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A rule base covering the entire input domain is required for the conventional Mamdani inference and Takagi-Sugeno-Kang (TSK) inference. Fuzzy interpolation enhances conventional fuzzy rule inference systems by allowing the use of sparse rule bases by which certain inputs are not covered. Given that almost all of the existing fuzzy interpolation approaches were developed to support the Mamdani inference, this paper presents a novel fuzzy interpolation approach that extends the TSK inference. This paper also proposes a data-driven rule base generation method to support the extended TSK inference system. The proposed system enhances the conventional TSK inference in two ways: (1) workable with incomplete or unevenly distributed data sets or incomplete expert knowledge that entails only a sparse rule base and (2) simplifying complex fuzzy inference systems by using more compact rule bases for complex systems without the sacrificing of system performance. The experimentation shows that the proposed system overall outperforms the existing approaches with the utilisation of smaller rule bases.

Abstract-Unlike traditional Internal Combustion Engine Vehicles (ICEVs), the introduction of Electric Vehicles (EVs) is a significant step towards green environment. Public Charging Stations (CSs) are essential for providing charging services for on-the-move EVs (e.g., EVs moving on the road during their journeys). Key technologies herein involve intelligent selection of CSs to coordinate EV drivers' charging plans, and provisioning of cost-efficient and scalable communication infrastructure for information exchange between power grid and EVs. In this article, we propose an efficient and scalable Publish/Subscribe (P/S) communication framework, in line with a coordinated onthe-move EV charging management scheme. The case study under the Helsinki city scenario shows the advantage of proposed CS-selection scheme, in terms of reduced charging waiting time and increased number of charged EVs, as charging performance metrics at EV and CS sides. Besides, the proposed P/S communication framework shows its low communication cost (in terms of signallings involved for charging management), meanwhile with great scalability for supporting increasing EVs' charging demands.

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