MGA Research Corporation

MGA Research Corporation Real Time Simulation Testing Gerald Roesser David Nagle Thomas Hutter MGA Research Corporation 1

MGA Research Corporation PRESENTERS Gerald Roesser BSEE MGA Associate since 2001 Group Leader Simulation Engineer Dave Nagle BSME MGA Associate since 2006 Simulation Test Engineer Thomas Hutter BSEE MGA Associate since 2000 Simulation Engineer 2

MGA Research Corporation Independent test services Began in New York, 1977 ISO/IEC 17025:2005 Accredited Specialize in Safety Regulations (FMVSS, ECE, SAE, ASTM, MIL_STD, etc.), Vibration, Noise, Life Cycle, Environmental, Equipment, etc. Industries served include: Automotive, Military, Aerospace, Rail, Other Transportation, etc. 3 Burlington, Wisconsin Troy, Michigan Greer, South Carolina Akron, New York Manassas, Virginia

MGA Research Corporation MGA and Simulation Testing 10 years of experience with Simulation Testing 13 Multi-Axis Simulation Tables 150 plus servo-hydraulic loops for multi-axis durability testing Hundreds of Simulation Tests and Components validated per year 10 Simulation Engineers Simulation Test supplier to all major OEMS and the majority of their suppliers 4

WEBINAR OVERVIEW Introduction: Vehicle Durability Testing Simulation and MAST testing overview Road Load Data Acquisition and Analysis Fixture Design Drive File Development Question and Answer 5

INTRODUCTION 6

INTRODUCTION Vehicle Durability Testing Simulation Testing is used in all transportation industries Using actual road data can help predict product performance more accurately. Design Goals for Quality can be met with less development time Multi-Axis Simulation Table (MAST) will be used as an example of simulation testing 7

INTRODUCTION Vehicle Durability Assessment Methods Test Driving, Actual Highway Miles Highly accurate prediction Time consuming Not Practical for new vehicles Proving Ground Track Loop Accurate life predication Highly Correlated Expensive Time and labor intensive Available late in the design process 8

INTRODUCTION Vehicle Durability Assessment Methods Component Block Cycle Testing Good for suppliers Great tool for A to B comparison Not representative of real world Not adequate for complex systems Real-Time Road Simulation Saves development time Accurately correlate to road data and predicts product life 9

Real Time Simulation Testing 10

Simulation Testing Overview Simulation Test Flow Chart 11

Simulation Testing Overview Determine end use of product or vehicle Perform a study to determine what type of road surfaces the vehicle will travel on Create Testing Goals Generate a Durability Schedule based on life expectancy and 95 th percentile usage Select a Test Rig that will be able to apply the collected road inputs 12

Simulation Testing Overview Surface # Time (s) Repeats Test Time (h) 1 2 3 4 5 6 100 528 66 42 1525 42 1456 42 547 57 900 57 Total Test Length 14.7 0.8 17.8 17.0 8.7 14.3 73.1 Example of a Generic Durability Schedule 13

Road Load Data Acquisition (RLDA) Data Types Collected During RLDA Wheel Force Transducers Wheel end to body displacement Chassis, body, or component tri-axial accelerometers Wheel-end acceleration Strain Gages Vehicle Speed GPS Environmental Conditions 14

Road Load Data Acquisition (RLDA) Optimize Data for Test Rig Use Durability Schedule to calculate occurrences of different road surfaces Check data and prepare for analysis and reduction 15

Road Load Data Acquisition (RLDA) Data Normalization Collected data must be normalized so that relative comparisons can be made between different road surfaces, events, and recordings made from the test rig itself. There must be a method in place so that accurate correlations can be derived. In order to compare surfaces, correlate to the real world, or find the worst case vibration scenario, the fatigue damage must be calculated. 16

Road Load Data Acquisition (RLDA) Normalize data for easy comparisons Conduct Relative Fatigue Damage Analysis Create Fatigue Damage Spectrum Establish relationship between actual road miles and laboratory miles using damage figures 17

