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Due to the continuous electrification of vehicles, the variety of different hybrid topologies is expected to increase in the future. As the calibration of real-time capable energy management systems (EMS) is still challenging, a development framework for the EMS that is independent of the hybrid topology would simplify the overall development process of hybrid vehicles. In this paper an analytical methodology, which is used to derive a fuel-optimal, rule-based EMS for parallel hybrids, is transferred to a series topology. It is shown that the fundamental correlations can be applied universally to both parallel and series configurations. This enables the possibility to develop a real-time capable, rule-based controller for a series HEV based on maps that ensures a fuel-optimal operation. These maps provide the optimal power threshold for the activation of the auxiliary power unit and the optimal power output dependent on the driver’s power request.

The overall efficiency of hybrid electric vehicles largely depends on the design and application of its energy management system (EMS). Despite the load coordination when operating the system in a hybrid mode, the EMS accounts for state changes between the different driving modes. Whether a transition between pure electric driving and internal combustion engine (ICE) powered driving is beneficial depends, among others, on the respective operation point, the route ahead as well as on the energetic expense for the engine start itself. The latter results from a complex interaction of the powertrain components and has a tremendous impact on the efficiency and quality of EMSs. Optimization based methods such as dynamic programming serve as benchmark for the design process of rule based control strategies. In case no energetic expenses are assigned to a state change, the resulting EMS suffers from being sub-optimal regarding the fuel consumption.

The efficiency of a Hybrid Electric Vehicle (HEV) strongly depends on its implemented Energy Management Strategy (EMS) that splits the driver’s torque request onto the Internal Combustion Engine (ICE) and Electric Motor (EM). For calibrating these EMS, usually, steady-state efficiency maps of the power converters are used. These charts are mainly derived from measurements under optimal conditions. However, the efficiency of ICEs fluctuates strongly under different conditions. Among others, these fluctuations can be induced by charge air temperature, engine oil temperature or the fuel’s knock resistance. This paper proposes a new approach for predicting the impact of any external influence onto the ICE efficiency. This is done by computing the actual deviation from the optimal reference ignition timing and adjusting the result by actual oil temperature and target air-to-fuel ratio.