The evaluation of electric vehicle electric/electronic-architectures (e/e-architectures) is the main topic of this paper. The electric vehicle is chosen as an example system, as it reflects the typical challenges of modern vehicle e/e-architecture development. The development of modern automotive technology also presents another important trend - vehicle electrification. New electric and electronic devices are developed and required in the automotive industry and control commands are exchanged by electric and electronic ones. The energy storage systems (ESS) properly reflect the above two aspects. The energy storage device also takes care of the peak loads, the high load dynamics, and it utilizes the braking energy in order to increase the efficiency. In this work a Li-ion battery and an ultracapacitor both are considered as energy storage devices. The ESS is designed in an iterative process under a driving cycle where the power flow through the vehicle is under the influence of a certain energy management strategy, which steadily and rapidly divides the power between the units.In this paper, a distributed e/e-architecture with a vehicle control unit is modeling. In the early development phase, there is quite a big degree of freedom in the allocation of function components to ECUs. Multiple objectives, like costs, weight or busload, have to be considered for optimizing the allocation. Moreover, an ant colony optimization (ACO) is introduced supporting a multi-objective optimization of the allocation. The new architecture facilitates the information exchange, minimizes the cost and effort of vehicle harness, and reserves the configurability and expandability.To support the design of e/e-architecture, the platform to simulate and compute electric vehicle dynamics and driving distance is critically important and useful. At last, it presents such a simulator, which consists of core components such as the power driven system and vehicle stability control systems. Moreover, concrete use cases of this simulator are given, which assess electric vehicle performance according to different functional and ESS hardware architectures.