrating the Strain Gages

Calibration was performed on each strain gage installation to adjust for  uneven test lead resistances, strain gage misalignment, and manufacturing  tolerances. The strain gages were evaluated on an Instron tensile testing  machine under compression at approximately 100 pound increments up to about 750  pounds (Figure 6). It would have been preferable to calibrate at even increments  of exactly 100 pounds, however, the equipment controls did not lend itself to  that sort of load-setting precision. The results were graphed and a linear  regression was performed to determine the degree of error present in each strain  gage (Figure 7).

The strain gages were not perfectly aligned with the axis of the tube during  installation and this introduced a systematic linear error. The correction  factor could be determined by analyzing the difference in the slopes found in  the collected data.

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Figure 6. Pushrod strain gage  calibration.

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Figure 7. Visualization of calibration data  for strain gage 2.

All strain gages consistently measured within five percent of the Instron  values over their entire range (0 to 750 pounds) after balancing the resistances  in the Wheatstone bridge and accounting for the installation error. Another  round of calibration was performed once the pushrods were installed into the  test vehicle on four individual scales with similar results.

Interpreting the Strain Gage Readings

It is important to note that the pushrods carry only the normal load present  in the wheels. Also, the actual force carried by the push rods is not linearly  related to the normal force experienced by the wheel. This is a result of the  sweeping motion caused by the suspension control arms. A nonlinear relationship  between wheel movement and pushrod mechanical advantage was observed and this  result is imaged in Figure 8.

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Figure 8. Visualization of mechanical  advantage change due to change in ride height in the rear suspension.

A simulation of the suspension motion was performed in SIEMENS NX5 CAD  software to understand the effects of this change in mechanical advantage due to  wheel position. The results for this investigation are presented in Tables 1 and  2 for the front and rear suspension, respectively. The correlation between  position and mechanical advantage was plotted in Graph 2 for the front and Graph  3 for the rear. All lengths were measured in inches.

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Table 1. Front pushrods mech. advantage  results

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Graph 2. Front pushrods mech. advantage  results.

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Table 2. Rear pushrods mech. advantage  results

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Graph 3. Rear pushrods mech. advantage  results.

The mechanical advantage changes a total of 6.0% and 8.4% from static ride  height as a result of the sweeping movement of the control arms. For the test  described in this study this change in mechanical advantage is considered an  uncertainty. At the time of writing this study the wheel position sensors were  not installed. In a more sophisticated version of this analysis one could  correlate wheel position and mechanical advantage to remove this geometry-caused  uncertainty.

It is important to note that the full sample rate of 10,000 samples per  channel was recorded. This was done to collect a large number of samples that  could be averaged and filtered to produce a more accurate, noise reduced result.  The static readings remained steady within ten pounds of the force, including  the vibrations and electromagnetic interface generated by the test vehicle’s  internal combustion motor. Testing could begin once the correlation between the  strain and normal load was developed.

Results and Discussion

A series of tests were run to validate the measurements acquired by the newly  instrumented pushrods. The evaluations were meant to introduce the highest  possible lateral and longitudinal load transfers into the suspension. The tests  included forward acceleration launches, braking, and a  clockwise/counter-clockwise skidpad (a circular track).

The skidpad was used to generate lateral load transfer. Five laps were  completed in the clockwise direction followed by five laps in the  counterclockwise direction. Figure 9 shows the processed readings from the  skidpad test.

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Figure 9. Recorded normal force per wheel  during skidpad.

Figure 9 clearly demonstrates the effects of hard corning on lateral load  transfer. The data illustrates when the driver entered the skidpad, cornered  clockwise, changed direction, and finally exited the track. The effects of  centripetal acceleration are clear and the load transfer from left to right can  be measured from these results. Approximately 70 percent of the sum sprung  vehicle weight transferred laterally during the clockwise laps of the  experiment. The driver and the test configured car weighed approximately 575  pounds. It is important to note that the pushrods only sense the weight of the  vehicle held by the suspension or sprung weight. The weight of the wheels and  suspension knuckles are not carried through the pushrods, but they are  transferred directly to the ground. The measured sprung weight of the test  configured vehicle with driver was approximately 525 pounds.

