In this paper an energy optimal control strategy for a highly maneuverable Robotic Electric Vehicle (ROboMObil) is presented. The ROMO is a development of the Robotics and Mechatronics Center (which is part of the German Aerospace Center) to cope with several research topics, like energy efficient, autonomous or remote controlled driving for future (electro-) mobility applications. Since saving electric energy is a primal goal when operating a battery electric vehicle (like the ROMO), we have developed a new approach for energy optimal control of an over-actuated electric car. The focus of the control strategy lies in the model based minimization of the actuator losses and power consumption for driving along a precalculated trajectory to optimize the overall efficiency. The approach is based on a real-time capable nonlinear control allocation (CA) algorithm, using quadratic programming, implemented in the object oriented modeling language Modelica. Two optimization objectives are analyzed and the performance is presented by simulation results. Finally an CA extension to nonlinear dynamic inversion is discussed, which is able to compensate the different time constants of the actuators.