Estimation the Residual Capacity of Ni-MH Battery Pack using NARMAX Method for Electric Vehicles

This paper presents a nonlinear autoregressive moving average with exogenous variables (NARMAX) method to estimate the residual capacity of high-capacity Ni/MH battery pack in electric vehicles. The state of charge (SOC) represents the battery residual capacity. The SOC of battery cannot be measured directly and estimated from measurable battery parameters such as current and voltage. The proposed NARMAX produces accurate SOC estimate, using industry standard Federal Urban Driving Schedule (FUDS) aggressive driving cycle test procedures. The results indicate that the NARMAX can provide an accurate and effective estimation of the SOC, resulting in minimal computation load and suitable for real-time embedded system application. The maximum average relative error of the estimating results is 0.02%.

I. Introduction

In response to the ever-increasing concerns on environmental protection and energy conservation, research and development of various technologies for electric vehicles (EVs) are being actively conducted. Among those EV technologies, the battery technology is the key to possible commercialization and popularization of EVs [1]–[5]. As EVs gain popularity, the importance of correct estimation of the current state of charge (SOC) of a battery is increasing. The owner of a gasoline-powered car needs to know how much gasoline is in the tank. In the same way, the owner of an EV needs to know how much energy is in the battery at any time. Unfortunately, SOC cannot be measured directly but must be estimated based on measurable battery parameters such as current and voltage.