Simulation-Optimization Approaches for the Co-Design of Electric Transportation Systems
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About this event
Electric transportation systems are central to reducing emissions from passenger transport and logistics, but their wider deployment is constrained by high upfront costs and the difficulty of maintaining reliable operations in real-world conditions. A fundamental tension underlies these challenges: infrastructure and vehicles must be designed for the operations they will face, yet operational strategies can only be defined once a system is designed. Because these decisions are highly interdependent, treating strategic, tactical, and operational choices sequentially leads to suboptimal outcomes. The natural resolution is co-design: jointly optimizing the system design and operation. This thesis investigates, develops, and validates co-design as a unifying framework for electric transportation systems, combining optimization and simulation to couple infrastructure sizing, vehicle design, and operational control across maritime, road freight, airport ground operations, and passenger-vehicle domains. Across these domains, co-design consistently outperforms separate design-then-operate approaches. Jointly optimizing ferry schedules, charging infrastructure, and battery sizing reduces total system cost relative to current practice. In road freight, centralized co-design of charging station locations and operational policies lowers average cost, reduces total installed charging power, and eliminates queuing. For airport ground support, smarter charging control simultaneously improves service levels and reduces both charger and fleet requirements. In energy support systems, simulation-based co-design of energy management and hybrid storage for charging stations yields more robust long-term designs. At the vehicle level, concurrent family design produces more competitive portfolios, though gains depend strongly on the market segments targeted. In all cases, simulation is key to reveal how operational realism shapes which designs perform well in practice and whether gains in reliability and cost are actually realized, albeit at the cost of higher modeling complexity. The overarching finding is that electric transportation systems become more implementable, cost-effective, and reliable when design, operations, and uncertainty-aware evaluation are treated as a unified problem. Achieving this requires optimization and simulation to be used together under a co-design paradigm to support realistic decision-making and accelerate the deployment of electric transportation systems.
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