Race Car Research Articles

Airfoil Design and Aerodynamics Characteristics of Energy-Efficient Race Car: CFD Analysis

The use of land transportation, primarily cars, is increasing annually. The energy required will increase along with the number of vehicles. Thus far, car manufacturers are required to improve car designs and propose fuel-efficient and environmentally friendly cars. The energy-efficient car competition, namely, Kontes Mobil Hemat Energi Indonesia, is organised for mechanical engineering students to contribute directly to research related to energy-efficient cars in Indonesia. One of the ways to save fuel is to reduce the aerodynamic force drag on the vehicle. This study aims to optimize the prototype vehicle airfoil design in producing the smallest possible coefficient of drag (Cd) and lift (Cl). A Taguchi design of experimental (DoE) is applied to set the 9 designs for this study, with three different values considered for each design parameters: Defiant Canard BL110, Clark YM15, Gottingen 256 for side airfoil shapes and Gottingen 410, Gottingen 460, and Boeing 737 Root for top airfoil shapes. This aerodynamic analysis uses the ANSYS 2020 R1 software, which is carried out at a speed of 30 km/h. Then the Cd and Cl values obtained will be analyzed. The results obtained for the optimal design of the Cd with variations in the side airfoil design Defiant Canard BL110 and top airfoil is Gottingen 410 with a Cd value of 0,1119. As for the optimal design of the Cl with variations in the side airfoil design Gottingen 256 and top airfoil is Gottingen 460 with a Cl value of 0,0250.

Safe and Reliable Movement of Fast LiDAR-based Self-driving Vehicle

Classification of objects is an important technique for autonomous ground vehicles to identify a surrounding environment and execute safe path planning. In this paper, a method based on horizontal segmentation is proposed to detect cone-shaped objects in vehicle’s vicinity using a LiDAR sensor. A captured point cloud is divided into five layers based on height information, and the division of detected objects into two groups, cones and others, has been made using classifiers available in MATLAB toolboxes. To separate the classified conical objects into four types used to mark the route, an algorithm for their recognition was developed and used. The proposed solution, verified by navigation experiments in real conditions using an unmanned racing car, has gave good results, i.e., a high rate of cone-shaped objects classification, a short processing time and a low computational load. The performed tests have allowed also to diagnose the causes of incorrect classification of objects. Thus, the experimental results indicated that the approach presented in this work can be used in real time for autonomous, collision-free driving along marked routes.

Research on Improved Algorithms for Cone Bucket Detection in Formula Unmanned Competition.

The model network based on YOLOv8 for detecting race cones and buckets in the Formula Unmanned Competition for Chinese university students needs help with problems with complex structure, redundant number of parameters, and computation, significantly affecting detection efficiency. A lightweight detection model based on YOLOv8 is proposed to address these problems. The model includes improving the backbone network, neck network, and detection head, as well as introducing knowledge distillation and other techniques to construct a lightweight model. The specific improvements are as follows: firstly, the backbone network for extracting features is improved by introducing the ADown module in YOLOv9 to replace the convolution module used for downsampling in the YOLOv8 network, and secondly, the FasterBlock in FasterNet network was introduced to replace the fusion module in YOLOv8 C2f, and then the self-developed lightweight detection head was introduced to improve the detection performance while achieving lightweight. Finally, the detection performance was further improved by knowledge distillation. The experimental results on the public dataset FSACOCO show that the improved model's accuracy, recall, and average precision are 92.7%, 84.6%, and 91%, respectively. Compared with the original YOLOv8n detection model, the recall and average precision increase by 2.7 and 1.2 percentage points, the memory is half the original, and the model computation is 51%. The model significantly reduces the misdetection and leakage of conical buckets in real-vehicle tests and, at the same time, ensures the detection speed to satisfy the deployment requirements on tiny devices. Satisfies all the requirements for deployment of tiny devices in the race car of the China University Student Driverless Formula Competition. The improved method in this paper can be applied to conebucket detection in complex scenarios, and the improved idea can be carried over to the detection of other small targets.

