The electric car is a solution designed as a zero-emission vehicle which is an alternative to reducing air pollution. There are various types of electric cars, this research focuses more on Hybrid Electric Vehicle (HEV). HEV is a vehicle that has at least two different energy sources. The most common combination today is the Internal Combution Engine (ICE) and an electric battery. HEV uses ICE with a smaller capacity than conventional vehicles, this results in more efficient fuel use. In HEV, there are several problems, including the response from ICE which is less than optimal when there is an increase in speed. ICE as the prime mover has a smaller capacity than conventional vehicles because it is assisted by the performance of the DC motor. When ICE is unable to maintain speed, the DC motor will help provide power. Therefore, it is necessary to regulate traction on a DC motor to help ICE achieve the desired speed, especially when there is an increase in speed. This study uses a neuro-fuzzy control method which has the advantage of being able to adapt to changes in parameters in the system. HEV itself requires a fast response, therefore, a predictive controller is used in order to predict the future torque value