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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 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.

In the future, conventional powertrains will increasingly be supplied by sustainable energy sources. Long-haul freight transport requires efficient energy storage and the ability to refuel quickly. For this reason, hydrogen-powered PEM fuel cells are being discussed as a future energy source for long-distance vehicles. However, there are numerous challenges in packaging, system cooling and service life. Above all, the dissipation of the fuel cell’s heat losses places high demands on the design of the cooling system due to the relatively low operating temperature. In the presented study, a complete generic drive train of a long-distance commercial vehicle was set up within a suitable simulation environment to investigate the required sizes of the fuel cell stack, the HV battery, the hydrogen tanks, and the cooling circuit.

In this paper, the multi-physical simulation workflow from electromagnetics to structural dynamics for a squirrel-cage induction machine is explored. In electromagnetic simulations, local forces and rotor torque are calculated for specific speed-torque operation points. In order to consider non-linearities and interaction with control system as well as transmission, time-domain simulations are carried out. For induction machines, the computational effort with full transient numerical methods like finite element analysis (FEA) is very high. A novel reduced order electro-mechanical model is presented. It still accounts for vibro-acoustically relevant harmonics due to pulse-width modulation (PWM), slotting, distributed winding and saturation effects, but is substantially faster (minutes to hours instead of days to weeks per operation point).