Analisis Pengaruh Kualitas Pelayanan dan Kualitas Produk Terhadap Kepuasan Konsumen Produk Velg HSR di Alpha Racing Toko Velg Ban dan Sporing Mobil Kab. Karawang

The aim of this research is to find out how consumer satisfaction is influenced by product quality and service quality of HSR wheel products at the Alpha Racing Tire and Car Spring Wheel Shop, Karawang Regency. Data was collected through a survey using a questionnaire to consumers who had used HSR wheel products at the shop. Linear regression analysis is used to test the relationship between the independent variables (service quality and product quality) and the dependent variable (consumer satisfaction). Consumer satisfaction with HSR wheel items is significantly influenced by the quality of the product and the quality of the service provided, according to research findings. The research results show that the coefficient of determination (R Square) test results are zero point five two four, which shows that around fifty-two point four percent of the variability in consumer satisfaction can be explained by service quality and product quality. These findings highlight the importance of high quality services and products in meeting consumer expectations and satisfaction in the auto wheel industry. There is also a discussion of management consequences and recommendations for further research.

Performance analysis of electric motor for Formula Student Race car

Performance analysis of electric motor for Formula Student Race car

Low-Voltage Control Circuits of Formula Student Electric Racing Cars

Formula Student (FS) competitions aim to prepare and encourage engineering students to participate in the progression of automotive and motorsport industries. The built racing cars adhere to strict regulations set by competition guidelines to ensure the safety of both teams and spectators. For electric racing cars, the high-voltage (HV) battery system usually operates within a voltage range between 100 V to 600 V to supply the motor and its controller with the required electrical power. It is essential to ensure that these components are operating effectively to minimize battery and motor current as well as to ensure efficient and reliable performance throughout the race. A low-voltage control system (LVCS), usually operating at 12 V, is used to coordinate a wide array of critical operational and safety functions to control the HV system. These functions include: (1) turning on/off procedures, (2) monitoring speed, voltage, and current, (3) interfacing with pedals, (4) controlling dashboard features, (5) managing lighting, (6) facilitating data communication, and (7) implementing safety protocols. The design and operation of the LVCS are crucial for compliance with safety regulations and enhancing the FS electric racing car (FSERC) performance. This details and discusses the design procedures of the LVCS, using the Lancaster E-Racing (LER) FSERC as a case study. The LER car employs a 400 V battery system to power a 68-kW permanent manet synchronous motor (PMSM) using a three-phase voltage source inverter. Using mathematical analysis, SIMULINK/MATLAB® computer simulations, and the experimental real-data results provided by the LER FSERC, this study seeks to offer valuable insights regarding the LVCS practical implementation and optimization.

Design and optimization of planetary wheel systems for formula racing cars

Design and optimization of planetary wheel systems for formula racing cars

Localization robustness improvement for an autonomous race car using multiple extended Kalman filters

In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one based on vehicle speed, GNSS availability, and signal quality. The low-speed Kalman filters are based on a kinematic vehicle model while the high-speed variants are based on a dynamic vehicle model. Several measurements were performed during test maneuvers to evaluate the performance of the filters. The proposed method succesfully handles sensor miscalibration and GNSS outages.

Optimizing Electric Racing Car Performance through Telemetry-Integrated Battery Charging: A Response Surface Analysis Approach

Optimizing Electric Racing Car Performance through Telemetry-Integrated Battery Charging: A Response Surface Analysis Approach

RAndomized Cluster Evaluation of Cardiac ARrest Systems (RACE-CARS) trial: Study rationale and design

