Purpose
This paper aims to present the design process, manufacturing and testing of a prototype of an axle carrier for Formula Student race car. The axle carrier is topologically optimized and ...additively manufactured using selective laser melting (SLM).
Design/methodology/approach
The shape of the axle carrier was created in three design stages using topology optimization and four additional design stages based on finite element calculations and experimental testing. Topology optimization was performed on the basis of relevant load cases. The sixth design stage was manufactured by SLM and then tested on a loading device together with photogrammetry measurement to obtain the real deformation. Measured deformations were compared with deformation calculated by the finite element method (FEM), verified and experiences used in the last design stage.
Findings
An additively manufactured axle carrier has a minimal safety factor of 1.2 according to experimental testing. The weight and maximal deformations are comparable with the milled part, although the material has about 50 per cent worse yield strength. The topologically optimized axle carrier proved big potential in the effective distribution of material and the improvement of toughness.
Practical implications
This paper helps the Formula Student team to enhance the driving performance while keeping low weight. It also improves further development and upgrading of the race car.
Originality/value
The whole design of the topologically optimized part was investigated – from estimation of the loads to experimental verification of FEM analysis on real part.
In this paper, we present the adaptation of the terminal component learning-based model predictive control (TC-LMPC) architecture for autonomous racing to the Formula Student Driverless (FSD) ...context. We test the TC-LMPC architecture, a reference-free controller that is able to learn from previous iterations by building an appropriate terminal safe set and terminal cost from collected trajectories and input sequences, in a vehicle simulator dedicated to the FSD competition. One major problem in autonomous racing is the difficulty in obtaining accurate highly nonlinear vehicle models that cover the entire performance envelope. This is more severe as the controller pushes for incrementally more aggressive behavior. To address this problem, we use offline and online measurements and machine learning (ML) techniques for the online adaptation of the vehicle model. We test two sparse Gaussian process regression (GPR) approximations for model learning. The novelty in the model learning segment is the use of a selection method for the initial training dataset that maximizes the information gain criterion. The TC-LMPC with model learning achieves a 5.9 s reduction (3%) in the total 10-lap FSD race time.
This paper presents a torque controller for the energy optimization of the powertrain of an electric Formula Student race car. Limited battery capacity within electric race car designs requires ...energy management solutions to minimize lap time while simultaneously controlling and managing the overall energy consumption to finish the race. The energy-managing torque control algorithm developed in this work optimizes the finite onboard energy from the battery pack to reduce lap time and energy consumption when energy deficits occur. The longitudinal dynamics of the vehicle were represented by a linearized first-principles model and validated against a parameterized electric Formula Student race car model in commercial lap time simulation software. A Simulink-based model predictive controller (MPC) architecture was created to balance energy use requirements with optimum lap time. This controller was tested against a hardware-limited and torque-limited system in a constant torque request and a varying torque request scenario. The controller decreased the elapsed time to complete a 150 m straight-line acceleration by 11.4% over the torque-limited solution and 13.5% in a 150 m Formula Student manoeuvre.
Engineering Design Communication is the main tributary for the sharing of information, knowledge & insights, and is fundamental to engineering work. Engineers spend a significant portion of their day ...communicating as they ‘fill in the gaps’ left by formal documentation and processes. Therefore, it comes as no surprise that there is much extant literature on this subject. The majority has been descriptive with little prescriptive research involving the introduction of either a tool or process. To begin to address this, previous work reports a Social Media framework to support Engineering Design Communication and this paper builds upon this previous work through the instantiation of the framework within a custom-built Social Media tool hereto referred to as PartBook. This has been prescribed within an eleven week race car design project. The study addresses the validation of the requirements that underpin the Social Media framework as well as investigating the impact the tool has/may have on engineering work, engineering artefacts and engineering project management. In order to do so, data has been captured through user activity, system usability, questionnaire, semi-structured interview and informal feedback.
This work presents a computational fluid dynamic (CFD) analysis of a drag reduction system (DRS) used in a Formula Student competition vehicle, focusing on the interaction between the triple wing ...elements, as well as on the electrical actuators used to provide movement to the upper two flaps. The S1123 wing profile was chosen, and a 2D analysis of the wing profile was made. The trailing edge was rounded off to conform to Formula Student competition safety rules, resulting in around a 4% decrease in the lift coefficient and around a 12% increase in the drag coefficient for an angle of attack of 12°, compared to the original wing profile. The multi-element profile characteristics are: wing main plate with 4°, first flap 28°, and second flap 60°. To evaluate the wing operation, end plates and electrical linear actuators were added, generating a maximum lift coefficient of 1.160 and drag coefficient of 0.397, which provides around a 10% reduction in lift and a 9% increase in drag compared to the absence of the linear actuators. When activating the DRS, the flap rotation generates about a 78% decrease in the aerodynamic drag coefficient and 53% in the lift coefficient for the minimum aerodynamic drag setting.
When it comes to racing applications, the primary engineering goal is to increase the performance envelope of the vehicle for a given set of tires. To achieve this goal, it is necessary to maximize ...the normal loads on the wheels while at the same time minimizing the tire load variation. The purpose of this paper is to present a mathematical model for a Formula Student car in order to study if performance gains are achieved by replacing the traditional passive suspension with a hydraulically interconnected suspension system. To have a complete picture of the advantages and disadvantages of each system, two vibrating models with 7 degrees of freedom were created in order to simulate the motion response of a Formula Student car to realistic excitations. Two particular interpretations of the results were chosen as important performance indicators. The first one is given by the pitch stability of the chassis relative to the road, which can be linked with a decrease in downforce load variation. The second one is the ability of the wheel to follow the road profile as closely as possible, which can be directly correlated with the amount of mechanical grip of the vehicle. The simulation results indicate that the hydraulically interconnected suspension system offers better results for both proposed cases but at the expense of the roll stability of the vehicle.
This study explains a coherent flow for designing, manufacturing, analyzing, and testing a tunable anti-roll bar system for a formula student racecar. The design process starts with the analytical ...calculation for roll stiffness using constraining parameters such as CG (Center of Gravity) height, total mass, and weight distribution in conjunction with suspension geometry. Then, the material selection for the design i.e. Aluminum 7075 T6 is made based on parameters such as density and modulus of rigidity. A MATLAB program is used to iterate deflection vs load for different stiffness and shaft diameter values. This is then checked with kinematic deflection values in Solidworks geometry. To validate with the material deflection, finite element analysis is performed on ANSYS workbench. Manufacturing accuracy for the job is checked using both static analysis in lab settings and using sensors on vehicles during on-track testing. The error percentage is found to be 4% between the target stiffness and the one obtained from static testing. Parameters such as moment arm length, shaft diameter and length, and deflection were determined and validated. This paper shows the importance of an anti-roll bar device to tune the roll stiffness of the car without interfering with the ride stiffness.
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