arXiv subjects

Juan Pablo Bertucci

Publications and source records attributed to Juan Pablo Bertucci.

4 recordsLinked to original sources

arXiv2026

Battery Electric Truck Infrastructure Co-design via Joint Optimization and Agent-based Simulation

As zero-emission zones emerge in European cities, fleet operators are shifting to electric vehicles. To maintain their current operations, a clear understanding of the charging infrastructure required and its relationship to existing power grid limitations is needed. This study presents an optimization frame-work for jointly designing charging infrastructure and schedules within a logistics distribution network, validated through agent-based simulations. We formulate the problem as a mixed-integer linear program and develop an agent-based model to evaluate various designs and operations under stochastic conditions. Our experiments compare rule-based and optimized strategies in a case study of the Netherlands. Results show that current commercial solutions suffice for middle-mile logistics, with central co-design yielding average cost reductions of 5.2% to 6.4% and an average 20.1% decrease in total installed power. While rule-based control effectively manages charging operations and mitigates delays, optimizing charge scheduling significantly reduces queuing times (99%), charging costs (13.5%), and time spent near capacity (10.9%). Our optimization-simulation framework paves the way for combining optimized infrastructure planning and realistic fleet operations in digital-twin environments.

eess.SY↗

arXiv2026

Simultaneous Optimization of Electric Ferry Operations and Charging Infrastructure

Electrification of marine transport is a promising solution to reduce sector greenhouse gas emissions and operational costs. However, the large upfront cost of electric vessels and the required charging infrastructure can be a barrier to the development of this technology. Optimization algorithms that jointly design the charging infrastructure and the operation of electric vessels can help to reduce these costs and make these projects viable. In this paper, we present a mixed-integer linear programming optimization framework that jointly schedules ferry operations, charging infrastructure and ship battery size. We analyze our algorithms with the case of the China Zorrilla, the largest electric ferry in the world, which will operate between Buenos Aires and Colonia del Sacramento in 2025. We find that the joint system and operations design can reduce the total costs by 7.8\% compared to a scenario with fixed power limits and no port energy management system.

eess.SY↗

arXiv2025

Optimal Co-Design of a Hybrid Energy Storage System for Truck Charging

The major challenges to battery electric truck adoption are their high cost and grid congestion.In this context, stationary energy storage systems can help mitigate both issues. Since their design and operation are strongly coupled, to make the best out of them, they should be jointly optimized. This paper presents a co-design framework for hybrid energy storage systems where their technology and sizing are optimized jointly with their operational strategies. Specifically, we consider a microgrid supporting truck chargers that consists of utility grid, solar panels, and energy storage systems including batteries, supercapacitors and flywheels. We frame the co-design problem as a mixed-integer linear program that can be solved with global optimality guarantees. We showcase our framework in a case-study of a distribution center in the Netherlands. Our results show that although the battery-only configuration is already competitive, adding supercapacitors or flywheel storage decrease total cost and increase energy sold back to the grid. Overall, the fully hybrid solution (Battery+Supercapacitors+Flywheel) offers the best outcomes, achieving the lowest overall cost (1.96\% lower compared to battery-only) and reduced grid dependency, but at a higher (2.6\%) initial investment.

eess.SY↗

arXiv2023

Joint Optimization of Charging Infrastructure Placement and Operational Schedules for a Fleet of Battery Electric Trucks

This paper examines the challenges and requirements for transitioning logistic distribution networks to electric fleets. To maintain their current operations, fleet operators need a clear understanding of the charging infrastructure required and its relationship to existing power grid limitations and fleet schedules. In this context, this paper presents a modeling framework to optimize the charging infrastructure and charging schedules for a logistic distribution network in a joint fashion. Specifically, we cast the joint infrastructure design and operational scheduling problem as a mixed-integer linear program that can be solved with off-the-shelf optimization algorithms providing global optimality guarantees. For a case study in the Netherlands, we assess the impact of different parameters in our optimization problem, specifically, the allowed deviation from existing operations with conventional diesel trucks and the cost factor for daily peak energy usage. We examine the effects on infrastructure design and power requirements, comparing our co-design algorithm with planned infrastructure solutions. The results indicate that current charging and electric machine technologies for trucks can perform the itineraries of conventional trucks for our case study, but to maintain critical time requirements and navigate grid congestion co-design can have a significant impact in reducing total cost of ownership (average 3.51% decrease in total costs compared to rule-based design solutions).

eess.SY↗