This work presents the instrumentation, modeling, and parameterization of an electric vehicle used for public transport. The aim is to characterize the mathematical model for its application in control systems design. A system identification technique based on a gray box approach is used to estimate specific parameters of the longitudinal model that cannot be measured directly. For this purpose, a data acquisition system was designed using high-amperage current sensors and an Odroid XU4 embedded system that records the vehicle’s input current, displacement, and velocity. Additionally, a semi-automatic acceleration system was developed to introduce a pseudo-random binary-type acceleration signal to excite all possible vehicle frequencies to perform the parameter identification.
