activity
20202026
most citedA Time-invariant Network Flow Model for Two-person Ride-pooling Mobility-on-Demand

3 citations · 10 across the 12 of their papers we have counts for

collaborators

13 papers

cs.AI2026

Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation

Niels Potters, Theo Hofman

This paper presents a black-box evaluation framework to systematically assess the ability of Large Language Models (LLMs) to generate Design Structure Matrices (DSMs) from structur…

eess.SY2023★ 1 cited

Effective Scaling of High-Fidelity Electric Motor Models for Electric Powertrain Design Optimization

Olaf Borsboom, Martijn Lokker, Mauro Salazar +1

In general, electric motor design procedures for automotive applications go through expensive trial-and-error processes or use simplified models that linearly stretch the efficienc…

eess.SY2023★ 1 cited

A Two-dimensional Spatial Optimization Framework for Vehicle Powertrain Systems

Jorn van Kampen, Mauro Salazar, Theo Hofman

This paper presents a modeling framework to optimize the two-dimensional placement of powertrain elements inside the vehicle, explicitly accounting for the rotation, relative place…

eess.SY2023

Cost-optimal Fleet Management Strategies for Solar-electric Autonomous Mobility-on-Demand Systems

Fabio Paparella, Theo Hofman, Mauro Salazar

This paper studies mobility systems that incorporate a substantial solar energy component, generated not only on the ground, but also through solar roofs installed on vehicles, dir…

math.OC2023★ 3 cited

A Time-invariant Network Flow Model for Two-person Ride-pooling Mobility-on-Demand

Fabio Paparella, Leonardo Pedroso, Theo Hofman +1

This paper presents a time-invariant network flow model capturing two-person ride-pooling that can be integrated within design and planning frameworks for Mobility-on-Demand system…

math.OC2023★ 2 cited

Optimal Endurance Race Strategies for a Fully Electric Race Car under Thermal Constraints

Jorn van Kampen, Thomas Herrmann, Theo Hofman +1

This paper presents a bi-level optimization framework to compute the maximum-distance race strategies for a fully electric endurance race car, whilst accounting for the low-level v…

eess.SY2022

Electric Autonomous Mobility-on-Demand: Joint Optimization of Routing and Charging Infrastructure Siting

Fabio Paparella, Karni Chauhan, Theo Hofman +1

The advent of vehicle autonomy, connectivity and electric powertrains is expected to enable the deployment of Autonomous Mobility-on-Demand systems. Crucially, the routing and char…

eess.SY2022★ 1 cited

Control and Design Optimization of an Electric Vehicle Transmission Using Analytical Modeling Methods

Olaf Borsboom, Thijs de Mooy, Mauro Salazar +1

This paper introduces a framework to systematically optimize the control and design of an electric vehicle transmission, connecting powertrain sizing studies to detailed gearbox de…

eess.SY2022

Electric Motor Design Optimization: A Convex Surrogate Modeling Approach

Olaf Borsboom, Mauro Salazar, Theo Hofman

This paper instantiates a convex electric powertrain design optimization framework, bridging the gap between high-level powertrain sizing and low-level components design. We focus…

eess.SY2021★ 2 cited

Energy-optimal Design and Control of Electric Powertrains under Motor Thermal Constraints

Mouleeswar Konda, Theo Hofman, Mauro Salazar

This paper presents a modeling and optimization framework to minimize the energy consumption of a fully electric powertrain by optimizing its design and control strategies whilst e…

eess.SY2021

Optimal Design of Electric Micromobility Vehicles

Olaf Korzilius, Olaf Borsboom, Theo Hofman +1

This paper presents a modeling and optimization framework to design battery electric micromobility vehicles, minimizing their total cost of ownership (TCO). Specifically, we first…

eess.SY2020

Transmission Ratio Design for Electric Vehicles via Analytical Modeling and Optimization

Theo Hofman, Mauro Salazar

In this paper we present an effective analytical modeling approach for the design of the transmission of electric vehicles. Specifically, we first devise an analytical loss model f…

eess.SY2020

Time-optimal Control Strategies for Electric Race Cars with Different Transmission Technologies

Olaf Borsboom, Chyannie A. Fahdzyana, Mauro Salazar +1

This paper presents models and optimization methods to rapidly compute the achievable lap time of a race car equipped with a battery electric powertrain. Specifically, we first der…