Road Load Data Acquisition (RLDA) 18 Damage is a unit-less number that normalizes complex data for comparison Data can be reduced to shorten time Damage comparisons are performed to ensure data still correlates Damage Analysis saves a significant amount of testing time

Simulation Test Rigs Upon editing and optimizing the data, it is time to select an appropriate test rig for your application. There several types of real-time simulation rigs and many ways to apply these inputs to your product. Real-Time simulation can mean applying force inputs, acceleration, displacement or even strain to your product on as many axes as collected in the field. 19

Simulation Test Rigs 20

MAST TABLE Multi-Axis Simulation Table (MAST) Made up of 6 hydraulic actuators connected to a test table Capable of moving in 6 degrees of freedom. X, Y, Z, roll, pitch, and yaw Frequency band of 2 to 50 Hz. Each actuator is instrumented with an LVDT to measure displacement. Samples are mounted to the table top 21

Test Fixture Design 22

Test Fixture Design The fixture must not a have a natural frequency in the frequency band of the test data. The fixture must also be light weight so as to not add too much moving mass to the test rig. CAD data is used to generate the fixture to ensure that the sample is mounted exactly as it would be on the vehicle and no extraneous stresses are induced. Test fixture itself can be run through a computer simulation to determine where improvements can be made. 23

Drive File Development 24

Drive File Development The drive file is the corrected data set that is generated to accurately match the desired data. A closed loop servo-hydraulic system will not immediately be able to match the desired data on command Data must be corrected for the dynamics of the system. PID tuning is effective for fixed frequency, fixed amplitude testing It is very difficult to get the command and feedback on a multi-axis system with crosstalk and complex dynamics at play to converge. Advanced software and controls in modern hydraulic controllers make the process easier. (RPC Pro) 25

Drive File Development Accelerometers are mounted to a test fixture or the sample just as they were when the data was collected. (Normally 3 tri-axial Accels) A random (white noise) input is commanded to each of the drive channels as the accelerometer response is recorded. This response yields a transfer function which can be used to match the acceleration response with the desired acceleration data collected from the road surfaces. Transfer functions and inverse transfer functions are generated. 26

Drive File Development Drive File Iterations System Inverse Example 27

Drive File Development Play-out of this drive file on the test rig. Calculate Error Adjust Gain on Drive File Repeat until data converges as pictured on the right 28

Drive File Development 29

Drive File Development The drive file iteration process is complete when all time history response files have been adequately matched to the desired data RMS value of each channel should be at least within 5% Maximum and minimum acceleration peaks should be within 10% Overlay the desired spectrum and response spectrum 30

Drive File Development 31

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QUESTION AND ANSWER 33

QUESTION AND ANSWER 34 Thank you for participating! MGA Contacts: Group Leader Gerald Roesser (Gerald.Roesser@mgaresearch.com) (248) 259-7331 Simulation Engineer Dave Nagle (David.Nagle@mgaresearch.com) (248) 670-4838 Simulation Engineer Thomas Hutter (Thomas.Hutter@mgaresearch.com) (586) 491-6161

Real Time Simulation Testing: An introduction This article will serve as an elementary course for the basics of simulation testing. There will be a discussion on vehicle durability test methods, an overview on the theory of simulation testing, a discussion on data acquisition and analysis, fixture design and drive file development. For the purposes of this presentation we will be discussing simulation testing as it relates to automotive vehicle durability development with a special emphasis on Multi-Axis Simulation Table or MAST testing. However, these same principles can be applied to many types of transportation vehicles that are utilized in a wide range of industries. In today s automotive industry, the primary goal is to design a vehicle that is both safe and durable. This design goal provides the best in value for customers and helps to build the manufacturer s reputation for quality and dependability. Historically, the durability of a vehicle is assessed in several different ways. The simplest form of testing is to merely drive the vehicle through its normal usage. If a vehicle is driven for 100,000 miles or 6 years, one will very accurately be able to assess its reliability over 100,000 miles. This test driving method, while obviously being the most accurate, is not the most efficient. As a consequence, test tracks have been created to simulate these road conditions. A typical proving ground test track will be made up of several types of road surfaces that the vehicle will see in the course of its product life. These surfaces are able to condense the amount of time it takes to expose a vehicle to an equivalent amount of fatigue exposure as it would be exposed to over a period such as 10 years. For example a test track can be designed to have a 40 to 1 ratio where one mile on the track is comparable to 40 miles in real world conditions. This is an effective test method but can only be conducted very late in the design process when an assembled prototype is available. It requires many drivers and a large investment in time and labor. Also, road surfaces can be custom tailored to specific vehicles or regions but this process can be time consuming and expensive.

