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The optimum design of an electrical distribution system (EDS) is based on the profound understanding and measurement of its thermal behavior, because this determines wire diameter and insulation material, has a major impact on the fusing strategy, and enables minimizing technical risk. Current methods of calculation require an extensive database, whereas the temperature measurements at selected points with normal sensors allow neither the precise rating of the actual insulation temperature within a wire bundle, nor the determination of the thermal impact of load currents. The presented approach is based on both a new measurement method and on a related evaluation algorithm. A common automotive wire is applied as a sensing device using its resistance temperature coefficient as the measurement principle.

The increasing power and safety requirements of electrical systems present a challenge for future automotive electrical networks. However, the modeling of use-profiles and the overall power consumption of electrical systems proves to be difficult as the number of potential on/off combinations of the loads is tremendous. Furthermore, the operation of some loads is correlated or depends upon the operating conditions. Thus, simple worst-case calculations applied to this complexity often lead to an over-specification of components. The proposed approach is based on the probabilities of loads being in the on-state and their respective interdependencies with each other and with boundary conditions such as time of day. Applying basic statistics and a new iterative algorithm, it allows the calculation of the probability of consumed total power for a given set of boundary conditions and of, very importantly, its expected continuous period.

One of the challenges faced when using Li-ion batteries in electric vehicles is to keep the cell temperatures below a given threshold. Mathematical modeling would indeed be an efficient tool to test virtually this requirement and accelerate the battery product lifecycle. Moreover, temperature predicting models could potentially be used on-board to decrease the limitations associated with sensor based temperature feedbacks. Accordingly, we present a complete modeling procedure which was used to calculate the cell temperatures during a given electric vehicle trip. The procedure includes a simple vehicle dynamics model, an equivalent circuit battery model, and a 3D finite element thermal model. Model parameters were identified from measurements taken during constant current and pulse current discharge tests. The cell temperatures corresponding to an actual electric vehicle trip were calculated and compared with measured values.

Within the scope of the development of autonomous vehicles, the mandatory reliability requirements of the electrical power supply, and consequently of the electrical distribution system (EDS), are increased considerably. In addition, the overall rising number of electrical functions leads to significantly higher electrical power demands, while strict cost, weight and packaging constraints must be upheld. Current developments focus on adding redundancies, enhancing physical robustness, or dimensioning critical components. New approaches address predictive power management, better diagnostic capabilities, and, the subject of this paper, alternative topologies and architectures [1]. These are derivations of the conventional tree structure, as well as ring- or linear-bus-based zonal architectures, which feature in part distributed storage devices or semiconductor switches that rearrange the power paths in case of a fault [2,3].

Noise, vibration and harshness (NVH) is one of the most important performance evaluation aspect of electric motors. Among the different causes of the NVH issues of electrical drives, the high-frequency spatial and temporal harmonics of the electrical drive system is of great importance. To reduce the tonal noise of the electric motors, harmonic injection methods can be applied. However, a lot of the existing related work focuses more on improving the optimization process of the parameter settings of the injected current/flux/voltage, which are usually limited to some specific working conditions. The applicability and effectivity of the algorithm to the whole frequency/speed range are not investigated. In this paper, a multi-domain pipeline of harmonic injection controller design for a permanent magnet synchronous motor (PMSM) is proposed.

Currently, circuit breakers and, in most cases, thermal fuses are used for wire protection due to their low cost and robust design. As an alternative, solid state switches are being considered within future electrical distribution systems (EDS) for several reasons, e.g. resetability, diagnosis, smaller tolerances, and reduced dependencies on ambient temperature or arcing. Particularely if combined with benefits on the system level, such an application can be advantageous. The new approach presented in this paper uses a thermal model of the wire instead of only an emulation of the thermal fuse behavior. This allows, based on the electrical current profile, the calculation of the wire temperature and thus a robust and precise protection of the wire. In addition, it minimizes the probability of faulty switching, which is of particular importance with regard to safety-critical electrical functions.

The topology of an EDS, defined by the routing paths and by the location of the distribution boxes and the inline connectors, has a strong impact on weight and required amount of material, especially of copper, as well as on the manufacturing- and assembly time. Although a good part of the routing and packaging is fixed due to technical reasons and carry-over situations, in general there are enough optional paths and locations to allow up to several thousand alternative topologies. For these reasons, an optimization is possible as well as important. For such an optimization, in this paper a method is presented to concurrently minimize predefined criteria, e.g. the required copper, length of the wires, and the overall length of the wire bundles. It is based on designated algorithms for the variation of the topology, the routing, and the calculation of the optimization criteria as mentioned above.