The electrification of the powertrain has been an important topic in the automotive industry for several years. Despite the political support and great efforts on the part of the industry, the breakthrough of electromobility has not yet taken place. Topics such as range, infrastructure and costs continue to be major challenges.

At the IMS, various projects dealing with the subject of electromobility are investigated, which should contribute to the implementation of ecologically sustainable mobility that is cost-effective and suitable for everyday use. Here, purely electric drive systems but also plug-in hybrid and range extender concepts are considered.

In research at the IMS, emphasis is placed on optimizing the powertrain on the one hand, and on the other hand, not looking at the “vehicle” system in isolation but in the overall context with energy generation and user behavior. For example, the potentials are being explored by linking the transport and energy generation sectors to improve the overall environmental performance. Other projects focus on the implementation of innovative, efficient and high-performance powertrain concepts.

Current Projects Related to this Key Topic:

Period: 2018 – 2021

Cooperation: TU München (FZG), Leibniz Universität Hannover (IAL, IMKT), ATE, AVL, BMW, Fuchs, Lenze, Magna, Schaeffler

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Speed4E is the follow-up project to the successfully completed research project Speed2E. As with in Speed2E, a purely electric drive train with two high-speed electric machines is to be designed and developed. The maximum speed should be raised from 30,000 to 50,000 rpm to further increase the power density. Another special feature is the multispeed sub transmission, which is realized by positive locking elements (dog clutches). For this purpose, a dedicated shift actuator and an innovative transmission control is developed. The integration of the drivetrain into a vehicle will enable the evaluation and optimization of shifting and driving comfort.

Contact: Daniel Schöneberger

Further informationen you can find on the Project homepage

Period: 2019 – 2020

Cooperation: HEAG mobilo, Entega AG

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The project is funded by the Pioneer Fund (Booster-Line) of the TU Darmstadt. The goal is developing a software tool for optimizing the charging infrastructure of electrified vehicles. In the course of the German energy transition to more renewable energy sources, charging infrastructures adopt a key role as interface between the energy and the transport sector. Consequently, the dimensioning of charging infrastructures is subject to several parameters of different academic fields. To overcome the complexity of this task, we develop a holistic optimization environment. In cooperation with the HEAG mobilo and the Entega AG, we analyze what the future charging infrastructure for the public transport in Darmstadt might look like. Among others, we consider traffic data, weather conditions, and topology data.

Contakt: Benjamin Blat-Belmonte

Completed Projects Related to this Key Topic:

Period: 2017 – 2018

Cooperation: DLR-VF

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Within the framework of the project FahrKLang, an optimization environment for the comparative assessment of the environmental impact of different drive concepts has been developed, which provides a reliable basis for the comparison of powertrain concepts. Real fleet driving data, which depicts the characteristic usage behavior of the drivers in Germany, is the starting point for dimensioning the powertrain concepts that shall be compared. Using stochastic synthesis methods, representative driving cycles are generated from the fleet driving data, which can map the extensive data sets in compressed form. This enables a computationally efficient evaluation of drive concepts by means of simulation based on real driving data. An optimization environment is used to determine the optimal powertrain parameterization and an operating strategy adapted to each configuration. The objective function of the optimization consists of the greenhouse gas emissions over the entire life cycle of the vehicles. For each drivetrain concept, the minimum greenhouse gas emissions are determined by the optimal dimensioning of the components. In this way, a reliable basis for the comparison of different drive concepts is created. Over additional technology neutral constraints, such as a required slope climbing ability, the plausibility of the generated powertrain parametrization is ensured. This method provides a robust basis for comparing powertrain technologies under varying boundary conditions. Normally, available vehicles on the market are used to determine the typical component characteristics of substitute vehicles for different powertrain concepts. However, as existent vehicles have been developed under various and unknown development goals, such as performance or brand image, the comparison of lifecycle greenhouse gas emissions needs to be scrutinized. The FahrKlang project, on the other hand, identifies the optimal parameterization and operation strategy of all powertrain concepts for reducing the environmental impact for each scenario, so that a common basis for comparison of the drive concepts is created. This baseline illustrates the potential of various powertrain concepts to reduce greenhouse gas emissions (the minimum achievable).

For the comparative evaluation of drive concepts different scenarios of external factors are examined. In addition to a scenario for the current status from 2018, development scenarios, e.g. for the forecasted German power mix or regarding the battery technology for the years 2030 and 2050 are discussed. The project FahrKLang carries out a differentiated investigation, especially for long-distance capable vehicles.

Contact: Arved Eßer

Selected Publications:

Verbrauchs- und Emissionsbewertung von Fahrzeugantriebskonzepten für die Langstreckenmobilität der Zukunft

Comparative Real-Driving Optimization of Drivetrain Concepts regarding the Ecological Impact – A Big Data Approach for the Fleet.

Development of an Optimization Framework for the Comparative Evaluation of the Ecoimpact of Powertrain Concepts

Period: 2015 – 2018

Cooperation: AKKA, Daimler AG, Magna Getrag

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The „Two-Drive-Transmission with Range-Extender (DE-REX)“ is an innovative parallel-series hybrid powertrain concept. The DE-REX concept is characterized by coupling two identical electric motors and an internal combustion engine via an automated transmission with the drive shafts of the vehicle. Thereby, the transmissions consists of two subtransmissions with two speeds each. The powertrain offers high efficiency while pure electric and hybrid driving and performs gear shifts without interruption of traction force.

