Matching and Control Optimization of Variable Geometry Turbochargers with Hydrogen FCEVs

Turbocharging of hydrogen fuel cell electric vehicles (FCEVs) has recently become a prominent research area, aiming to improve FCEV efficiency and viability to help decarbonise the transport sector. This work compares the performance of electrically assisted variable-geometry-turbocharging (VGT) with a fixed-geometry turbocharger (FGT) by optimising both the sizing of the components and their operating points, ensuring both designs are compared at their respective peak performance. A MATLAB-Simulink reduced-order model is used first to identify the most efficient components which match to the fuel cell air-path requirements. Maps representing the compressor and turbines are then evaluated in a 1D flow model to optimise cathode pressure and stoichiometry operating targets for net system efficiency, using an accelerated genetic algorithm (A-GA). Good agreement was observed between the two models’ trends, with negligible difference in system efficiency and modelled shaft speed under optimised conditions. However, a sensitivity study demonstrates significantly higher efficiency when operating at non-ideal flows and pressures for the VGT when compared to the FGT, suggesting that VGTs may provide higher level of tolerance under variable environmental conditions such as ambient temperature, humidity, and transient loading. Overall, it is concluded that the efficiency benefits of VGT are marginal, and therefore not necessarily significant enough to justify the additional cost and complexity that they introduce.