A third test method is basic fatigue or block cycle testing. This type of testing can be highly effective on a component level basis when the life expectancy of a component is already known based on past history. This approach is excellent for suppliers. With this type of testing, one can predict the reliability of a component by saying part A is stronger than part B. If part B has historically been a reliable part, then it is accepted that part A will be at least as good. This method is not as accurate for complex systems and is not representative of the multitude of inputs that a vehicle will see in the real world. Finally, there is Real Time Simulation Testing. This form of testing has the best of both worlds as it can be highly correlated to real world performance and also save costly development time. The remaining portion of this presentation will focus on the test methods and the process for conducting this type of testing. Simulation testing as described in this presentation is the technique of predicting the structural integrity and durability of a product by using an advanced form of physical testing. This test method incorporates the use of actual road data combined with a durability schedule based upon the market and region in which the vehicle will be used. Time history data is collected on vehicles while being driven through conditions normal to the context for which they were designed. Using advanced analysis techniques, the data can be optimized to create a physical test rig in a laboratory environment that will be highly correlated to real world conditions while saving valuable time and money. This flow chart demonstrates the general simulation test method. First, determine the appropriate road and driving conditions for the vehicle being developed. This is done by doing a market study and considering the end use of the product. Next, collect road load data by instrumenting the vehicle. The collected data is then analyzed and reduced. The test length is calculated while holding fixtures are designed. Next, the sample is mounted to a test rig, and excited such that the response matches the desired road data through an iterative process. If after the test there are failures then there may be a design change and the test will be run again.

The first step is to determine the type of data that needs to be collected and how to use it. Normally when a vehicle is designed, it is intended for use within a certain market and/or region. A study is performed to understand the in-service conditions. This study will take into account the various types of road surfaces, road speeds, and environmental conditions. The frequency or distribution of occurrences of each type of road surface is also taken into account. A document called a durability schedule is produced which will detail this statistical information. The durability schedule will later be used to determine the test length and the number of times each road surface simulation is repeated. Each of these surfaces must be sampled in a process called Road Load Data Acquisition or (RLDA). Surface # Time (s) Repeats Test Time (h) 1 100 528 14.7 2 66 42 0.8 3 1525 42 17.8 4 1456 42 17.0 5 547 57 8.7 6 900 57 14.3 Total Test Length 73.1 Example of a Generic Durability Schedule For example, if a product is designed to be a delivery truck in rural areas with 50% of the roads unpaved then the durability schedule will conclude that half of the simulation data must be sampled from these dirt roads. This chart above is an example of a generic durability schedule. In addition to the vibration, certain components such as radiators and exhaust systems are exposed to temperature and environmental conditions simultaneously. This is accomplished in the laboratory using extreme temperature chambers and hot gas burners. To collect Road Load Data (RLD) a vehicle must be instrumented and driven across a sampling of the road surfaces travelled during normal usage. The data collected can include many types of measurements. The following are some of the most common types: Wheel Force Transducers Wheel end to body displacement Chassis, body, or component tri-axial accelerometers Wheel-end acceleration Strain Gages Vehicle Speed GPS Environmental Conditions

