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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.

The knowledge of representative load collectives and duty cycles is crucial for designing and dimensioning vehicles and their components. For human driven vehicles, various methods are known for deriving these load spectra directly or indirectly from fleet measurement data of the customer vehicle operation. Due to the lack of market penetration of highly automated and autonomous vehicles, there is no sufficient fleet data available to utilize these methods. As a result of increased demand for ride comfort compared to human driven vehicles, autonomous vehicle operation promises reduced driving speeds as well as reduced lateral and longitudinal accelerations. This can consequently lead to decreasing operation loads, thus enabling potentially more light-weight, cost-effective, resource-saving and energy-efficient vehicle components.

This paper discusses the dependency between powertrain design and automated driving. The research questions are to what extent automated driving influences the powertrain design and how energy and fuel consumption is affected in comparison to customer driving. For this investigation a concept study is carried out for a D-segment vehicle and multiple powertrain topologies, ranging from non-electrified to plug-in hybrids and battery electric vehicles. In order to answer the research questions, the used development process and the methods for optimizing the drive system are presented accordingly, taking into account all vehicle requirements, the drive system and the components and their interactions with each other. This work focuses on two automated driving functions developed at the Institute of Automotive Engineering of the Technische Universität Braunschweig. The functions are an “automated valet parking” and a “highway pilot”.

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.

In view of the rapidly increasing complexity of conventional as well as hybrid powertrains, a systematic composition platform seeking for the global optimum powertrain is presented in this paper. The platform can be mainly divided into three parts: the synthesis of the transmission, the synthesis of the internal combustion engine (ICE) and the optimization and evaluation of the entire powertrain. In regard to the synthesis of transmission concepts, a systematical and computer-aided tool suitable both for conventional und hybrid transmissions is developed. With this tool, all the potential transmission concepts, which can realize the desired driving modes or ratios, can be synthesized based on the vehicle data and requirements.

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).

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.