Due to increasing sales figures, the energy consumption of battery-electric vehicles is moving further into focus. In addition to efficient driving, it is also important that the energy losses during AC charging are as low as possible for a sustainable operation. In many situations it is not possible or necessary to charge the vehicle with the maximum charging power e.g., in apartment buildings. The influence of the charging mode (number of phases used, in-cable-control-box or used wallbox, charging current) on the charging efficiency is often unknown. In this work, the energy consumption of two electric vehicles in the Worldwide Harmonized Light-Duty Vehicles Test Cycle is presented. In-house developed measurement technology and vehicle CAN data are used. A detailed breakdown of charging losses, drivetrain efficiency, and overall energy consumption for one of the vehicles is provided. Finally, the results are discussed with reference to avoidable CO${}_2$ emissions. The charging losses of the tested vehicles range from 12.79 to 20.42%. Maximum charging power with three phases and 16 A charging current delivers the best efficiencies. Single-phase charging was considered down to 10 A, where the losses are greatest. The drivetrain efficiency while driving is 63.88% on average for the WLTC, 77.12% in the “extra high” section and 23.12% in the “low” section. The resulting energy consumption for both vehicles is higher than the OEM data given (21.6 to 44.9%). Possible origins for the surplus on energy consumption are detailed. Over 100,000 km, unfavorable charging results in additional CO${}_2$ emissions of 1.24 t. The emissions for an assumed annual mileage of 20,000 km are three times larger than for a class A+ refrigerator. A classification of charging modes and chargers thus appears to make sense. In the following work, efficiency improvements in the charger as well as DC charging will be proposed.

Current batteries of battery electric vehicles (BEVs) require a battery management system (BMS) in order to enable a safe and long-lasting operation. The main functions of the battery management systems are a continuous monitoring of the voltage of each cell, a continuous monitoring of the battery temperature, the control of the charge current and the discharge current as well as the prevention of both a deep discharge and an overcharging. For the realization of these functions, different architectures are possible, ranging from an individual intelligent system at each cell up to a realization of the whole BMS within one central computing unit for the whole vehicle. This paper investigates and structures different architectural possibilities, discusses analysis possibilities and presents approaches for the synthesis of sensible architectures such as BMS. A concept synthesis for the start-up and shut-down of the high-voltage system is presented by comparing three different integrated pre- and discharging circuits and using a Hardware-in-the-Loop (HiL) program as an example. Finally, a topology consisting of three switches and two resistors (3S2R2) turns out to be the best one, due to the number of components, safety and price.

Since battery electric vehicle (BEV) sales are increasing, the calculation of necessary electric power supply, and energy consumption data, and vehicle range is important. The Worldwide harmonized Light vehicles Test Procedure (WLTP) currently in use can deliver data to collect comparable energy consumption data for different vehicles on defined chassis dynamometer test cycles. Nevertheless, the energy consumption and so the range of BEVs are also dependent on the individual trajectory of the user. Therefore, five velocity profiles are developed in this work. The maximum speeds are based on typical velocities in German city traffic and extra-urban traffic. The energy required to finish a single velocity profile is assumed to be constant despite varying maximum velocities. With this kind of driving profiles it is possible to create an individual and more precise statement on the energy consumption and the range of a BEV. In this work, the profiles are driven on a chassis dynamometer with an VW e-Up. The vehicle charging efficiency is tested with two different AC charging modes and is also taken into account. The drive efficiencies of the tested vehicle are presented in dependence of the velocity profile driven. Finally the results are compared with a real-driving velocity profile and the energy consumption data obtained by the board computer of the vehicle.

In the field of inner-city cargo transportation, solutions such as electrified cargo trailers are increasingly being used. To provide an intelligent drivetrain control system that improves driving dynamics and enables safety, it is necessary to know the characteristics of the trailer system. This includes the behavior of the tires. Existing investigations of bicycle tires focus on camber-angle-dependent models. However, in most trailers, a rigid mounting of the tires without camber is used. For this reason, a bicycle tire model is created within the scope of this study using real measurement data that represent a 20 in tire with typical wheel loads and without camber. The measurements were collected with the mobile tire measurement laboratory of the Bern University of Applied Sciences on an asphalt test site under real conditions. Crosstalk occurring in the measurement hub during the data collection was successfully corrected using a matrix method. With help of the so-called Magic Formula, a tire model was created that can be used for driving dynamics simulations and controller design.

Currently, a consensus in the scientific community can be observed that it is necessary to reduce the carbon footprint and the use of fossil resources in order to ensure the ongoing well-being of humanity and our planet. Battery electric vehicles (BEVs) can contribute to this reduction, as they can use energy from sustainable sources as well as store it in order to enable individual mobility. Still, as long as sustainable energy is not available in abundance and a share of our energy still is generated using fossil sources, it is important to consider the energy consumption of these BEVs in greater detail. BEVs may actually consume more energy than necessary due to an architecture borrowed from non-BEVs, due to their drive-train topology, due to many individual product development issues and last but not least because they are not operated at their highest efficiency. This paper addresses the evaluation of a specific sustainable product development process for BEVs. The study is based on detailed energy consumption simulations of smaller BEVs with different drive train technologies. A general consideration of sustainability and utility based on the design choices, as well as of societal consequences, leads to requirements and challenges for sustainable product development. A digital product development process is described, which addresses these challenges.