Utilization of Smartphone Data for Driving Cycle Synthesis Based on Electric Two-Wheelers in Shanghai

Abstract

Driving cycles play an important role in analysis, design, and optimization of vehicles. The use of smartphones as data acquisition devices leads to easier access to a large test group, but results might be less accurate than with professional test devices. In this work, a systematic comparison of smartphone-based data acquisition and data recorded by a professional device is performed regarding the simplicity of data acquisition and the accuracy of energy estimation. Challenges and opportunities of smartphone-based driving cycle synthesis are described. A frequency analysis presents differences in sampling rates and energy characteristics. It is shown that a sampling rate of 1Hz is sufficient to cover relevant dynamics for low-power electric two-wheelers (E2Ws). The driving behavior of E2Ws in Shanghai is used as a case study and analyzed by means of a data collection campaign. Based on a localized E2W driving cycle in Shanghai, a data collection strategy for improving driving cycles is proposed. In particular, the inclusion of data collection by smartphone and an offline data fusion with IMU data to improve energy predictions are presented. The derived method can help manufacturers to estimate energy consumption and improve the design process of localized driving cycles.