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The Texas A & M University Formula SAE program currently has no rigorous method for analyzing or predicting the overall dynamic behavior of the student-designed racecars. The objective of this study is to fulfill this need by creating a full vehicle ADAMS/Car model incorporating an empirical tire-road force model and validating the longitudinal performance of the model by using vehicle responses recorded at the track. Creating the model requires measuring mass and inertia properties for each part, measuring the locations of all the kinematic joints, testing the Risse Racing Jupiter-5 shocks to characterize damping and stiffness, measuring engine torque, and modeling the tire behavior. Measuring the vehicle performance requires installation of the Pi Research DataBuddy data acquisition system and appropriate sensors. The 2002 Texas A & M University Formula SAE racecar, the subject vehicle, was selected because it already included some accommodations for sensors and is almost identical in layout to the available ADAMS/Car model Formula SAE templates. The tire-road interface is described by the Pacejka '94 handling force model within ADAMS/Car that is based on a set of Goodyear coefficients. The majority of the error in the model originated from the Goodyear tire model and the 2004 engine torque map. The testing used Hoosier tires and the 2002 engine intake and exhaust configuration. The deliverable is a full vehicle model of the 2002 racecar with a 2004 engine torque map and a tire model correlated to longitudinal performance recorded at the track using the installed data acquisition system. The results of the correlation process, confirmed by driver impressions and performance of the 2004 racecar, show that the 2004 engine torque map predicts higher performance than the measured response with the 2002 engine. The Hoosier tire on the Texas A & M University Riverside Campus track surface produces 75 " 3% of peak longitudinal tire performance predicted by the Goodyear tire model combined with a road surface friction coefficient of 1.0. The ADAMS/Car model can now support the design process as an analysis tool for full vehicle dynamics and with continued refinement, will be able to accurately predict behavior throughout a complete autocross course.
Racecar data acquisition used to be limited to well-funded teams in high-profile championships. Today, the cost of electronics has decreased dramatically, making them available to everyone. But the cost of any data acquisition system is a waste of money if the recorded data is not interpreted correctly. This book, updated from the best-selling 2008 edition, contains techniques for analyzing data recorded by any vehicle's data acquisition system. It details how to measure the performance of the vehicle and driver, what can be learned from it, and how this information can be used to advantage next time the vehicle hits the track. Such information is invaluable to racing engineers and managers, race teams, and racing data analysts in all motorsports. Whether measuring the performance of a Formula One racecar or that of a road-legal street car on the local drag strip, the dynamics of vehicles and their drivers remain the same. Identical analysis techniques apply. Some race series have restricted data logging to decrease the team’s running budgets. In these cases it is extremely important that a maximum of information is extracted and interpreted from the hardware at hand. A team that uses data more efficiently will have an edge over the competition. However, the ever-decreasing cost of electronics makes advanced sensors and logging capabilities more accessible for everybody. With this comes the risk of information overload. Techniques are needed to help draw the right conclusions quickly from very large data sets. In addition to updates throughout, this new edition contains three new chapters: one on techniques for analyzing tire performance, one that provides an introduction to metric-driven analysis, a technique that is used throughout the book, and another that explains what kind of information the data contains about the track.
The brake system is inarguable one of the most critical aspect of a vehicle safety. It has always been the major concern for design engineers to develop a system that gives a steady performance with respect to time. In order to achieve that feat, one of the most common problems that arises in maintaining a brake is the problem of brake fluid vaporization. The race cars of the Formula SAE team at the University of Texas of Arlington face this challenge on a regular basis because of repetitive braking on curved tracks. In order to ensure safety of the vehicles, a study has been proposed in this report that deals with the problem of repetitive braking under extreme (hard) braking conditions and the temperature dependence of the brake fluid on it. The study was concentrated on finding the heat partition towards the brake disk and brake pads when brakes are applied. The theoretical results of the simulation conducted in MATLAB were later verified by the experimental ones performed on a Formula SAE vehicle of the University of Texas at Arlington.
This book presents the definition of a methodology to deeply analyze the dynamic and handling of a Formula SAE car, focusing the attention on the creation of a vehicle model able to simulate almost all the common maneuvers that the formula has to perform during a typical race. During the development of this work, two different models have been created: a 3 DOF one and a 15 DOF one. Both of them, built starting from the effective Formula SAE car geometric and inertial data, have been tested on common maneuvers and the results compared with the real car telemetry, to prove the efficiency and correct response of the simulator. Both the models gave interesting results, always demonstrating to give correct outputs, compared to real car or to commercial software.
This book was written to help engineers to design safer brakes that can be operated and maintained easily. All the necessary analytical tools to study and determine the involvement of brakes in accident causation are included as well as all essential concepts, guidelines, and design checks.
Several standardized courses for Formula SAE (FSAE) testing are introduced and described with sufficient detail to be reproduced by any Formula SAE team. Basic analysis methods for the courses are given as well as explanations of how those analyses could be used. On-car data from the Global Formula Racing (GFR) SAE cars is used to verify the analysis methods, give estimates to unknown variables, and show the relevance of the standard testing courses. Using the courses and methods described in this paper should allow standardized comparison of FSAE car performance, as well as provide a method to verify simulations and evaluate changes in vehicle performance from tuning. Instrumentation of all suspension member forces with strain gauge load cells is shown to be an extremely powerful tool for measuring vehicle performance and quantifying vehicle dynamic characteristics. The design and implementation of strain gauge load cells is described in detail to provide a template for reproducing similar results in other vehicles. Data from the GFR 2011 FSAE car is used throughout the paper to: show the design process for making effective suspension member load cells, show the calibration processes necessary to ensure quality data is collected, illustrate the calculation of suspension corner forces, and show the effectiveness of measuring vehicle dynamic characteristics with this technique. Using the methods described in this paper should provide data that allows a more complete and thorough understanding of on-car vehicle dynamics. This data may be used to validate vehicle models.
A Practical Guide to Race Car Data Analysis was written for the amateur and lower-level professional racers who either have a data system in their cars or who may be thinking about installing one but who do not have access to an experienced data engineer. Many of the data systems available today at reasonable prices offer capabilities that only professional race teams could afford just a few years ago. Unfortunately, most of these racers do not know how to use more than a small part of those capabilities. Using real track data, numerous real-world examples, and more than 200 illustrations, the Guide gives them the knowledge and skills they need to select, configure and use their data systems efficiently and effectively.Beginning with a detailed discussion of the things racers need to know about the hardware and software necessary for a an effective data system, the Guide continues with chapters on basic data analysis tools, more sophisticated data analysis tools like x-y plots and math channels, damper potentiometers and the wealth of important data they produce, brake and clutch pressure sensors, and creative use of math channels. The Guide concludes with a comprehensive scheme for analyzing data, examples of the data views used with the scheme, and detailed information on how to create and configure the data views.
Vehicle dynamics on a Formula SAE vehicle are inter-dependent with almost all mechanical systems on the car and require a thorough understanding of design tradeoffs in order to maximize the vehicle's acceleration capabilities while maintaining consistent driver feedback. This thesis summarizes the developments and accumulated knowledge on MIT's Formula SAE team with regards to suspension and vehicle dynamics of the 2018 - 2020 seasons in order to inform the design and vehicle development for future years. Vehicle kinematics, vehicle dynamics, and tire selection are covered, in addition to the impact of aerodynamics, steering, and control arms on suspension development. Areas for further research are described. Throughout the thesis, the importance of quantifying and documenting design decisions is highlighted.