The paper presents the design, development, and implementation of a telemetry system able to acquire the vehicle parameters and process them in real time, thanks to a specific mathematical model. The live data provided to the driver helps establishing the best driving strategy, also thank to a continuous connection with the pitwall. The architecture of the telemetry system consists of an electronic board, capable of managing information towards the driver, received from a smartphone, and forwarded to the cloud for external monitoring, which allows for real-time changes to the control strategy. In particular, the developed system has been used during the Shell Eco-marathon competition to obtain the lowest possible consumption.

A telemetry-driven architecture for the development of data-intensive race strategies / De Carlo, Matteo; Simeone, Emanuele; Radano, Luigi; Carello, Massimiliana. - ELETTRONICO. - 1:(2024), pp. 1-6. (Intervento presentato al convegno 2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) tenutosi a Victoria (SY) nel 1-2 February 2024) [10.1109/acdsa59508.2024.10467558].

A telemetry-driven architecture for the development of data-intensive race strategies

De Carlo, Matteo;Simeone, Emanuele;Radano, Luigi;Carello, Massimiliana
2024

Abstract

The paper presents the design, development, and implementation of a telemetry system able to acquire the vehicle parameters and process them in real time, thanks to a specific mathematical model. The live data provided to the driver helps establishing the best driving strategy, also thank to a continuous connection with the pitwall. The architecture of the telemetry system consists of an electronic board, capable of managing information towards the driver, received from a smartphone, and forwarded to the cloud for external monitoring, which allows for real-time changes to the control strategy. In particular, the developed system has been used during the Shell Eco-marathon competition to obtain the lowest possible consumption.
2024
979-8-3503-9452-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2991143
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