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Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

Beside the automotive industry, where 2-cylinder inline engines are catching attention again, twin-cylinder configurations are quite usual in the small engine world. From stationary engines and range-extender use to small motorcycles up to big cruisers and K-Cars this engine architecture is used in many types of applications. Because of very good overall packaging, performance characteristics and not least the possibility of parts-commonality with 4-cylinder engines nearly every motorcycle manufacturer provides an inline twin in its model range. Especially for motorcycle applications where generally the engine is a rigid member of the frame and vibrations can be transferred directly to the rider an appropriate balancing system is required.

With the increase of hotel and ancillary loads and replacement of engine driven mechanical and hydraulic loads with electrical loads, automotive systems are becoming more electric. This is the concept of More Electric Cars (MEC) that necessitates a higher system voltage, such as the proposed 42V, for conventional cars. In this paper, the development of the 42V electric power system for vehicle applications is reviewed. The system architecture and motor drive problems associated with the 42V electric power system are analyzed. Solutions to these problems are also discussed.

In this paper, a mild hybrid drive train has been proposed. A small electric motor with low rated voltage (42 V) is used to (1) propel the vehicle at low speed, (2) replace the fluid-coupled torque converter and (3) realize regenerative braking. With proper design and control, the fuel economy in urban driving can be significantly improved without much change from conventional drive train to the mild hybrid drive train.

Significant amount of energy is lost in frequent braking, automatic transmission and engine idling for a conventional engine powered passenger car while driving in cities. In this paper, a mild hybrid vehicle drive train has been introduced. It uses a small electric motor with floating stator, called TRANSMOTOR and small and a battery pack. The transmotor functions as a generator, engine starter, frictionless clutch (electric torque coupler), regenerative braking and propelling. The mild hybrid drive train can effectively reduce the urban-driving fuel consumption by regenerative braking, eliminate of energy losses in conventional automatic transmission and engine idling. The drive train can use low voltage system (42V for example), due to the low electric power rating, and is more similar to conventional drive train than full hybrid vehicle. Therefore, less effort is needed to evolve it from conventional vehicles.

In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Global vehicle simulation is already a well-established tool to support the vehicle development process. In contrast to conventional vehicles, electrified powertrains offer an additional challenge to the thermal conditioning: the durability of E-components is not only influenced by temperature peaks but also by the duration and amplitude of temperature swings as well as temperature gradients within the components during their lifetime. Keeping all components always at the preferred lowest temperature level to avoid ageing under any conditions (driving, parking, etc.) will result in very high energy consumption which is in contradiction to the efficiency targets.

This paper discusses a new computer simulation tool, V-Elph, which extends the capabilities of previous modeling and simulation efforts by facilitating in-depth studies of any type of hybrid or all electric configuration or energy management strategy through visual programming and by creating components as hierarchical subsystems which can be used interchangeably as embedded systems. V-Elph is composed of detailed models of four major types of components: electric motors, internal combustion engines, batteries, and vehicle dynamics which can be integrated to simulate drive trains having all electric, series hybrid, and parallel hybrid configurations. V-Elph was written in the Matlab/Simulink graphical simulation language and is portable to most computer platforms. A simulation study of a sustainable, electrically-peaking hybrid-electric vehicle was performed to illustrate the applicability of V-Elph to hybrid and electric vehicle design.

The rate in the electrification of vehicles has risen in recent years. With intensified development more and more attention is paid to the noise and vibration in such vehicles especially from the EDU (Electric Drive Unit). In this paper the main NVH simulation process of a high-speed E-axle up to 30,000 rpm for premium class vehicle application is presented. The high speed, high-power density and lightweight design introduces new challenges. Benchmarking of different EDUs and vehicles leads to targets which can be used at the early stage of development as subsystem targets. This paper shows the CAE methodology which can be used to verify the design and guarantee the target achievement. Using CAE both source and structure can be optimized to improve the NVH behavior.

The automotive domain has seen safety engineering at the forefront of the industry’s priorities for the last decade. Therefore, additional safety engineering efforts, design approaches, and well-established safety processes have been stipulated. Today many connected and automated vehicles are available and connectivity features and information sharing are increasingly used. This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cybersecurity. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has, therefore, recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles.

Today, OEMs are challenged with an increasing number of powertrain variants and complexity of controls software. They are facing internal pressure to provide mature and refined calibrations earlier in the development process. Until now, it was difficult to respond to these requests as the drivability's calibration tasks are mostly done in vehicles. This paper describes a new methodology designed to answer these challenges by performing automated shift quality calibration prior to the availability of vehicles. This procedure is using a powertrain dynamometer coupled with a real-time vehicle dynamics model. By using a Power Train Test Bed (PTTB), a physical vehicle is not required. As soon as the vehicle dynamics model and its parameters have been defined, it can be simulated on the PTTB and drivability calibrations can be developed. A complete powertrain is coupled with low inertia and highly dynamic dynamometers.

Validation of highly automated or autonomous vehicles is nowadays still a major challenge for the automotive industry. Furthermore, the homologation of ADAS/AD vehicles according to global regulations is getting more essential for their safe development and deployment around the world. In order to assure that the autonomous driving function is able to cope with the huge number of possible situations during operation, comprehensive testing of the functions is required. However, conventional testing approaches such as driving distance-based validation approach in the real world, can be time- and cost-consuming. Therefore, a scenario-based virtual validation and testing method is considered to be a proper solution. In this paper, we propose a virtual assessment framework using a fully automated test case generation method. This framework is embedded into the continuous development and validation process.

