Growing concerns about CO2 emissions and global warming are driving the electrifica- tion of the transportation sector through the adoption of electric vehicles (EVs). In recent years, significant advancements in batteries technologies have contributed to no- table market growth. Nevertheless, the limited driving range of EVs continues to pose a challenge to broader adoption. To address this issue, the first part of this thesis focuses on the development of a driving simulator for electric vehicles. The simulator integrates both hardware and software components to realistically replicate the behaviour of an EV within a real-world driving environment. Results indicate that the simulator effectively reproduces driving dynamics with an acceptable degree of uncertainty. In the second part of the thesis, the simulator is employed to analyse driving behaviour. A study was conducted involving twelve participants, evenly divided by gender, across three driving scenarios that included urban and highway routes, both with and without traffic. Fuzzy Logic was used to assess driving styles, outputting a Driving Behaviour index (DBI) to intuitively identify the aggressiveness. Each participant repeated the tests during three different times of day — morning, afternoon, and evening — to investigate variations in driving behaviour over the course of the day. Data analysis, performed using Matlab, revealed a correlation between driving behaviour and energy consumption. Additionally, the results showed an increase in the driving behaviour index as the day progressed.
Le crescenti preoccupazioni per le emissioni di CO2 e il riscaldamento globale stanno incentivando l’elettrificazione del settore dei trasporti attraverso l’adozione di veicoli elet- trici (EV). Negli ultimi anni, i significativi progressi nelle tecnologie delle batterie hanno contribuito a una notevole crescita del mercato. Tuttavia, l’autonomia limitata dei veicoli elettrici continua a rappresentare un ostcolo alla diffusione su larga scala. Per affrontare questa problematica, la prima parte di questa tesi è dedicata allo sviluppo di un simula- tore di guida per veicoli elettrici. Il simulatore integra componenti hardware e software per riprodurre in modo realistico il comportamento di un veicolo elettrico in un con- testo di guida reale. I risultati ottenuti indicano che il simulatore è in grado di replicare le dinamiche di guida con un’incertezza accettabile. Nella seconda parte della tesi, il simulatore viene impiegato per analizzare lo stile di guida. È stato condotto uno stu- dio che ha coinvolto dodici partecipanti, equamente divisi per genere, in tre scenari di guida che includono percorsi urbani e autostradali, con e senza traffico. La logica fuzzy è stata utilizzata per valutare gli stili di guida, producendo un indice di comportamento alla guida (Driving Behaviour Index o DBI) per identificare intuitivamente l’aggressività. Ogni partecipante ha ripetuto i test durante tre fasce orarie - mattina, pomeriggio e sera - al fine di valutare le variazioni del comportamento di guida nel corso della giornata. L’analisi dei dati, condotta tramite Matlab, ha evidenziato una correlazione tra lo stile di guida e il consumo di energia. Inoltre, i risultati hanno mostrato un aumento dell’indice di comportamento di guida con il progredire della giornata.
Correlating driving behaviour and energy consumption by developing an EV simulator
CANALI, GIANLUCA;Brucci, Lorenzo
2024/2025
Abstract
Growing concerns about CO2 emissions and global warming are driving the electrifica- tion of the transportation sector through the adoption of electric vehicles (EVs). In recent years, significant advancements in batteries technologies have contributed to no- table market growth. Nevertheless, the limited driving range of EVs continues to pose a challenge to broader adoption. To address this issue, the first part of this thesis focuses on the development of a driving simulator for electric vehicles. The simulator integrates both hardware and software components to realistically replicate the behaviour of an EV within a real-world driving environment. Results indicate that the simulator effectively reproduces driving dynamics with an acceptable degree of uncertainty. In the second part of the thesis, the simulator is employed to analyse driving behaviour. A study was conducted involving twelve participants, evenly divided by gender, across three driving scenarios that included urban and highway routes, both with and without traffic. Fuzzy Logic was used to assess driving styles, outputting a Driving Behaviour index (DBI) to intuitively identify the aggressiveness. Each participant repeated the tests during three different times of day — morning, afternoon, and evening — to investigate variations in driving behaviour over the course of the day. Data analysis, performed using Matlab, revealed a correlation between driving behaviour and energy consumption. Additionally, the results showed an increase in the driving behaviour index as the day progressed.| File | Dimensione | Formato | |
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2025_07_Brucci_Canali_ExecutiveSummary.pdf
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Descrizione: Executive Summary
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2025_07_Brucci_Canali_Tesi.pdf
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Descrizione: Tesi
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https://hdl.handle.net/10589/240641