In 2020, the European Commission launched the European Green Deal, aiming to make Europe climate-neutral. Agriculture contributes significantly to CO2 emissions, with machinery producing around 70 million tons annually. To reduce this, researchers are exploring hybrid and fully electric tractors. These offer environmental benefits and can power implements efficiently, improving overall sustainability, which encompasses environmental, economic, and social dimensions. However, adoption is limited by high costs and short autonomy, affecting economic feasibility. The feasibility of electrifying tractors largely depends on their mission profiles, which vary by size and task. A key challenge in designing electric powertrains is the absence of a reference cycle. Agencies like the EPA have explored off-cycle technologies, which assess real-world efficiency improvements. This study introduces an electrification index (EI) to evaluate the sustainability of converting diesel tractors to electric, using real-world data collected over a year from a diverse fleet in Emilia Romagna, Italy. Data were gathered through CANBUS loggers and analyzed with a task classification algorithm considering geolocation and CANBUS signals. Mission profiles were created, and key performance indicators, such as peak power and energy demand, were defined. Each diesel tractor was digitally modeled as an electric counterpart to estimate feasible battery sizes. Mission profile data were then applied to these models to calculate the EI, integrating environmental and economic factors. Results suggest electrification viability is influenced by farm scale, access to charging, battery technology advancements, tractor size and their mission profile.

Varani, M., Mattetti, M., Intrevado, F.P. (2025). Electrifying Agriculture: Evaluating Tractor. Electrification with a Data-Driven Approach. St. Joseph (MI) : American Society of Agricultural and Biological Engineers [10.13031/aim.202501445].

Electrifying Agriculture: Evaluating Tractor. Electrification with a Data-Driven Approach

Varani, Massimiliano
;
Mattetti, Michele;Intrevado, Francesco Pio
2025

Abstract

In 2020, the European Commission launched the European Green Deal, aiming to make Europe climate-neutral. Agriculture contributes significantly to CO2 emissions, with machinery producing around 70 million tons annually. To reduce this, researchers are exploring hybrid and fully electric tractors. These offer environmental benefits and can power implements efficiently, improving overall sustainability, which encompasses environmental, economic, and social dimensions. However, adoption is limited by high costs and short autonomy, affecting economic feasibility. The feasibility of electrifying tractors largely depends on their mission profiles, which vary by size and task. A key challenge in designing electric powertrains is the absence of a reference cycle. Agencies like the EPA have explored off-cycle technologies, which assess real-world efficiency improvements. This study introduces an electrification index (EI) to evaluate the sustainability of converting diesel tractors to electric, using real-world data collected over a year from a diverse fleet in Emilia Romagna, Italy. Data were gathered through CANBUS loggers and analyzed with a task classification algorithm considering geolocation and CANBUS signals. Mission profiles were created, and key performance indicators, such as peak power and energy demand, were defined. Each diesel tractor was digitally modeled as an electric counterpart to estimate feasible battery sizes. Mission profile data were then applied to these models to calculate the EI, integrating environmental and economic factors. Results suggest electrification viability is influenced by farm scale, access to charging, battery technology advancements, tractor size and their mission profile.
2025
American Society of Agricultural and Biological Engineers Annual International Meeting (ASABE 2025)
1539
1548
Varani, M., Mattetti, M., Intrevado, F.P. (2025). Electrifying Agriculture: Evaluating Tractor. Electrification with a Data-Driven Approach. St. Joseph (MI) : American Society of Agricultural and Biological Engineers [10.13031/aim.202501445].
Varani, Massimiliano; Mattetti, Michele; Intrevado, Francesco Pio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1040644
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