The link between the world of communications and the world of racing is provided by the telemetry systems in electric racing cars. These systems send real-time data about the vehicle’s behavior and systems to enable informed decisions during the race. The objective of this research was to integrate telemetry into the battery bank of an electric racing car in order to find the optimal values of current and voltage that optimize the charging process and thus improve the performance of the vehicle in competition using Response Surface Analysis. Specifically, the telemetry system consisted of an Arduino Mega, a digital wattmeter, and temperature sensors, all installed in the vehicle. Once the telemetry data were obtained, a response surface design was fitted with current, voltage, and temperature as factors varying from low to high values, with the objective function being to minimize the battery charging time. Using the response surface methodology and the steepest descent algorithm, it was found that all factors significantly affect the charging time, with the minimum charging time being 6961 s, obtained with a current of 2.4 amps and voltages of 50.5 volts and 43.6 volts.

Este artículo presenta el análisis estructural de una jaula de seguridad para Renault Logan 2005 bajo la normatividad de la Federación Internacional de Automovilismo para vehículos de turismo; particularmente, se considera el ensayo de carga vertical sobre el arco principal. Se llevaron a cabo simulaciones por medio de un software de elementos finitos, en las cuales se definieron la geometría y material usado, además de establecer las condiciones de frontera, carga y contactos. Se analizó el comportamiento mecánico bajo la carga exigida por FIA de 90 KN teniendo en cuenta el criterio de falla de la energía de distorsión y la deformación total. Posteriormente, se encontró que deformaciones permanentes pueden originarse por encima de 32.2 KN, mientras que fallas localizadas pueden presentarse por encima de 44 KN. Hay que mencionar además que los resultados demuestran que la implementación de las exigencias mínimas geométricas, de material y de manufactura de FIA no garantizan necesariamente la seguridad de la estructura.

This paper presents a detailed fifth-order mathematical model of a three-phase induction motor, used in the WECC (Western Electricity Coordinating Council) composite load model. The main objective is to analyze the dynamic behavior of three-phase induction motors during fault-induced delayed voltage recovery (FIDVR) events, a critical phenomenon in power system voltage stability. The model is implemented in MATLAB/Simulink and validated by comparing its results with previous studies, demonstrating its ability to capture transient and subtransient responses under voltage disturbances. Different types of motors (A, B, and C) are analyzed, and variations in load and voltage disturbance magnitudes are studied. The results show that the model is accurate and robust, making it useful for voltage stability studies in systems with high induction motor penetration. However, the model has limitations, such as the lack of consideration for frequency drives and protection systems, suggesting areas for future research.

The link between the world of communication and the world of racing is provided by telemetry systems in electric racing cars. These systems send real-time data about the vehicle’s behavior and systems to enable informed decisions during the race. The aim of this research was to integrate telemetry into the battery bank of a racing electric vehicle to find the optimal values of current and voltage that optimize the charging process, thus improving the vehicle’s performance in competition using Response Surface Analysis. Particularly, the telemetry system consisted of an Arduino Mega, a digital wattmeter, and temperature sensors, all installed in the vehicle. Once the telemetry data was obtained, a response surface design was adapted with current, voltage, and temperature as factors, varying from low to high values, with the objective function being to minimize the battery’s charging time. Applying the response surface methodology and the steepest descent algorithm, it was found that all factors significantly affect the charging time, with the minimum charge time being 6961 seconds, obtained with a current of 2.4 amps and voltages of 50.5 volts and 43.6 volts.