In this paper, a parallel HEV hybrid controller is developed in the MATLAB/Simulink environment. Using the driver commands, the battery state of charge and the engine map, a set of efficient rules has been developed to efficiently split the power between the engine and the motor. The steps are: 1) Estimate the instantaneous torque demand. 2) Using the estimated torque, the feedback signals and the engine map, find the best operating point and then split the power and let the engine work as near as possible to this efficient point, that can be done by controlling the motor (or generator). In the case of motor, let its torque supply the rest of the torque needed, while the engine works near its efficient point, or in the case of generator, let its torque supply an additional load to put the engine in an efficient point. 3) Control the motor to supply the transient torque demand, and keep the engine torque constant as long time as possible, this help to reduce fuel consumption. Finally simulations of a conventional and hybrid vehicle are performed using Simulink environment to check the controller and series of results will prove the effectiveness of the proposed controller and will show the advantage of hybrid powertrain over conventional one in term of fuel economy.

Almost all HEV battery control strategies keep the battery state of charge (SOC) within a lower limit (SOCmin) (these strategies also called charge sustaining strategies). The goal from sustaining the SOC in this way is to prolong the battery life. But the question is; what is the optimal value of (SOCmin) for a battery, to achieve best fuel economy and longer battery life at the same time?; knowing that when (SOCmin) is too low (around SOCmin=0.2) we get good fuel economy per one speed cycle but the battery dies soon and cannot perform a lot of cycles, but when (SOCmin) is high (around SOCmin=0.8) the battery can survive for a larger number of speed cycle but with poor fuel economy per cycle. The objective of this paper is to propose a method to investigate and solve this problem by simulation using Simulink environment; we used the manufacture’s data of a Ni-MH battery, empiric equations, and appropriate control strategy to find the optimal value of (SOCmin). The study shows that, for best fuel economy per one cycle; the (SOCmin) value must be as small as possible, for longer battery life; the (SOCmin) value is about (SOCmin=0.85) and for the optimal case (which is the total improvement brought by the battery from first time use until its end of life); the optimal (SOCmin) value is about (SOCmin=0.7).