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This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Battery simulation by a DSP-controlled high current power supply is used to improve repeatability and comparability of starting tests, especially at low temperatures. The simulator's algorithm calculates the internal resistance of the battery by a timely constant resistor and a variable resistor representing the actual discharge history. The output voltage of the simulator is set as a function of internal resistor and load current with temperature and state of charge as setup parameter. The simulator was evaluated in cold start testing in comparison to real batteries. As a result, batteries are simulated with high repeatability. Deviations to real battery behavior are in the range of test to test deviations using real batteries.

The software design of this new engine control unit is based on a unique and homogenous torque structure. All input signals are converted into torque equivalents and a torque coordinator determines their influence on the final torque delivered to the powertrain. The basic torque structure is independent on the type of fuel and can be used for gasoline, diesel, or CNG injection systems. This allows better use of custom specific algorithms and facilitates reusability, which is supported by the graphical design tool that creates all modules using automatic code generation. Injection specific algorithms can be linked to the software by simply setting a software switch.

Recent years have witnessed a dramatic increase in global ethanol production, while cellulosic feedstock or the algae-based production approach make more sustainable ethanol production foreseeable in many countries. The ethanol produced will increasingly penetrate the markets not only as blending component, but also as main fuel component, boosting demand for flex-fuel vehicles. One of the main challenges for flex-fuel vehicles is the cold start due to the poor vapor pressure of ethanol. This is detrimental to starting capability in DISI engines in particular, with increased cylinder wall wetting causing higher oil dilution. The most efficient solution for DISI engines is a smart injection strategy, enabling fuel vaporization during injection in the compression stroke. But this requires optimum injection parameters such as injection timing, split ratio and rail pressure.

The protection of pedestrians from injuries by accidental collision is a primary focus of the automotive industry and of government legislation [1]. In this area, scientists and developers are faced with a multitude of requirements. Complex scenes are to be analyzed. The wide spectrum of where pedestrians and cyclists appear on the road, weather, and light conditions are just examples. Data fusion of raw or preprocessed signals for several sensors (cameras, radar, lidar, ultrasonic) need to be considered as well. Accordingly, algorithms are very complex. When moving from prototypic environments to embedded systems, additional constraints must be considered. Limited system resources drive the need to simplify and optimize for technical and economic reasons. With all these constraints, how can the safety functions be safe-guarded? This submission considers scene-based methods for the development of vehicle functions from prototype to series production focusing on functional safety.

For the NOx removal from diesel exhaust, the selective catalytic reduction (SCR) and lean NOx traps are established technologies. However, these procedures lack efficiency below 200 °C, which is of importance for city driving and cold start phases. Thus, the present paper deals with the development of a novel low-temperature deNOx strategy implying the catalytic NOx reduction by hydrogen. For the investigations, a highly active H2-deNOx catalyst, originally engineered for lean H2 combustion engines, was employed. This Pt-based catalyst reached peak NOx conversion of 95 % in synthetic diesel exhaust with N2 selectivities up to 80 %. Additionally, driving cycle tests on a diesel engine test bench were also performed to evaluate the H2-deNOx performance under practical conditions. For this purpose, a diesel oxidation catalyst, a diesel particulate filter and a H2 injection nozzle with mixing unit were placed upstream to the full size H2-deNOx catalyst.

The development of energy efficient air conditioning systems for electric vehicles is an ever increasing challenge, because the cooling as well as the heating of the passenger compartment reduces the cruising range dramatically. Electric cars are usually equipped with a scroll compressor and a separate electric motor with appropriate power electronics. However, this solution is critical in terms of the installation space, the weight and also the costs. Therefore, an innovative and energy efficient drivetrain structure for electric vehicles was developed, which integrates the motor of the A/C-compressor directly into the drivetrain. Thus it is possible to switch off the compressor motor and to use the main motor for the drive of the compressor at certain driving situations. As a result, the operating point of the main motor can be shifted to a better efficiency.

