The development of modern vehicles and electrified drivetrains in particular is characterised by high complexity and a wide diversity of variants coupled with increasing customer expectations. Legal requirements as well as specifications and customer requirements on the vehicle are most important for an optimised transmission layout complying with the constraints mentioned above. The optimisation of individual components usually does not result in an optimum vehicle concept - the holistic view of the vehicle system requires a "cross-component" approach. In this regard, the so-called EVID method (Electric Vehicle Identification) is used in order to determine the optimum drivetrain configuration for selected types of vehicles that are used for different purposes (e.g. city vehicle or delivery vehicles used in the city and for long-distance transport). Objective parameters are used to identify the optimum vehicle for the variation of different basic parameters (e.g. number of speeds, transmission spacing, system performance, rotational speed and torque of electric motors and battery capacity) which differ in their variation range. The objective parameters include mileage, energy consumption and cost, each of them with a different weighting in the so called evaluation matrix. The values of the objective parameters are generated for different drivetrain configurations based on an automated algorithm derived from calculation models (e.g. for cost, vehicle weight, maximum speed) and the simulation for determining the energy balance. In order to reduce the computation time required for the evaluation, mathematical models (MM) are used: a mathematical function approximates complex physical models. In accordance with EVID, the mathematical models are meant to depict the correlation between basic and objective parameters as precisely as possible. The first part of the presentation describes the methodological approach, the second part presents the optimum drivetrain configuration. Furthermore, results from the sensitivity analysis about the influence of individual basic parameters on the optimum drivetrain concept and on the objective parameters of the evaluation will be presented. The development of electrified drivetrains is characterised by high complexity and a large number of variants. Different requirements like requirement specifications, customer and legal requirements play a key role for an optimal design of the drivetrains. Based on defined evaluation parameters, the EVID method allows the determination of an optimal design of an electric drivetrain for a vehicle concept and its respective application area. The definition of the electric vehicles with regard to the application profiles, possible topology and component combinations in addition to the identification of the minimum requirements is used as the basis for an evaluation matrix. A driver and driving environs model, which takes the representative driving cycles developed by using the 3D method into account, and a modular drivetrain model are used to determine the objective parameters. In addition to the basic parameters with varying values, a mathematical model is developed based on these parameters, which allows the identification of the optimal drivetrain configuration. Apart from the identification of the optimal topology and its components, a sensitivity analysis of the optimal concept with varying basic parameters is used to analyse the influence of the components characteristics on the overall concept and to guarantee a substantial analysis of the optimal drivetrain configuration. With regard to the application of the results, the EVID method offers potential for the advancement of available components in the short term due to the understanding of their influence on the overall drivetrain. In the medium term, the development of drivetrain and peripheral components can be matched to the identified requirements. The application-oriented method can increase profits and efficiency due to the investments in concepts and components that lead to the desired results.