Battery-powered wheelchairs require accurate and reliable range prediction to offer the maximum visibility of the current battery state to users, and to help them schedule future trip plans as well as fulfill the maximum battery economy potential. It is also one of the most critical parameters of wheelchairs to ensure the safety of users. However, range prediction is a very complicated issue by the fact that batteries are subject to current profiles, external influences, history of battery use, and aging. The prediction is even more challenging with unknown future driving conditions. The aim of this paper is to use a preview of a 3-D map, geographic information systems, and global positioning systems to develop an accurate range estimation system for battery-powered wheelchairs. This allows range prediction based on previewed driving road conditions. The nonlinearity of Li-ion batteries is also taken into consideration by using a circuit based battery model. Altogether, this methodology offers robustness and accuracy under varying operating conditions. Simulation results are presented to validate the proposed estimation method.

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