Based on the results of the completed project Doppel-E-Antrieb, in the publically fundet DE-REX project the electric motors and the transmission were designed, manufactured and set up as entire powertrain with an internal combustion engine at both a powertrain test bench and a demonstrator vehicle. All goals of the project were achieved and therefor, the project was successfully completed at June, 30th 2018.

Contact: Andreas Viehmann

Further informationen you can find on the project website.

Period: 2013 – 2016

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From the customer's point of view there are two major obstacles to the electrification of the powertrain: costs and range. Although plug-in hybrid vehicles (PHEV) address the range problem they do not solve the cost issue. These solutions are only supplemented by specific and expensive electrical components and therefore they have a high price.

Subproject IMS „concept and simulation (operating strategy)“

Participating enterprises and research institutions strive to show that plug-in hybrid vehicles are feasible at attractive costs with the aid of a modular and scalable construction system.

The project part of TU Darmstadt focuses on simulative optimization topics, especially on the hybrid operating strategy.

The objective is to build up a simulation environment with which it is possible to perform optimizations with automated parameter variations. In addition to the important step of determining the cost reduction potential it especially is essential to develop a modular operating strategy, which enables a comparison of different variants of PHEVs. Among other investigations the simulations are used to determine, how a modular approach of the operating strategy affects the overall efficiency.

Further information you can find on the project website.

Selected publications: BEREIT: Optimization of Parallel Hybrid Electric Vehicle (HEV) Fleets

Period: 2014-2017

Cooperation: TU München (FZG), Leibnitz Universität Hannover (IAL, IMKT)

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The overall goal of Speed2E was the development, optimization and test of a high-speed electric powertrain. Increasing the speed of the electric machine has the potential to significantly increase the power density of the electric machine and the overall efficiency of the vehicle. In order to meet requirements regarding drive-of-torque, top speed, efficiency and driving comfort, a powertrain with two electric motors was built, with a multispeed sub transmission. With the help of the operating strategy and transmission control developed for this innovative drivetrain by IMS, a safe, efficient and comfortable operation was realized and validated on a test bench.

Contact: Daniel Schöneberger

Further informationen you can find on the project website.

Period: 2012-2014

Cooperation: Institut für Elektrische Energiewandlung (TU Darmstadt)

The aim was to optimize a novel, highly efficient electric powertrain for a application as a traction drive in vehicles. The electric machines were designed as high speed drives with the highest possible torque and power density. The transmission should be designed to be as compact and efficient as possible with at least two stages and two gears per coupled electric machine.

Automated manual transmissions in a layshaft design are the simplest way for realizing multiple gears. With the Two-Drive-Transmission shown in the picture (an automated manual transmission (AMT) driven via two input paths) it is possible to avoid uncomfortable interruptions in tractive force during gear changes.

The use of two smaller electric motors also leads to an increase in efficiency compared to an electric vehicles with only one powerful electric motor. In partial load operation, only one of the two electric motors provides propulsion, resulting in higher specific load and thus better efficiency of the electric machine.

By coupling a combustion engine, a series-parallel hybrid architecture is created, which allows the operating modes “pure electric driving”, “series hybrid mode”, “parallel hybrid mode” and “pure combustion engine driving”.

First simulation results showed a considerable increase in efficiency and thus CO2 savings. In the New European Driving Cycle (NEDC), energy consumption is 17% lower than for an electric vehicle with only one electric motor and a 1-speed transmission.

Period: 2010-2013

Cooperation: TU Braunschweig (Institut für Fahrzeugtechnik)

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The development of modern vehicles and in particular of electrified drive systems is characterized by a high degree of complexity and a wide variety of variants with rising customer expectations. With a look at the design of the drives optimised to these boundary conditions, the focus is on legal requirements as well as specifications and customer requirements for the vehicle. In order to create an optimal vehicle concept, it is usually not appropriate to optimize the individual components with regard to the requirements, but to take a holistic view of the vehicle system requires a cross-component approach.

In this context, the so-called EVID method (Electric Vehicle Identification – identification of optimal powertrain configurations for electric vehicles) is used. The aim of the EVID method is to determine an optimal powertrain configuration for each of a selection of vehicle concepts that differ in their application profile (e.g. city vehicle or distribution vehicle in the city and overland traffic). If the input parameters are varied (design parameters of the components such as number of gears, ratio coverage, total system power, electric motor torque, battery capacity), the optimum solution is identified on the basis of the characteristic parameters relating to driving performance, energy balance and costs, which are taken into account in an evaluation function by means of different weightings. Mathematical models (MM) enable an evaluation with minimum computing time. These models are intended to represent the interrelationship of basic and characteristic parameters as accurately as possible. The MM and the computational models are then used in an optimization algorithm to identify the optimal concept, its components and the associated input and characteristic parameter values.

Project Structure graphic

Ausgewählte Veröffentlichungen: Antriebsstrangoptimierung von Elektrofahrzeugen