Search Results

There is an increasing customer demand for adjustable chassis control features which enable adaption of the vehicle comfort and driving characteristics to the customer requirements. One of the most promising vehicle control systems which can be used to change the vehicle characteristics during the drive is the semi-active suspension system. This paper presents a Rule-Optimized Fuzzy Logic controller for semi-active suspension systems which can continuously adjust itself not only according to the road conditions but also to the driver requirements. The proposed controller offers three different control modes (Comfort, Normal and Sport) which can be switched by the driver during driving. The Comfort Mode minimizes the accelerations imposed on the driver and passengers by using a softer damping. On the other hand, the increased damping in Sport Mode provides better road holding capability, which is critical for sporty handling.

This paper presents a performance analysis study for the Rule-Optimized controller of a semi-active suspension system. The Rule-Optimized controller is based on a Fuzzy Logic control scheme which offers new opportunities in the improvement of vehicle ride performance. An eleven degree of freedom full vehicle ride dynamics model is developed and validated through laboratory tests performed on a hydraulic four-poster shaker. An optimization process is applied to obtain the optimum Fuzzy Logic membership functions and the optimum rule-base of the semi-active suspension controller. The global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle is determined through discrete optimization with Genetic Algorithm (GA).

This paper deals with the relationship between powertrain design and the requirements resulting from connected and automated driving. The questions addressed are how much powertrain design will change in regard to automated and connected driving and which powertrain in an automated vehicle will prove to be the optimum solution. To this end, a concept study is being conducted for a D-segment vehicle and multiple powertrain topologies ranging from non-electrified, mild-hybrids to plug-in hybrids and battery electric vehicles. The development processes required to address this issue is presented accordingly, as well as the necessary methods for systemic drive optimization, taking into account all requirements of the vehicle, the drive system and the components and their interactions with each other. The requirements resulting from connected and automated driving as well as their influences on vehicle and drive concepts are elaborated.

The optimization and further development of automated driving functions offers great potential to relieve the driver in various driving situations and increase road safety. Simulative testing in particular is an indispensable tool in this process, allowing conclusions to be drawn about the design of automated driving functions at a very early stage of development. In this context, the use of driving simulators provides support so that the driving functions of tomorrow can be experienced in a very safe and reproducible environment. The focus of the acceptance and optimization of automated driving functions is particularly on vehicle lateral control functions. As part of this paper, a test person study was carried out regarding manual vehicle lateral control on the dynamic vehicle road simulator at the Institute of Automotive Engineering.

In the context of urban smart mobility, vehicles have to communicate with each other, surrounding infrastructure, and other traffic participants. By using Vehicle2X communication, it is possible to exchange the vehicles’ position, driving dynamics data, or driving intention. This concept yields the use for cooperative driving in urban environments. Based on current V2X-communication standards, a methodology for cooperative driving of automated vehicles in mixed traffic scenarios is presented. Initially, all communication participants communicate their dynamic data and planned trajectory, based on which a prioritization is calculated. Therefore, a decentralized cooperation algorithm is introduced. The approach is that every traffic scenario is translatable to a directed graph, based in which a solution for the cooperation problem is computed via an optimization algorithm.

Electrified drives will change significantly in the wake of the further introduction of automated driving functions. Precise drive dimensioning, taking automated driving into account, opens up further potential in terms of drive operation and efficiency as well as optimal component design. Central element for unlocking the dimensioning potentials is the knowledge about the driving functions and their application. In this paper the implications of automated driving on the drive and component design are discussed. A process and a virtual toolchain for electric drive development from concept optimization to detailed component dimensioning is presented. The process is subdivided into a concept optimization part for finding the optimal drive topology and layout and a detailed prototype dimensioning process, where the final detailed drive dimensioning is carried out.