Out-of-hospital cardiac arrest (OHCA) occurs in nearly 350,000 people each year in the United States (US). Despite advances in pre- and in-hospital care, OHCA survival remains low and is highly variable across systems and regions. The critical barrier to improving cardiac arrest outcomes is not a lack of knowledge about effective interventions, but rather the widespread lack of systems of care to deliver interventions known to be successful. The RAndomized Cluster Evaluation of Cardiac ARrest Systems (RACE-CARS) trial is a 7-year pragmatic, cluster-randomized trial of 60 counties (57 clusters) in North Carolina using an established registry and is testing whether implementation of a customized set of strategically targeted community-based interventions improves survival to hospital discharge with good neurologic function in OHCA relative to control/standard care. The multi-faceted intervention comprises rapid cardiac arrest recognition and systematic bystander CPR instructions by 9-1-1 telecommunicators, comprehensive community CPR training and enhanced early automated external defibrillator (AED) use prior to emergency medical systems (EMS) arrival. Approximately 20,000 patients are expected to be enrolled in the RACE CARS Trial over 4 years of the assessment period. The primary endpoint is survival to hospital discharge with good neurologic outcome defined as a cerebral performance category (CPC) of 1 or 2. Secondary outcomes include the rate of bystander CPR, defibrillation prior to arrival of EMS, and quality of life. We aim to identify successful community- and systems-based strategies to improve outcomes of OHCA using a cluster randomized-controlled trial design that aims to provide a high level of evidence for future application.

Careers: Aakhilesh Singhania: This Bosch Engineer Speeds Hybrid Race Cars to the Finish Line

Careers: Aakhilesh Singhania: This Bosch Engineer Speeds Hybrid Race Cars to the Finish Line

Influence of Tire-Enveloping Model Complexity on High-Frequency Simulations

ABSTRACT Race tires are subject to high speeds and high vertical loads during cornering. They are also subject to extreme stress when they are driven over high-frequency and low-amplitude curbs, often leading to tire failures. Research and development by D. C. Davis and P. W. A. Zegelaar has shown that when the tire moves over high-frequency, low-amplitude, and short-wavelength obstacles, it exhibits obstacle-enveloping properties. Tire response over such obstacles includes vertical force variation, longitudinal force variation, and rotational speed variation. Additionally, such road inputs excite tire belt dynamics that include high-frequency modes. Therefore, a single-contact-point model is no longer sufficient to predict tire response over such obstacles. To better capture the tire obstacle-enveloping behavior, advanced contact patch models such as the tandem-cam model by P. W. A. Zegelaar, the radial–interradial spring model by J. M. Badalmenti and G. R. Davis Jr., and the flexible ring model by S. Gong have been developed. To capture high-frequency tire belt dynamics, the rigid-ring model has been developed by P. W. A. Zegelaar. Previous work combines the rigid-ring model with the tandem-cam model to capture obstacle-enveloping behavior and tire belt dynamics up to 60–100 Hz. This paper presents a comparative study of different tire–road contact models to simulate high-frequency curbs typically found at racetracks. The curb profile of the Singes corner at the Paul Ricard racetrack is chosen for simulations as it is known to be extremely demanding on the tires, often causing failures. An advanced four-wheel model is used to simulate a race car at high speeds. Metrics to quantify the tire response over these high-frequency curbs are created and an investigation is conducted to quantify the influence of tire model complexity on the metrics.

Effects of Race Car's Speed on the Aerodynamic Aspect Using Computational Fluid Dynamics Analysis

This research employs Computational Fluid Dynamics (CFD) methods to investigate the intricate relationship between race car speed and external aerodynamics during high-performance racing competitions. The primary objectives encompass the application of CFD in pre-processing and analyzing external aerodynamic aspects, coupled with a comprehensive examination of the external flow around a race car for a nuanced understanding of its aerodynamic performance. Various car speeds were considered with the RANS (k-ω SST) turbulent model. The results unveiled a direct correlation between inlet velocity and the maximum velocity attained by the race car. The aerodynamic design intricately directs the airflow, leading to higher velocities predominantly along the upper part of the car body. Noteworthy is the revelation that the highest recorded maximum velocity of 231.06 m/s coincides with a peak inlet velocity of 200 m/s, suggesting a consistent increase in maximum velocity with rising inlet velocity. This research emphasizes the pivotal role of inlet velocity in achieving peak car speed performance. It sheds light on the significance of turbulent model selection in capturing the complexities of external flow dynamics. This knowledge contributes to optimizing the external aerodynamics of race car body design, ultimately enhancing performance and competitiveness in the dynamic world of Formula 1 racing.