It was fascinating and reassuring to note the sum force of all the normal  loads remained approximately stable throughout skidpad testing. The skidpad was  limited to approximately thirty feet in diameter due to time and resource  constraints. The effects of the aerodynamic generated downforce were reduced  along with its related increase in grip. This reduction in grip prevented the  car from achieving its maximum cornering acceleration and reduced the overall  maximum weight transfer. A more stable reading could be obtained with a larger  skidpad as it is easier for a driver to maintain a consistent radius with more  room allowed for steering correction.

A series of five acceleration launches were run to investigate longitudinal  load transfer. Figure 10 displays a capture of one of the launches. At the  beginning of the launch (1.1 seconds), the rear of the car witnesses a lower  than statically observed weight as the tires begin to rotate. The force in the  rear quickly ramped to about 20 percent more than static after the wheels began  to develop traction (1.9 seconds). An up gear shift was initiated (2.5 seconds)  and the force rebounded to below static, thereafter, climbing again (3.0  seconds) after the second upshift. A final upshift was activated at 3.9 seconds.  The brakes were applied (7.5 seconds) and the front of the car finally saw  action. The front of the car witnessed an impressive 50 percent increase in  normal load at the expense of the rear. In order to position the car for the  next acceleration launch the driver began to turn left, but he continued braking  (8.5 seconds). During that time an impressive combined lateral and longitudinal  weight transfer was observed (9.0 seconds). The sudden transition from straight  line acceleration to left cornering slightly pitched the car and this movement  loaded the suspension dampers creating an additional normal force on the right  wheels.

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Figure 10. Normal force experience during an  aggressive acceleration.

A final test involving repeated heavy braking was conducted to analyze the  effects of longitudinal load transfer. Figure 11 illustrates the results of four  consecutive braking exercises. The braking test track was setup as a long  ellipse to allow for the highest possible speed before braking. A more ideal  track involving two long straight-aways would have been preferred; however, a  parking lot of satisfactory size was not available for testing.

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Figure 11. Normal force experience during an  aggressive braking.

The test driver completed four laps on the track and his consistency is  visible in the data. The front of the car consistently showed a 50 percent  loading increase under heavy braking while the rear loading repeatedly dropped  to zero. Negative values are not unreasonable as the pushrods should experience  tension when lifting the unsprung weight of the wheels, however, the negative  values of over 50 pounds are suspicious and will be subject to further  investigation. It is possible the sudden loading of the dampers in fast motion  rebound are responsible for the unexpectedly low negative values.

When braking the car generally lurched forward on its suspension while  slightly lifting the rear. This was usually followed by the rear abruptly  returning to level. The transient peaks between 250 and 300 pounds witnessed in  the rear left pushrod are attributed to damper loading caused by rapid shock  movement.

The instrumented test vehicle witnessed an approximately 70 percent load  transfer under sustained cornering and an approximately 50 percent longitudinal  load transfer during heavy braking. During forward acceleration an ~20 percent  increase of normal load was measured in the rear wheels while no significant  change was observed in the front. Further testing with the strain gauge  instrumented vehicle in warm weather and proper sized track will reveal the true  maximum normal loads and weight transfer figures.

Conclusion and Recommendations

The experimental strain gage based apparatus successfully captured the normal  forces present in the four wheels of the test vehicle. The effects of heavy  lateral and longitudinal acceleration were related to their respective load  transfers. The results collected within this study along with future track  testing will be of great value in refining future test vehicles.

Though the results are of a satisfactory quality to aid future structural  design, further efforts could increase the precision of the testing apparatus.  For example, it was noted that flexing the wire bundles could introduce a  measurable ripple of several pounds into the collected data. The wire resistance  changed as the cross-sectional area deformed during bending. This effect could  be reduced by choosing thicker leads with stiffer insulation. Also, proper  shielding and a reduction in wire length should also improve signal quality. The  usefulness of extracted data is directly related to the consistency of the test  track. Pavement quality, changes in track elevation, and ambient temperature  affect tire force generating performance. Logging strain gage data continuously  during the lifetime of the vehicle or testing on a professionally maintained  track in a warm, sunny location could experimentally determine the absolute  maximum normal forces and load transfer figures.


The author would like to thank Eric Cunningham of National Instruments for  his assistance in facilitating the delivery of the primary test equipment. To  David Erdos, whose LabVIEW knowledge proved invaluable to completing the project  within schedule. To my fellow S&T Racing teammates for their cooperation and  effort. And many thanks are in order to Dr. Hank Pernicka of the Mechanical and  Aerospace Engineering Department of the Missouri University of Science and  Technology for his incredible patience and encouragement.