Calibrating a vehicle’s powertrain for dynamic operation needs to focus on efforts to mitigate the risks of thermal overload which may arise in the stator or rotor components of an e-motor. Risks also may arise for expected NVH or durability targets, with torque and torque “oscillations” acting as primary sources for the vehicles’ NVH behavior. Both topics, temperature measurement of stator and rotor as well as dynamic torque measurements of the powertrain’s drive shaft are addressed with examples demonstrating the sensors applications in normal test bed and vehicle configurations.

The automotive industry is racing to introduce some degree of hybridization into their product ranges. Since the term “hybrid vehicle” can cover a wide range of differing technologies and drivetrain topologies, this has led to a large amount of vehicles that call themselves “hybrid”. This poses an interesting challenge for marketers to differentiate these vehicles from the incumbents. However, it is not just the marketers who are faced with challenges, the developers of such hybrid drivetrains are faced with a rise in technical complexity due to the wide range of operating modes hybridization introduces. As propulsive torque is being generated in more than one place in a hybrid vehicle, the transitions from conventional drive to electrically supported drive bring with them complex aspects of multi-dimensional system control. The challenge is to be able to implement hybrid technology in an existing drivetrain, while adapting the existing components as required.

The automotive industry is racing to introduce some degree of hybridization into their product ranges. Since the term "hybrid vehicle" can cover a wide range of differing technologies and drivetrain topologies, this has led to a plethora of vehicles that call them "hybrid." This poses an interesting challenge for marketers to differentiate these vehicles from the incumbents. However, it is not just the marketers who are faced with challenges, the developers of such hybrid drivetrains are faced with a rise in technical complexity due to the wide range of operating modes hybridization introduces. As propulsive torque is being generated in more than one place in a hybrid vehicle, the transitions from conventional drive to electrically supported drive bring with them complex aspects of multi-dimensional system control. The challenge is to be able to implement hybrid technology in an existing drivetrain, while adapting the existing components as required.

For a broad acceptance of electric vehicles, the trade-off between all electric range and battery cost respectively weight represents the most important challenge. The all electric range obtained under real world conditions most often deviates significantly from the nominal value which is measured under idealized conditions. Under extreme conditions - slow traffic and demanding requirements for cabin heating or cooling - the electrical range might become less a question of spatial distance but even more of total operation time. Whereas with conventional powertrain, high flexibility of the total driving range can be obtained without sacrificing cost, with a pure battery vehicle this results in extreme high cost and weight of the energy storage. Therefore the difference between the typical daily driving range (e.g. in Germany 80-90% is below 50 km) and the minimum total range requested by most customers for acceptance of battery vehicles (200- 250 km), becomes essential.

A fuel cell/battery hybrid system for an electric vehicle was characterized under simulated driving conditions. The fuel cell is a 72 cell stack with 270 cm2 per cell of active electrode area. It has a continuous output of 1500 Watts and a peak power of 3000 Watts operating on hydrogen and atmospheric pressure air. The batteries are a tubular flooded lead-acid type. Seven 6 volt modules were connected in series with each module having a normal capacity of 205 Ahr. The fuel cell battery hybrid system was laboratory tested using a variable load battery cycler to simulate electric vehicle operation over a Modified Simplified Federal Urban Driving Schedule (MSFUDS). The fuel cell/battery hybrid operated successfully under steady state and dynamic conditions with the performance of the fuel cell only slightly degraded under the dynamic conditions of MSFUDS compared to steady state operation.

This paper presents calculations of external car aerodynamics by using the Partial-Averaged Navier-Stokes (PANS) variable resolution model in conjunction with the Finite Volume (FV) immersed-boundary method. The work presented here is the continuation of the study reported in Basara et al. [1, 2]. In that work, it was shown that the same accuracy of predicted aerodynamic forces could be achieved for both types of computational meshes, the standard body-fitted mesh and the immersed boundary (IB) Cartesian mesh, by using the Reynolds-Averaged Navier-Stokes (RANS) k-ζ-f model as well as by using the Partially-Averaged Navier-Stokes (PANS) method. Based on the accuracy achieved, Basara et al. [2] concluded that further work could focus on evaluating the turbulence modelling on the immersed boundary meshes only.

The demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

Currently lithium-batteries are the most promising electrical-energy storage technology in fully-electric and hybrid vehicles. A crashworthy battery-design is among the numerous challenges development of electric-vehicles has to face. Besides of safe normal operation, the battery-design shall provide marginal threat to human health and environment in case of mechanical damage. Numerous mechanical abuse-tests were performed to identify load limits and the battery's response to damage. Cost-efficient testing is provided by taking into account that the battery-system's response to abuse might already be observed at a lower integration-level, not requiring testing of the entire pack. The most feasible tests and configurations were compiled and discussed. Adaptions of and additions to existing requirements and test-procedures as defined in standards are pointed out. Critical conditions that can occur during and after testing set new requirements to labs and test-rigs.

The noise vibration and harshness (NVH) simulation of electric machines becomes increasingly important due to the use of electric machines in vehicles. This paper describes a method to reduce the calculation time and required memory of the finite element NVH simulation of electrical machines. The stator of a synchronous electrical machine is modeled as a two-dimensional problem to reduce investigation effort. The electromagnetic forces acting on the stator are determined by FE-simulation in advance. Since these forces need to be transferred from the electromagnetic model to the structural model, a coupling algorithm is necessary. In order to reduce the number of nodes, which are involved in the coupling between the electromagnetic and structural model, multipoint constraints (MPC) are used to connect several coupling nodes to one new coupling node. For the definition of the new coupling nodes, the acting load is analyzed with a 2D-FFT.