A real time energy management (EMS) optimizing algorithm is introduced that performs similar to offline dynamic programming (DP) for parallel HEVs. The EMS and the DP are compared, especially with the addition of a local hill climbing technique, to the example performance prediction of the fuel consumption of a 1.67 tonne large car using a 50 kW Honda Insight engine (representing 65% power reduction from standard) as reference. Then the performance of the vehicle in HEV mode, with a parallel 30 kW motor/generator is examined. The average improvement of this vehicle over five drive cycles from around the world is about 50% reduction in fuel consumption. Next the engine is replaced with an advanced SI turbocharged engine with assisted ignition which returns the performance to that expected of this class of car i.e. 0-100 km/h acceleration time of 7 s. This results in a 14% average reduction in fuel consumption across the five cycles compared with the base Honda engine. Then in optimized hybrid configuration, the advanced engine powertrain demonstrates that not only is a smaller motor/generator and associated energy control and storage needed but the average fuel consumption across the five cycles is reduced by 59% below the original. Finally an ultimate engine is examined; for the Euro NEDC the HEV fuel consumption is 3.23 L/100km or 75 gCO2/km, well under the Euro 2020 target of 90 g/100km, whilst maintaining an acceptable 8.3s 0-100km/h acceleration capability.