Radio alignment for inductive charging of electric vehicles

Wei Ni, Iain B. Collings, Xin Wang, Ren Ping Liu, Alija Kajan, Mark Hedley, Mehran Abolhasan

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)

Abstract

To maximize power transfer for inductively charging electric vehicles (EVs), charger and battery coils must be aligned. Wireless sensors can be installed to estimate misalignments; however, existing ranging techniques cannot satisfy the precision requirements of the misalignment estimation. We propose a high-precision wireless ranging and misalignment estimation scheme, where high precision is achieved by iteratively measuring, estimating, and aligning the coils. Another key aspect is to convert the nonconvex misalignment estimation to a more tractable problem with a convex objective. We develop a conditional gradient descent method to solve the problem, which performs gradient descent (or conditional gradient descent on the boundary of the search space) and projects out-of-boundary points back into the space. Employing experimentally validated models, we show that our scheme can achieve 92% of the efficiency of perfectly aligned coils in 90% of operations, and tolerate correlated distance measurement errors. In contrast, the prior art is susceptible to correlation, undergoing a significant efficiency degradation of 18.5%.

Original languageEnglish
Article number7035092
Pages (from-to)427-440
Number of pages14
JournalIEEE Transactions on Industrial Informatics
Volume11
Issue number2
DOIs
Publication statusPublished - 27 Apr 2015

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