To meet the targets of Indian future emission legislation, an electrification and automation of today’s manual transmission technology is necessary. For this reason, IAV invented an electrified automated transmission family, based on well-known manual transmission technology. This low-cost automated manual transmission (AMT) approach is equipped with a 48 V electric machine and can be used as pure electric or hybrid drivetrain. Furthermore, it is possible to realize power shifts by using just one dry friction element. A small number of standard components combined with a low voltage electric machine and an electromechanical actuation system is sufficient to create a maximum of flexibility to meet future emission fleet targets, without having the disadvantageous high costs for a high-voltage electric system. To detect the optimal powertrain configuration, IAV used a unique advance development tool called Powertrain Synthesis.

The low-NOx standard for heavy-duty trucks proposed by the California Air Resources Board will require rapid warm-up of the aftertreatment system (ATS). Several different aftertreatment architectures and technologies, all based on selective catalytic reduction (SCR), are being considered to meet this need. One of these architectures, the close-coupled SCR (ccSCR), was evaluated in this study using two different physics-based, 1D models; the simulations focused on the first 300 seconds of the cold-start Federal Test Procedure (FTP). The first model, describing a real, EuroVI-compliant engine equipped with series turbochargers, was used to evaluate a ccSCR located either i) immediately downstream of the low-pressure turbine, ii) in between the two turbines, or iii) in a by-pass around the high pressure turbine.

The majority of powertrain types considered important contributors to achieving the CO2 targets in the transportation sector employ a battery as an energy storage device. The need for batteries is hence expected to grow drastically with increasing market share of CO2-optimized powertrain concepts. The resulting huge pressure on the development of future electrochemical energy storage systems necessitates the application of advanced methodologies enabling a fast and cost-efficient concept definition and optimization process. This paper presents a model-based methodology for the optimization of BEV thermal management concept layouts and operation strategies targeting minimized energy consumption. Starting at the vehicle level, the proposed methodology combines appropriate representations of all primary powertrain components with 1D cooling and refrigerant circuit models and focuses on their interaction with the battery chemistry.

There is an enormous effort to implement safety functionality into battery systems to prevent any accidents with the poisonous and inflammable ingredients of the electrolytes and electrode materials. But not only the safety regulation for lithium ion batteries will be different in comparison to the home electronics application, also the operating strategy must be different to guaranty the required lifetime in the automotive industry up to 10-12 years. This paperwork will show an approach to get offline (on test benches) and/or online (installed inside the car) information regarding the current healthy and state inside the cell. As an approach modeling of physical effects by the help of electro impedance spectroscopy (EIS) will be applied.

Future heavy-duty (HD) concepts should fulfill very tight tail-pipe NOx emissions and simultaneously fulfill the fuel efficiency targets. In current HD Euro VII discussions, real working cycles become key to ensure emission conformity. For instance, cold start and cold ambient conditions during testing with low load profiles starting from 0% payload, require external heating measures. Knowing the trade-off between fuel consumption and tail-pipe NOx emissions a holistic engine and EAT system optimization with innovative thermal management is required. Towards a carbon neutral mobility, Hydrogen combustion engines are one of the key solutions. Advanced combustion system development enables maximal usage of lean burning as the major advantage of the Hydrogen fuel for efficiency improvement and NOx reduction.

The powertrain electrification is currently not only taking place in public road mobility vehicles, but is also making its way to the racetrack, where it’s driving innovation for developments that will later be used in series production vehicles. The current development focus for electric vehicles is the balance between driving power, range and weight, which is given even greater weighting in racing. To redefine the current limits, IAV developed a complete e-powertrain for a racing MX motorcycle and integrated it into a real drivable demonstrator bike. The unique selling point is the innovative direct phase-change cooling (PCC) of the three-phase e-motor and its power electronics, which enables significantly increased continuous power (Pe = 40 kW from 7,000 rpm to 9,000 rpm) without thermal power reduction. The drive unit is powered by a replaceable Lithium-Ion round cell battery (Ubat,max = 370V) with an energy storage capacity of Ebat = 5 kWh.