electric vehicle

In the field of electric vehicle usage, an inherent challenge lies in the restricted mileage capacity prior to requiring a recharge, hindering broader acceptance of electric vehicles. To alleviate this concern, enhancing the comprehension of vehicle energy consumption and range plays a pivotal role in easing the anxieties of electric vehicle drivers. Within this context, a novel model-based predictive approach is introduced for estimating electric vehicle energy consumption. This method considers the vehicle's specific parameters, the road network's topology, and actual traffic conditions.

Unlike a car, a modern electric vehicle (EV) can have different configurations of the electrical traction subsystem using one, two or four drive-wheel electric motors. This paper investigates a two-motor front-wheel drive configuration, in which the control of the electromagnetic torques of the motors provides two functions: electric traction and direction control. The latter function performs an electronic differential, which is used in place of the traditional mechanical differential transmission and mechanical steering system.

One of the key problems in the implementation of closed-loop control systems is to measure all states of a dynamic system, especially, when there are severe environmental conditions. Consequently, the use of certain types of sensors is impossible for technical or economic reasons. Also, in electromechanical systems, there are a lot of values that cannot be directly measured by physical sensors. Thus, mathematical algorithms named as observers and estimators are in use to calculate the states of the dynamic system utilizing math model and available set of sensors.