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Transfer path analysis is a powerful tool to support the vehicle NVH development. On the one hand it is a fast method to gain an overview of the complex interplay in the vehicle noise generation process. On the other hand it can be used to identify critical noise paths and vehicle components responsible for specific noise phenomena. FEV has developed several tools, which are adapted to the considered noise phenomena: Powertrain induced interior noise and vibration is analyzed by VINS (Vehicle Interior Noise Simulation), which allows the deduction of improvement measures fast enough for application in the accelerated vehicle development process. Further on vehicle/powertrain combinations not realized in hardware can be evaluated by virtual installation of the powertrain in the vehicle, which is especially interesting in the context of engine downsizing from four to three or six to four cylinders.

Using a holistic 1D engine simulation approach for the modelling of full-transient engine operation, allows analyzing future engine concepts, including its exhaust gas aftertreatment technology, early in the development process. Thus, this approach enables the investigation of both important fields - the thermodynamic engine process and the aftertreatment system, together with their interaction in a single simulation environment. Regarding the aftertreatment system, the kinetic reaction behavior of state-of-the-art and advanced components, such as Diesel Oxidation Catalysts (DOC) or Selective Catalytic Reduction Soot Filters (SCRF), is being modelled. Furthermore, the authors present the use of the 1D engine and exhaust gas aftertreatment model on use cases of variable valve train (VVT) applications on passenger car (PC) diesel engines.

The automotive industry continues to develop new powertrain technologies aimed at reducing overall vehicle level fuel consumption. The ongoing trends of “downsizing” and “down speeding” have led to the development of turbocharged engines with low displacement and high torque density. In order to meet the launch response requirements with these engines as well as fuel economy needs, transmissions with large ratio spreads will need to be developed. Due to the lack of torque amplification from the torque converter, the next generation of dual clutch transmissions (DCT) will need to have larger launch ratios and ratio spreads than currently available in production today. This paper discusses the development of a new family of DCT (called “xDCT”) for use in front wheel drive vehicles, aimed at meeting some of these challenges. The xDCT family features two innovative concepts, the idea of “gear generation” and “supported shifts”.

The interest in electric propulsion of vehicles has increased in recent years and is being discussed extensively by experts as well as the public. Up to now the driving range and the utilization of pure electric vehicles are still limited in comparison to conventional vehicles due to the limited capacity and the long charging times of today's batteries. This is a challenge to customer acceptance of a pure electric vehicle, even for a city car application. A Range Extender concept could achieve the desired customer acceptance, but should not impact the “electric driving” experience, and should not cause further significant increases in the manufacturing and purchasing cost. The V2 engine concept presented in this paper is particularly suited to a low cost, modular vehicle concept. Advantages regarding packaging can be realized with the use of two generators in combination with the V2 engine.

A new approach is presented to modelling wall heat transfer in the exhaust port and manifold within 1D gas exchange simulation to ensure a precise calculation of thermal exhaust enthalpy. One of the principal characteristics of this approach is the partition of the exhaust process in a blow-down and a push-out phase. In addition to the split in two phases, the exhaust system is divided into several sections to consider changes in heat transfer characteristics downstream the exhaust valves. Principally, the convective heat transfer is described by the characteristic numbers of Nusselt, Reynolds and Prandtl. However, the phase individual correlation coefficients are derived from 3D CFD investigations of the flow in the exhaust system combined with Low-Re turbulence modelling. Furthermore, heat losses on the valve and the seat ring surfaces are considered by an empirical model approach.

Modifications have been made to the calibration and control of Diesel engines to increase the temperature of the exhaust especially in cold weather and part load operation. The main purpose for this advanced calibration is to enable the reduction of emissions by improving catalytic activity. An alternative method for increasing exhaust temperature is providing electric heat. Test results show the feasibility of applying various amounts of electric heat and the related increases in exhaust temperature as well as speed of heating. Simulation modeling extends the application of electric heat to a complete engine map and explores the potential impact on engine performance and emission reduction benefits.

Advanced powertrains for modern vehicles require the optimization of conventional combustion engines in combination with tailored electrification and vehicle connectivity strategies. The resulting systems and their control devices feature many degrees of freedom with a large number of available adjustment parameters. This obviously presents major challenges to the development of the corresponding powertrain control logics. Hence, the identification of an optimal system calibration is a non-trivial task. To address this situation, physics-based control approaches are evolving and successively replacing conventional map-based control strategies in order to handle more complex powertrain topologies. Physics-based control approaches enable a significant reduction in calibration effort, and also improve the control robustness.

The increasing pressure on the engine development process via tighter legislations and increasing competition lead to search for the best possible design for each engine component. Especially the dynamic parts, which contribute to total engine friction at most, are under extreme focus. The search for the optimum layout of crankshafts considering the design aims, such as low friction, low weight and high durability, is usually a manual variation process with limited number of design loops. Within this study computer aided (CA) automated optimization methodologies are integrated into the design procedure to achieve the best possible design solution according to the objectives under consideration of the predefined constraints. An extensive crankshaft optimization study is performed and resulted in many novel and patented design features. A case study for a modern in-line four-cylinder crankshaft is performed to show the potentials.

