The increase in temperature of atmosphere is mostly attributed to human activity due to the combustion products of excessively used fossil fuels. These products create greenhouse effect whereby the planet’s surface temperature increases. Use of renewable and clean energy sources is the best solution to reduce increase rate of warming, to mitigate the results of climate change and not to go beyond the irreversible point for the sustainability of life on the planet. The second major source of green house gases comes after electricity generation is transportation sector due to increasing traveling demand as well as its fastest growing rate. There are stringent emission limits stipulated by governors. The proposed emission limits for near future can no longer be satisfied by Internal Combustion Engines (ICE) despite the good advancements in engine technologies. There are numerous studies to adapt clean energy sources on road vehicles. Hydrogen and pure electric energy is seen as an excellent solution for zero emission vehicles. But there are some obstacles for both power sources. The use of hydrogen as common fuel in internal combustion is seen to be unfeasible in immediate future, due to storage, production and availability problems. Hydrogen is not an energy source but it is an energy carrier. Besides this its well-to-wheel efficiency is low with respect to fossil fuels. As to batteries, their poor energy density and long charging time hampers the use of batteries as main power source in on road vehicles. The best solution is to use less or carbon intensive fuels or increasing average efficiency of ICE by using secondary power source in the vehicle. Hybrid vehicles which combine at least two power sources are temporary solution on the way of zero emission vehicles. Hybridization provides means of fuel consumption and emission reduction. Using secondary power source allows down-sizing the engine. Smaller engines operate more efficiently than bigger ones since internal combustion engines are designed to operate efficiently at high loads. Recuperation of the thrown energy and engine stop option are another advantages of hybrid vehicles in fuel economy. Power distribution strategy between energy sources and wheels is of great importance to exploit hybrid vehicles’ features and this may give satisfactory results even in the situations where engine down-sizing and idle stop cannot be implemented. Power management is a complicated global optimum problem since it involves too many objectives such as fuel consumption and emission reductions as well as drive-ability and acceleration performance of hybrid vehicle. Dynamic Programming (DP) technique generally is used to solve global optimum problems with nonlinear constraints. Due to the computational burden and uncertainty in driver’s power demand, dynamic programming technique cannot be handled real-time with available computation technologies. Optimum power split strategy is determined off-line for a given drive cycle and control rules are extracted at the end of DP solution. There are alternative techniques developed that give sub-optimal solutions approaching global optimum results and can be implemented real-time. These methods are based on finding optimum power split ratio in a time interval by applying predictive control or finding instantaneous optimum power split by using equivalent fuel consumption methods. The vehicle speed profile in shorter time intervals is estimated and DP solution is computed for optimum power split in model predictive control methods. Equivalent fuel quantity of battery energy is converted by using mean efficiencies for a defined cycle and then best power split ratio is chosen. Modeling and rule based control methodology of a converted vehicle is explained in this study. The Ford Transit light commercial vehicle is converted to a hybrid electric vehicle. Since it has front and rear wheel drive versions are available in the market, mounting an electric motor to rear axle of front wheel drive version resulted in a parallel hybrid electric vehicle. The construction of longitudinal hybrid electric vehicle models is given. The use of these models to develop rule based control and simulation results are given.