HELECAR-D: A dataset for urban electro mobility in Moroccan context

Area of Science:

• Environmental Science
• Transportation Engineering
• Data Science

Background:

• Growing adoption of electric vehicles (EVs) driven by environmental regulations.
• Constraints in emerging economies, like Morocco, hinder EV integration, including infrastructure and regulatory gaps.
• Need for localized data to improve EV energy management systems.

Purpose of the Study:

• To present a novel dataset on electric vehicle (EV) exploitation in Morocco.
• To support the development of improved energy management systems for EVs facing range and charging limitations.
• To facilitate research and development in EV applications within the Moroccan context.

Main Methods:

• Data collection via an onboard electronic card during driving cycles in the Rabat-Salé-Kénitra region.
• Recording key parameters: date, time, Battery State of Charge (SoC), speed, location, weather, traffic, and speed limits.
• Data preprocessing and storage in a Comma Separated Values (CSV) file.

Main Results:

• A comprehensive dataset capturing real-world EV operational data in Morocco.
• The dataset includes diverse factors influencing EV performance and energy consumption.
• Data is structured for accessibility and usability in various EV-related applications.

Conclusions:

• The released dataset is a valuable resource for advancing EV research and development in Morocco.
• It can inform strategies for overcoming adoption barriers and optimizing EV energy management.
• The data supports applications like predictive modeling, charging optimization, and grid integration.