Edward M. Kasprzak

The Formula SAE Tire Test Consortium— Tire Testing and Data Handling

The Formula SAE Tire Test Consortium (FSAE TTC) was established to provide high quality tire data to participating FSAE teams for use in the design and setup of their racecars. Currently, data on ten different constructions of tires has been measured at Calspan’s Tire Research Facility and distributed to all consortium members. In this paper we review the history of the FSAE TTC— the inception, organization and continuing operation of this all-volunteer effort. Details of tire testing will be explored, including the many options and constraints considered while designing the tire test matrix. Finally, a review of the measured data is provided. This includes a description of all the output channels and an overview of ways in which FSAE teams can make use of the data.

Racecar Optimization and Tradeoff Analysis in a Parallel Computing Environment

In this paper, we present an approach to the optimization of a racecar using vehicle dynamics simulation in a parallel-computing environment. The use of vehicle dynamics simulations in the automotive and auto racing industries is widespread. Complex vehicle simulations can include hundreds of parameters and be very computationally expensive to perform. This limits the number of design configurations that can be considered within a reasonable time, preventing thorough exploration of the design space. It also limits the usefulness of these simulations during the course of a race weekend when time is of the essence. In this paper, we present results from work to overcome this problem. Our results focus on determining the Pareto optimal designs for a vehicle model with three design variables running simulated races around corners of different radii.

Inflation pressure effects in the nondimensional tire model

Inflation pressure affects every aspect of tire performance. Most tire models, including the Radt/Milliken Nondimensional Tire Model, are restricted to modeling a single inflation pressure at a time. This is a reasonable limitation, in that the Nondimensional model forms an input/output relationship between tire operating conditions and force & moment outputs. Traditional operating conditions are normal load, slip angle, inclination angle, slip ratio and road surface friction coefficient. Tire pressure is more like a tire parameter than a tire operating condition. Since the Nondimensional Tire Model is semi-empirical it does not specifically deal with tire parameters like sidewall height or tread compound. Still, tire pressure is the easiest tire parameter to change, and as the air temperature within the tire varies during use so does the inflation pressure. Thus, it is desirable to incorporate inflation pressure into the Nondimensional Tire Model as an input. This paper discusses the effects of tire pressure on tire force and moment output. Effects on lateral force and aligning torque are investigated in detail. Additionally, the effects on cornering stiffness, friction coefficients, peak aligning torque coefficient and peak shape are reviewed. New techniques to implement pressure effects in the Nondimensional Model are presented. Applications of these techniques are shown on a Formula SAE tire and a full-size radial racing tire. Additionally, the effects of inflation pressure on tire spring rate and loaded radius are investigated. While these are not modeled using Nondimensional techniques, they are important variables accompanying any tire model.

Experiential learning in vehicle dynamics education via motion simulation and interactive gaming

Creating active, student-centered learning situations in postsecondary education is an ongoing challenge for engineering educators. Contemporary students familiar with visually engaging and fast-paced games can find traditional classroom methods of lecture and guided laboratory experiments limiting. This paper presents a methodology that incorporates driving simulation, motion simulation, and educational practices into an engaging, gaming-inspired simulation framework for a vehicle dynamics curriculum. The approach is designed to promote active student participation in authentic engineering experiences that enhance learning about road vehicle dynamics. The paper presents the student use of physical simulation and large-scale visualization to discover the impact that design decisions have on vehicle design using a gaming interface. The approach is evaluated using two experiments incorporated into a sequence of two upper level mechanical engineering courses.

Tire asymmetries and pressure variations in the radt/milliken nondimensional tire model

The Nondimensional Tire Model is based on the idea of data compression to load-independent curves. Through the use of appropriate transforms, tire data can be manipulated such that, when plotted in nondimensiona l coordinates, all data falls on a single curve. This leads to a highly efficient and mathematically consistent tire model. In the past, data for slip angle and slip ratio has been averaged across positive and negative values for use with the transforms. In this paper, techniques to handle tire asymmetries in lateral and longitudinal force are presented. This is an important advance, since in passenger cars driving/braking data is almost always asymmetric and, depending on tire construction, lateral force data may follow likewise. In addition, this paper is the first to explore the inclusion of inflation pressure as an operating variable in the Nondimensional Tire Theory. Inflation pressure affects the shape of the tire curves, notably the linear range stiffness and peak force friction coefficient. With this new variable, the operating conditions addressed by Nondimensional Tire Theory now include slip angle, slip ratio, inclination angle, normal load, surface friction coefficient and inflation pressure.

Design and Optimization of Reconfigurable Vehicle Platforms

Continuous advancements in technology have resulted in customers expecting enhanced performance across a variety of diverse and changing operating conditions. When multiple system objectives exist, traditional design techniques incorporate tradeoffs to reach a final design. In this paper, the desire to meet a variety of system objectives is accomplished through the design of reconfigurable systems. Reconfigurable systems are capable of undergoing changes to their configuration to meet new objectives, function effectively in varying operating environments, and deliver value in dynamic market conditions. However, permitting such changes to a system increases complexity and cost, from both a monetary perspective and allocation of resources. If this increase is too large, only a subset of design variables can be made adaptable, making the need for incorporating product platforming apparent. The intelligent design of a core architecture to accommodate the changing number of adaptable design variables allows for broader applications when technical and economic constraints are present. To illustrate this approach, a case study involving the design and optimization of a reconfigurable race car is introduced. The performance of this vehicle is assessed on different racetracks, with the overall goal being the minimization of the time required to traverse each track section. The results from this case study demonstrate the effectiveness of combining reconfigurable system design with product platforming techniques to achieve individualized products that meet the many demands of the consumer.

Motion Simulation Experiments for Driver Behavior and Road Vehicle Dynamics

This paper discusses the design and development of a motion-based driving simulation and its integration into driving simulation research. The integration of the simulation environment into a road vehicle dynamics curriculum is also presented. The simulation environment provides an immersive experience to conduct a wide range of research on driving behavior, vehicle design and intelligent traffic systems. From an education perspective, the environment is designed to promote hands-on student participation in realworld engineering experiences that enhance conventional learning mechanisms for road vehicle dynamics and engineering systems analysis. The paper assesses the impact of the environment on student learning objectives in an upper level vehicle dynamics course and presents results from research involving teenage drivers. The paper presents an integrated framework for the use of real-time simulation and large-scale visualization to both study driving behaviors and to discover the impact that design decisions have on vehicle design using a realistic simulated driving interface. [DOI: 10.1115/1.3617437]

Modeling of Supply Chain Decision Logic Using PID Controllers

Most manufacturing takes place in the context of a supply chain. Each station in the supply chain must not only manufacture a product but also decide how much to produce. This decision is influenced by the supply of materials/components from the next station down in the supply chain and the demand from the next station up. With the advent of increased customization, inventory management is increasingly becoming a critical issue in the manufacturing process. In this paper we model the decision logic at each stage of a supply chain system through the use of system identification and PID controllers. The goal is to investigate and manage the costs of manufacturing a product in the context of a supply chain. It is assumed that the supply chain has well-understood interactions between individual positions, allowing for a focus on the ordering decision logic. A review of ordering strategies is presented, and a discussion of the difficulties in determining PID gains for human decision makers is included. The results show a range of correlation between the PID simulation and measured supply chain inventories. This stems from a number of factors, which are discussed. Additionally, ordering strategies to optimize the supply chain are investigated.Copyright