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In this paper a rule-based energy management for parallel hybrid electric vehicles (HEVs) is presented, which is based on the principles describing the optimal control behavior. Therefore we first show the general relations that can be used to describe the optimal limit of electric driving as well as the optimal torque split among the two propulsion systems. Subsequently these relations are employed to derive maps, which represent the optimal behavior depending on several input parameters. These maps are then used as inputs for the rules in the proposed energy management. This not only makes it possible to automatically calibrate the rule-based controller but also gives the optimal control in every driving situation. Given it is not fuel-efficient to turn the internal combustion engine (ICE) on or off for short intervals, it is further shown how this approach allows to adjust the established limit for electric driving by additional rules.

In this paper, a serial/parallel hybrid electric vehicle with a 17 kWh battery and 400 V voltage level is simulated. The vehicle is a C-segment vehicle, which has optimized driving resistances. It also has an external recharge possibility, which enables fully electric driving. The vehicle uses an Otto-engine concept as well as two electric motors. One motor is a permanent magnet synchronous motor and can be used as traction motor or generator, the other one is an induction motor used as main traction motor for the vehicle. The vehicle uses a 2-speed gearbox, where the electric motors are mounted in P2-configuration. To reach optimal results for the fuel consumption, an operating strategy based on the Equivalent Consumption Minimization Strategy (ECMS) is introduced and implemented in the vehicle simulation.

Electric cars are getting popular more and more and the expectations of the customers are very challenging. Concerning comfort, the situation is clear: customers want an electric car to be quiet and without any annoying noise from the powertrain. To develop an electric powertrain with a minimum noise level and minimized whining it is necessary to have an accurate CAE-simulation and precise criteria to assess whining noise. Based on the experience with electric powertrains in research cars the CAE-modelling was improved and a new ‘whining intensity factor’ was acquired for the development of Daimler's electric cars. The results are a very low noise level and a minimized whining noise, nearly not noticeable giving a comfortable sound to the customers of the smart electric drive and the B-Class Electric Drive.