The gradual decline in global oil reserves and presence of ever so stringent emissions rules around the world, have created an urgent need for the production of automobiles with improved fuel economy. HEVs (hybrid electric vehicles) have proved a viable option to guarantying improved fuel economy and reduced emissions.The fuel consumption benefits which can be realised when utilising HEV architecture are dependent on how much braking energy is regenerated, and how well the regenerated energy is utilized. The challenge in developing an HEV control strategy lies in the satisfaction of often conflicting control constraints involving fuel consumption, emissions and driveability without over-depleting the battery state of charge at the end of the defined driving cycle. To this effect, a number of power management strategies have been proposed in literature. This paper presents a comprehensive review of theseliteratures, focusing primarily on contributions in the aspect of parallel hybrid electric vehicle modelling and control. As part of this treatise, exploitable research gaps are also identified. This paper prides itself as a comprehensive reference for researchers in the field of hybrid electric vehicle development, control and optimization.

Hybrid electric vehicles (HEVs) offer the potential for fuel consumption improvements when compared to conventional vehicle powertrains. The fuel consumption benefits which can be realised when utilising HEV architecture are dependent on how much braking energy is regenerated, and how well the regenerated energy is utilized.

Improved fuel efficiency in hybrid electric vehicles, requires a fine balance between internal combustion engine usage and battery energy, using a carefully designed energy management control algorithm.

Fuel efficiency in hybrid electric vehicles requires a fine balance between combustion engine usage and battery energy, using a carefully designed control algorithm. Owing to the transient nature of HEV dynamics, driving conditions prediction, have unavoidably become a vital part of HEV energy management. The use of vehicle onboard telematics for driving conditions prediction have been widely researched and documented in literature, with