Once the RLDA has been performed and the durability schedule has been agreed upon, it is time to start optimizing the data for use on a multi-axis test rig. The durability schedule will tell you statistical data about how often each surface should be used while the expected end-use of the product will dictate the test goal and test length. Ideally we would like to simulate these road surfaces on the test rig in as short amount of time as possible while retaining the maximum amount of correlation to the real world. The data is edited and any errors or dead space is removed. If there are areas with relatively no input then these are removed as well. At this phase the collected data must be normalized so that relative comparisons can be made between different road surfaces, events, and recordings made from the test rig itself. There must be a method in place so that accurate correlations can be derived. In order to compare surfaces, correlate to the real world, or find the worst case vibration scenario, the fatigue damage must be calculated. With a time history file, it can be difficult to compare the relative effect the inputs have on a sample. This process makes that easier. Relative Fatigue Damage Analysis is conducted by reducing the data or vehicle inputs to a series of cyclic events using a method such as Rainflow counting. When used in combination with an S/N curve, a transfer function can be developed that will predict the relationship between the inputs and accumulated damage. The data is thereby normalized so that relative comparisons can be made and the total damage incurred from testing can be assessed. The data is also dependent on frequency, speed, and acceleration so a Fatigue Damage Spectrum is produced. The fatigue damage spectrum is a spectral representation of a fatigue damage index as a function of any system s natural frequency. This spectrum is computed directly from the Power Spectral Density function representing the field conditions and provides a relative fatigue damage estimate based on acceleration levels and exposure time. The damage number attached to a set of data is an effective way to compare data sets and correlate the test rig to the real world. This method helps us to ensure that one mile on the road is equivalent to one virtual mile in the laboratory. In very simple terms Damage is a unit-less number that represents the severity of a time history file based on its maximum and minimum peaks, as well as the RMS of the data. A software program called Glyphworks, which is produced by ncode, is used to cut sections of these time history files, and analyze them for damage retention. Each channel of acceleration data is used to calculate an individual damage number prior to any data editing. Following the data editing, another damage calculation is performed and a percentage comparison is used to make sure that the edited files have retained most of the damage from the original files. This data compression technique is used to shorten the test duration and make the testing process more efficient. The significance of this process is substantial, as in some cases, it can likely compress a test of the vehicle s durability life from over a month to just a week or less. This method of accelerated testing is thought to realistically validate a product in a rapid manner. By decreasing test duration, one will see improvements in productivity and cost savings.

Upon editing and optimizing the data, it is time to select an appropriate test rig for your application. There are several types of real-time simulation rigs and many ways to apply these inputs to your product. Real time simulation can mean applying force inputs, acceleration, displacement or even strain to your product on as many axes as collected in the field. MGA conducts simulation testing on MAST tables, Four Post Actuators, Electro- Dynamic Shakers as well as direct coupled multi-axis system tests where the actuators are attached directly to the sample. This type of rig is common in suspension testing where for example six actuators may be attached directly to the corner of a vehicle. Another example is connecting directly to the frame of a vehicle for testing such as cab shake where the Cab is being validated as it responds to inputs on the frame. For this article I will be using MAST or Multi-Axis Simulation Table testing as the example. A MAST rig is made up of 6 hydraulic actuators connected to a table capable of moving in 6 degrees of freedom. This includes x, y, z, roll, pitch and yaw. The table is capable of reproducing vibration frequencies from 2 to 50 Hz. Each actuator is instrumented with an LVDT to measure displacement. Samples are mounted to the table top so that road inputs can be applied to actuators and road surfaces can be simulated. In the case of a MAST test, the desired data is presented as acceleration or strain. Accelerometers are mounted to the table top and sample while the actuators are stroked until there is a match. I will elaborate more on that process later. For other types of components or systems, the desired data signals may be presented as force. In this case actuators can be connected to the sample with a load cell and the desired load data is matched. Further, there are cases such as torsion bar testing where a displacement file is given and the objective is to simulate the rotational displacement that a torsion bar experiences in the field. Basically any data set collected in the field can be simulated in the lab regardless of its type. Once the appropriate type of test rig is selected as a validation tool, the holding fixture design becomes very important. The goal of the holding fixture is to provide a means to attach input actuators to the sample. In the case of a MAST test, the fixture holds the sample in vehicle ride attitude on the tabletop while accurately matching the attachments to the vehicle. The fixture must not induce any additional stresses or contribute a response due to its natural frequency that affects the vibration placed on the sample. Several items must be considered during fixture design. The fixture must not have a natural frequency in the frequency band of the test data. For a MAST test, the natural frequency has to be at least above 50 Hz if not 200Hz for assurance. The fixture must also be lightweight so as to not add too much moving mass to the test rig. This will also keep the natural frequency high, this in combination with the stiffness. It is important that the fixture mounting points are accurate. Normally CAD data is used to create the fixture design. This will ensure that the sample is mounted exactly as it would be on the vehicle and no extraneous stresses are induced. Often a test fixture itself can be run through a computer simulation to determine where improvements can be made.

