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A comparison of the performance of graphene‐based supercapacitors is difficult, owing to the variety of production methods used to prepare the materials. To the best of our knowledge, there has been no systematic investigation into the effect of the graphene production method on the supercapacitor performance. In this work, we compare graphene produced through several routes. This includes anodic and cathodic electrochemically exfoliated graphene, liquid phase exfoliated graphene, graphene oxide, reduced graphene oxide, and graphene nanoribbons. Graphene oxide exhibited the highest capacitance of approximately 154 F g−1 in 6 M KOH at 0.5 A g−1 attributed to oxygen functional groups giving an additional pseudocapacitance and preventing significant restacking; however, the capacitance retention was poor, owing to the low conductivity. In comparison, the anodic electrochemically exfoliated graphene exhibited a capacitance of approximately 44 F g−1, the highest of the 'pure' graphene materials, which all exhibited superior capacitance retention, owing to their higher conductivity. The cyclability of all of the materials, with the exception of reduced graphene oxide (70 %), was found to be greater than 95 % after 10 000 cycles. These results highlight the importance of matching the graphene production method with a specific application; for example, graphene oxide and anodic electrochemically exfoliated graphene would be best suited for high energy and power applications, respectively. [ABSTRACT FROM AUTHOR]

A system‐level behavioural modelling technique is described for a switched reluctance motor drive. The model enables simple and efficient analysis or simulation of multiple drive systems such as pumps, actuators and engine starters within a more‐electric network, for example, on‐board an aircraft. The behavioural model is based on a power balance analysis. The transfer functions in the model are parameterised from experimental tests on the drive system, resulting in a simple model that only reproduces the average behaviour of the input–output variables necessary for system‐level analysis. No data from the manufacturer is required to develop the model. The technique is discussed and validated using an engine starter in an aircraft test facility. [ABSTRACT FROM AUTHOR]