Data Acquisition Device (DAQ) is an electronic component used in formula student vehicles. To optimize the performance of the formula student vehicle and its driver, it is necessary to analyze and ...monitor the data acquisition system. Parameters acquired on the car include the position of the brake pedal/throttole and wheel speed. DAQ system has 5 input channels namely 3 analog input pins and 2 digital input pins, and 3 output channels, which is the controller pin, fault pin, and brake light pin. The DAQ system in this research is designed and made using Teensy 3.6, a signal conditioning circuit consisting of an RC low pass filter, voltage follower, non-inverting amplifier, and logic level shifter. DAQ system uses CANBUS to read and process sensor data. DAQ system can acquire data from the KTC Linear Motion Position sensor PZ-12-A-50P with an accuracy value of 99,91%; Hall-effect Rotary Position sensor RTY120LVNAX with an accuracy value of 99,94% for both the first and second sensors; and Proximity sensor LJ12A3-4-Z/BX with an accuracy value of 99,58% for the first sensor and 99,46% for the second sensor. DAQ is able to run controller signal processing, detect faults, and activate brake light signal according to FSAE rules.
The braking system is one of the most critical systems in the vehicle as it ensures drivers' safety. The brake master cylinder is the medium of pressurization that converts brake pedal force into ...brake pressure. The main objective of this paper is to design a swivelling brake master cylinder of the hydraulic braking system for a Formula Society Automotive Engineers (FSAE) vehicle that is best suited for cost-effective manufacturing. Due considerations are given to safety on maximum operating conditions of driver effort and friction coefficient, along with precision manufacturing to attain desired tolerances relative to its applications with seals. The design is based on its use in swiveling geometry for a compact assembly. Multiple simulations were performed to finalize the material and corresponding manufacturing techniques to make assembly efficient and cost-effective without compromising safety and reliability.
The ways to reduce the number of wires suitable for the main control unit were considered. A block diagram of the algorithm of actions of the created special device is proposed, which allows ...minimizing the number of wires. The format of CAN-messages containing data from all polled sensors and an electrical circuit diagram is presented. A general view of the developed device is presented, which made it possible to reduce the number of signal wires running through the entire vehicle to two pieces.
The proliferation of electric vehicle (EV) technology is an important step towards a more sustainable future. In the current work, two-layer feed-forward artificial neural-network-based machine ...learning is applied to design soft sensors to estimate the state of charge (SOC), state of energy (SOE), and power loss (PL) of a formula student electric vehicle (FSEV) battery-pack system. The proposed soft sensors were designed to predict the SOC, SOE, and PL of the EV battery pack on the basis of the input current profile. The input current profile was derived on the basis of the designed vehicle parameters, and formula Bharat track features and guidelines. All developed soft sensors were tested for mean squared error (MSE) and R-squared metrics of the dataset partitions; equations relating the derived and predicted outputs; error histograms of the training, validation, and testing datasets; training state indicators such as gradient, mu, and validation fails; validation performance over successive epochs; and predicted versus derived plots over one lap time. Moreover, the prediction accuracy of the proposed soft sensors was compared against linear or nonlinear regression models and parametric structure models used for system identification such as autoregressive with exogenous variables (ARX), autoregressive moving average with exogenous variables (ARMAX), output error (OE) and Box Jenkins (BJ). The testing dataset accuracy of the proposed FSEV SOC, SOE, PL soft sensors was 99.96%, 99.96%, and 99.99%, respectively. The proposed soft sensors attained higher prediction accuracy than that of the modelling structures mentioned above. FSEV results also indicated that the SOC and SOE dropped from 97% to 93.5% and 93.8%, respectively, during the running time of 118 s (one lap time). Thus, two-layer feed-forward neural-network-based soft sensors can be applied for the effective monitoring and prediction of SOC, SOE, and PL during the operation of EVs.
The current impact attenuator used by the Formula Student team of University of Lisbon is an out-of-shelf solution consisting in an aluminum honeycomb. The competition regulations defined for the ...impact attenuator's design allow room for innovation, which can be used to build more efficient structures and explore new materials. The main objective of this work is to design and optimize a composite impact attenuator lighter than the solution currently used by the team. Experimental results and numerical models presented in previous works are considered in the development of a new approach. Several design parameters are studied and their influence on the behavior of the impact attenuators are taken into account. Direct Multisearch (DMS) algorithm directly coupled to Abaqus software is used to perform the optimizations. The lighter solutions' mass is compared to the baseline aluminum structure's and detailed descriptions are presented for chosen optimal designs, which constitute an improvement regarding the baseline's mass.
This study involves the development of a Suspension system for FSAE vehicles participating in the Combustion Category. The front setup is also introduced with a bar-type Anti-Roll Bar (ARB) to ...manipulate the Understeer and Oversteer response of the vehicle. The initial parametric study was performed with an iterative approach in the spreadsheet. Race-cars also have stiffer suspension i.e.; the ride frequency is above 2 Hz; the reason being that the driver does strict maneuvering on the race track. FSAE vehicles have ARB's for better cornering performance and to manipulate the response of the vehicle mainly understeer and oversteer suiting to the driver. Another advantage is the limitation of camber gain caused by the body roll as it improves the traction. Further, the Kinematic study of all the components in the system was analyzed through IPG Kinematic Software. The focus was made on the variation of Camber Angle, Steer Angle, Track Change, and Roll Angle with and without the ARB incorporation. The calculation for the selection of different bearings is also performed. Considering the previous vehicles and the new design goals, parametrizing of the vehicle is also performed. The overhang of the vehicle plays an important factor in the longitudinal load transfer during the braking and acceleration. Forces experienced by all the components were also extracted from the software. This data is then used as the input parameter for Structural Simulation on CAE platform ANSYS. Material properties of Aluminum 6061 T-6 are used for the Bell Cranks and carbon Steel is used for ARB setup. Static structural simulation is performed on the Front Rocker, Upright and Hub. Specific torsional simulation is done on the ARB considering the axial offset position of the support bearing and the loading point on the blade.
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