Summary The design of a battery pack commonly deals with high performance goals and challenging constraints in terms of cost, volume or weight. One of the most crucial variables to maximise is the nominal energy, which depends on the number of discrete battery cells that can be allocated and their individual technical specifications. This work proposes a systematic method to optimise the nominal energy of a constrained battery pack from the perspective of the series‐parallel topology. A mathematical and graphical characterisation is presented on how the main battery's variables are related to a topology bounded to discretisation procedures. It was theoretically found that the effects of rounding the values of the topology may lead to a considerable loss of potential nominal energy, a risk that increases linearly with the number of series. The behaviour of the battery is assessed under nominal conditions and under the event of a cell failure. The theoretical analysis suggests that the detrimental effects due to an open‐circuit increase as the number of series increases, while it is the opposite in the case of a shorted cell. The method is satisfactorily implemented in the development of two different battery packs for solar competition cars with limiting regulations. The candidate topologies outperformed the nominal energy of topologies defined without the method in up to 5%. It was also found that selecting an energy‐maximising topology is not always the most convenient choice, because other variables may be of interest and are dependent on the topology as well. The method is of great use to guide the topology definition process in early theoretical stages, which is usually a compromise between allocating as much cells as possible within constraints, and approaching other performance goals such as a given nominal voltage or capacity. Copyright © 2017 John Wiley & Sons, Ltd.

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Abstract. Precise control of technical system variables in industrial processes and manned and unmanned missions is critical as their results should be achieved plenty. This takes place in Control Rooms (CR) where Operators make decisions based on the large amount of received data. This work proposes a method for weighting variables of a technical system based on their impact on the mission objectives. The relationships between variables and mission functions are defined using a Function to Data Matrix (FDM) in order to allow Operators to determine their criticality. The proposed method was applied for the mission control of the Racing Solar Vehicle Primavera1 which participated in the World Solar Challenge (WSC) 2013 in Australia.

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