A Phenomenological Evaluation of the Psychological Factors That Influence Motorsports Performance

Race car drivers not only face high-speed challenges but also need to manage complex team dynamics and sponsor relations and are exposed to unique fan access while competing. This study examines the unique psychological aspects of motorsports and how race car drivers currently train psychological skills to match these distinctive demands. Adopting a phenomenological approach, this study involved semistructured interviews with 11 professional race car drivers. The interviews focused on drivers’ psychological experiences during racing and their psychological preparation. Thematic analysis of the interview data revealed key psychological factors impacting performance. These included concentration, confidence, anxiety, managing emotional states, unique social aspects, and motivation. Drivers also had an interest in psychological-skills training but reported a lack of resources and consistent application. This study highlights the unique psychological challenges presented in motorsports, and the findings underscore the need for targeted psychological-skills training and resources for race car drivers.

The way to maintain the stability of race cars at high speed

Nowadays, cars are used quite often and require good stability and handling while driving to keep passengers safe. At the same time, the race car also must have better stability and handling at high speeds than family cars so that they can ensure that the driver can handle the track and get the best performance in extreme conditions. Therefore, the shape of the vehicle and the design of the different components play a key role in ensuring its stability at high speeds. From an aerodynamic point of view, the streamlined body design, the application of spoilers, the design of the tail and the ground effect are all factors that are crucial to the stability of the car. This paper will look at how the race car remains stable at high speeds from an aerodynamic perspective, and how its shape and different components of the car affect its stability and handling. From our research, we find that all of them have crucial effects and exist different forces on the car body

Evaluating the Impact of Environmental and Operational Conditions on the Characteristics of CFRP Epoxy Composites

The purpose of this study is to determine the material properties of CFRP composites in the form of a fabric for the construction of racing car bodywork. This work focused on the determination of the strength and tribological properties as well as investigating the effects of the operating environment on the developed material. Three material variants, differing in the number of layers used to produce the reinforcement, were used in this study. The tests were carried out on two-/three-/four-layer sheets produced by infusion. Due to the later use of the tested composites for the sheathing of a racing car, the results obtained were analysed in terms of the most favourable strength properties while keeping the weight as low as possible. In this study, the hardness, impact strength, and tensile and bending stresses of the developed composites were examined. In addition to the strength properties, the density, the effects of immersion in water, and the composite’s resistance to staining and friction in the presence of aggressive media were also checked. The structure and the breakthroughs resulting from the strength tests were observed using a stereoscopic microscope. The material’s resistance to sunlight and UVB was also tested.

DFA Analysis Revolutionizes FSAE Steering, Enhancing Efficiency in Automotive Design

In the dynamic realm of automotive engineering, particularly in Formula Society of Automotive Engineers (FSAE) racing, where vehicle assessment is based on efficiency, motor power, chassis dynamics, and steering, there exists a notable focus on steering system design. This research delves into the conceptualization and component development aimed at aiding automotive mechanics in crafting steering systems for FSAE race cars. Employing Solid Edge 2021 software, the study utilizes the Design of Assembly (DFA) analysis method to streamline the mechanical process. Through DFA analysis, the study assesses various Technical Attributes (TAs) of the steering system, revealing values ranging from 0.548 to 1.765. The ideal steering system ensures that the desired steering input by the driver aligns with the output motion of the vehicle, known as the Ackerman condition. Steering gear mechanisms translate rotational motion into translation and adjust the effort applied to the steering linkage. The study's findings contribute to the advancement of steering system design in FSAE vehicles, emphasizing ergonomic considerations and the utilization of advanced software tools like Catia and Solid Edge 2021 for enhanced performance and safety. Highlight: FSAE steering: DFA analysis enhances design efficiency for racing vehicles. Software aid: Solid Edge 2021 streamlines FSAE steering system development. Ergonomic focus: Design prioritizes driver comfort and vehicle performance optimization. Keywoard: FSAE vehicles, Steering system design, DFA analysis, Solid Edge 2021, Ergonomics