Now that the data has been collected and analyzed and the test fixture has been designed and built, it is time to mount the sample and begin to match the system response to the input data. This process of matching the desired data to the response is the same no matter what the test type. These basic principles apply to frame coupled testing, 4 post testing, MAST testing and all types of simulation testing. Today we will go into depth on the iterative process used to match desired data to the response on a MAST system. This stage of the test setup is what is known as the drive file iteration process. The drive file is the corrected data set that is generated to accurately match the desired data. In general a closed loop servo-hydraulic system such that is used in a MAST test will not immediately be able to match the desired data on command until the required offsets are calculated and the data is corrected for the dynamics of the system. If you are familiar with control systems you will know that a servo-hydraulic loop employs closed loop PID tuning to ensure that the feedback matches the command. In a fixed frequency, fixed amplitude test this tuning method is very easy to control. A few simple adjustments will allow a user to accurately correct the command-feedback loop until a match is achieved. With a complex time history file, this task quickly becomes much more complicated. It is very difficult to get the command and feedback on a multi-axis system with crosstalk and complex dynamics at play to converge. This is where advanced software such as RPC Pro and hardware in modern hydraulic controllers are called in to make the process easier. To start the drive file iteration process, accelerometers are mounted to a test fixture or the sample just as they were when the data was collected. Usually at least three tri-axial accelerometers are used to define a space and give greater resolution Strain gages are sometimes applied to help match the road data and provide a more accurate picture of the damage induced by the vibration. Next, a random (white noise) input is commanded to each of the drive channels as the accelerometer response is recorded. This response yields a transfer function which can be used to match the acceleration response with the desired acceleration data collected from the road surfaces. A filter is created to omit any data that is beyond the workable range of the test equipment. Each of

the desired channels is generally filtered from 2-50 Hz, and an initial drive file is created using the transfer function and inverse transfer function. The next step is to play-out this drive file on the test rig. The accelerometer response is filtered and error is calculated. If the response does not match the desired file then the drive file must be adjusted to command a better match. RPC Pro software allows for specific gains to be applied to each of the acceleration response channels, and based on the error of the previous drive file play-out, the drive command is adjusted and acceleration is recorded again. This process is repeated until the desired acceleration is matched. The screenshots below show how a file begins to converge after each iteration. The second plot is an example of a good match after several passes.

The example plot shows an overlay of desired acceleration and response acceleration data for a single channel. In some simulation tests such as a MAST test, the control mode may not be the same as the feedback mode. For example, if acceleration is the data type the test engineer is trying to match, the control mode may be displacement. The drive file will then adjust displacement control as it measures the error in acceleration feedback. This method can make it easier to control the table in some cases as displacement is a more stable control mode and less susceptible to noise and other transient influences. The drive file iteration process is complete when all time history response files have been adequately matched to the desired data. From our previous experience in vibration testing, the RMS value of each channel should be at least within 5% of the desired RMS value, and the maximum and minimum acceleration peaks should be within 10% of the desired peaks. This criteria is usually determined by the customer but can be altered depending on the application. Another factor used to determine if a time history match is satisfactory is to overlay the desired and response spectrums and make sure they are the same level across the entire frequency range. This will show if there are any issues with matching certain frequencies due to resonance of the fixture or system.

Once the acceleration data is matched and a satisfactory match in the time and frequency domain is achieved for all road surfaces, the drive inputs are saved and played in a specific sequence to simulate the vehicle life. The sequence is determined by the durability schedule that was created at the beginning of this process. Typical tests can be anywhere from 1 day to 2 weeks depending on the complexity and length of the data.