Cost and fuel-optimal selection of HEV topologies using Particle Swarm Optimization and Dynamic Programming

@article{Nuesch2012CostAF,
  title={Cost and fuel-optimal selection of HEV topologies using Particle Swarm Optimization and Dynamic Programming},
  author={Tobias Nuesch and Tobias Ott and S{\o}ren Ebbesen and Lino Guzzella},
  journal={2012 American Control Conference (ACC)},
  year={2012},
  pages={1302-1307}
}
In this paper, we apply a methodology to select the cost and fuel-optimal topology of a set of topologies for hybrid electric vehicles (HEVs). For each topology, the optimal component sizes are determined by optimizing a weighted sum of fuel consumption and powertrain costs. Vehicle performance constraints are imposed to ensure a minimum level of drivability. The constrained optimization problem is solved using Particle Swarm Optimization (PSO), and deterministic Dynamic Programming (DP) is… CONTINUE READING

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