Computational Analysis of Aerodynamic Drafting Effects in Lemans Racing Cars

Le Mans racing is a comprehensive motorsport event that tests not only the long-distance stability of race cars but also considers fuel economy and speed, where aerodynamics plays a crucial role. Many manufacturers place great emphasis on the aerodynamic design of race cars. However, in-depth research on the application of drafting effects in Le Mans racing and studies on team formations are somewhat lacking. Through Ansys simulations, this study deeply explores the impact of drafting on race cars and, by varying the distances between cars, identifies differences in air resistance encountered by different formations. The findings reveal that drafting can substantially decrease the aerodynamic drag experienced by race cars when they are positioned at relatively close proximities to each other. As this distance increases, a "drag bubble" phenomenon occurs within a certain range, where the trailing cars begin to experience increased resistance. On the other hand, the study of car formations under race-regulated conditions has identified optimal vehicle spacing that minimizes the average aerodynamic drag faced by the team, providing strategic insights into the arrangement of team formations for improved race performance.

A novel model predictive controller for the drifting vehicle to track a circular trajectory

ABSTRACT In rally racing, a high sideslip cornering technique known as drifting is employed to minimise the lap time. However, for autonomous vehicles, tracking the trajectory while drifting is a challenging control problem due to the conflict between the two objectives. This paper proposes a novel model predictive controller (MPC) with two operation modes to address this conflict. In Mode 1, fuzzy expert strategies combined with the lateral error are designed to calculate the drift equilibrium point. Subsequently, the linear MPC controller is utilised to achieve quick adjustments of the lateral error. In Mode 2, terminal state constraints and error constraints are added to the MPC optimisation problem. The stability of the MPC controller is guaranteed to keep the vehicle within the expected error range. Finally, a comparison between the existing expert controller and the proposed controller is carried out on both the CarSim platform and a 1:10 scale race car. The results demonstrate that the proposed controller outperforms the existing expert controller in terms of tracking performance and drift stability.

An environmental life cycle assessment of electric race car: a case study of eVarta

AbstractThe study concerns the life cycle assessment (LCA) of a prototype electric racing car, Formula Student, developed by students of the Poznan University of Technology under the name of eVarta. The main objective of this study is to identify critical environmental points and indicate key elements of the vehicle's life cycle, along with the impact of the assumptions made. In the first part of the work, a literature review and standard review are conducted to organise the information and methodological steps for the LCA components and their application in the subsequent stages of the study. The work focusses on defining the right assumptions, the process of data collection and its appropriate aggregation, as well as the creation of a functional structure for the object under study. SimaPRO software is used to perform the assessment. The results of the evaluation show the high importance of the vehicle transportation stage in the entire life cycle and the significant impact of the transport-related processes, mostly considering the fact that the eVarta is a concept racing car, used only in specific conditions of Formula Student races around the world. Most of the distances between races are covered using external transport means, and eVarta is used only for racing. The second main source of environmental impacts is related to the use of resources associated with the production of the high-voltage traction battery and the use of aluminium and related processes. eVarta is a custom concept race car, designed and built by the team of students from different faculties at Poznan University of Technology (Poland). As a prototype, eVarta demonstrates high levels of environmental burden related to the production of materials and techniques. The proportion of these impacts may be limited by using a 3D CAD model to improve the information flows regarding the production of all parts. Moreover, the reduction of the environmental impacts may be reached by: (a) enhancement of production of traction battery, (b) substitution of construction materials, and (c) improvements during use, e.g. implementation of energy recovery systems during braking. Graphical Abstract