Improvement of the in-cycle speed fluctuation and system efficiency of an auxiliary power unit

Well reported problems around air quality and climate change, together with the energy crisis resulting from finite fossil fuel resources is motivating all the automotive manufacturers to develop new propulsion systems through electrification and hybridisation. The range extended electric vehicle (REEV) is one of these solutions that seeks a practical compromise between the on-board battery size and the one-charge driving range. The auxiliary power unit (APU) is the key component in a REEV and is designed to maintain the battery charge for long distance trips. Since the APU does not propel the vehicle, it only requires a small capacity engine with low-cylinder-count. This type of engine exhibits severe speed fluctuations due to its low firing frequency. As the engine and the M/G are isolated from the vehicle driving wheels, it is possible to use the electric machine to deliver a counteracting torque to the engine reducing the resultant torque spikes and thus the system speed oscillation but likely to increase the electric losses. This research work aims to minimise the speed fluctuation balanced against the extra losses introduced. A Dynamic Torque Control (DTC) strategy was designed and tested on an APU using a novel approach to achieve this target. The system components were modelled individually regarding to the prototype system specifications, which is developed within a collaborative R&D project. The empirical engine model was calibrated with extensive bench testing data to recreate the in-cycle torque waveforms. The motor/generator was modelled as a novel hybrid between an analytical model and an FEA model which allowed the winding inductance variation due to the current rise to be included in the model. This approach was designed to replicate the electric machine performance with high fidelity whilst keeping the computational time and cost low. With the help from the system model, the DTC torque demand patterns were designed based on detailed analysis of the contribution factors of the speed fluctuation and the electric machine losses. A unique Pareto Curve of the speed fluctuation reduction and the electrical loss was identified during the analysis and allowed the optimal demand pattern to be developed for a given torque capability electric machine. The simulation results showed that the system in-cycle speed fluctuations could be reduced by 16.4% and 19.11% at 2000rpm full load and 4500rpm full load condition respectively while the electric specific fuel consumption (ESFC) rose by 2.26% and 1.35% at the same operation points. The DTC strategy was implemented in the prototype APU and successfully tested on the rig at 2000rpm and 4500rpm. A reduction in the speed oscillation and the ESFC increase consistent with the simulation results were observed. The simulation estimates on ESFC was proved within an error of 2.19%. This research improves the insight into the mechanisms that are responsible for increased losses when dynamic torque control is used and develops an optimisation approach which takes account of these factors. When an electric machine, which does not have the same instantaneous peak torque capability as the engine, is used in an APU, a better compromise between speed fluctuation smoothing and system efficiency can be achieved.