1D codes are nowadays commonly used to investigate a turbocharged ICE performance, turbo-matching and transient response. The turbocharger is usually described in terms of experimentally derived characteristic maps. The latter are commonly measured using the compressor as a brake for the turbine, under steady “hot gas” tests. This approach causes some drawbacks: each iso-speed is commonly limited to a narrow pressure ratio and mass flow rate range, while a wider operating domain is experienced on the engine; the turbine thermal conditions realized on the test rig may strongly differ from the coupled-to-engine operation; a “conventional” net turbine efficiency is really measured, since it includes the effects of the heat exchange on the compressor side, together with bearing friction and windage losses.

With the increasing popularity of seamless gear changing and smooth driving experience along with the need for high fuel efficiency, transmission system development has rapidly increased in complexity. So too has transmission control software while quality requirements are high and time-to-market is short. As a result, extensive testing and documentation along with quick and efficient development methods are required. FEV responds to these challenges by developing and integrating a transmission software product line with an automated verification and validation process according to the concept of Continuous Integration (CI). Hence, the following paper outlines a software architecture called “PERSIST” where complexity is reduced by a modular architecture approach. Additionally, modularity enables testability and tracking of quality defects to their root cause.

Despite the trend in increased prosperity, the Indian automotive market, which is traditionally dominated by highly cost-oriented producion, is very sensitive to the price of fuels and vehicles. Due to these very specific market demands, the U-LCV (ultra-light commercial vehicle) segment with single cylinder natural aspirated Diesel engines (typical sub 650 cc displacement) is gaining immense popularity in the recent years. By moving to 2016, with the announcement of leapfrogging directly to Bharat Stage VI (BS VI) emission legislation in India, and in addition to the mandatory application of Diesel particle filters (DPF), there will be a need to implement effective NOx aftertreament systems. Due to the very low power-to-weight ratio of these particular applications, the engine operation takes place under full load conditions in a significant portion of the test cycle.

One of the challenges faced when using Li-ion batteries in electric vehicles is to keep the cell temperatures below a given threshold. Mathematical modeling would indeed be an efficient tool to test virtually this requirement and accelerate the battery product lifecycle. Moreover, temperature predicting models could potentially be used on-board to decrease the limitations associated with sensor based temperature feedbacks. Accordingly, we present a complete modeling procedure which was used to calculate the cell temperatures during a given electric vehicle trip. The procedure includes a simple vehicle dynamics model, an equivalent circuit battery model, and a 3D finite element thermal model. Model parameters were identified from measurements taken during constant current and pulse current discharge tests. The cell temperatures corresponding to an actual electric vehicle trip were calculated and compared with measured values.

Tighter emission limits are discussed and established around the world to improve quality of the air we breathe. In order to control global warming, authorities ask for lower CO2 emissions from combustion engines. Lots of efforts are done to reduce engine out emissions and/or reduce remaining by suitable after treatment systems. Watlow, among others, a manufacturer of high accurate, active temperature sensor ExactSense™, wanted to understand if temperature sensor accuracy can have an influence on fuel consumption (FC). For this purpose a numerical approach was chosen where several non-road driving cycles (NRTCs) were simulated with the data base of a typical Stage IV heavy duty diesel engine. The engine is equipped with an exhaust gas after treatment system consisting of a DOC, CDPF and an SCR. In this work scope, the investigations shall be restricted to the FC benefits obtained in the active and passive DPF regeneration.

This paper presents the comparison of two different approaches for crankcase structural analysis. The first approach is a conventional quasi-static simulation, which will not be detailed in this work and the second approach involves determining the dynamic loading generated by the crankshaft torsional, flexural and axial vibrations on the crankcase. The accuracy of this approach consists in the development of a robust mathematical model that can couple the dynamic characteristics of the crankshaft and the crankcase, representing realistically the interaction between both components. The methodology to evaluate these dynamic responses is referred to as hybrid simulation, which consists of the solution of the dynamics of an E-MBS (Elastic Multi Body System) coupled with consecutive FEA (Finite Element Analysis).

Model-based control strategies along with an adapted calibration process become more important in the overall vehicle development process. The main drivers for this development trend are increasing numbers of vehicle variants and more complex engine hardware, which is required to fulfill the more and more stringent emission legislation and fuel consumption norms. Upcoming fundamental changes in the homologation process with EU 6c, covering an extended range of different operational and ambient conditions, are suspected to intensify this trend. One main reason for the increased calibration effort is the use of various complex aftertreatment technologies amongst different vehicle applications, requiring numerous combustion modes. The different combustion modes range from heating strategies for active Diesel Particulate Filter (DPF) regeneration or early SCR light-off and rich combustion modes to purge the NOx storage catalyst (NSC) up to partially premixed combustion modes.

The increased demand in fuel economy and the reduction of CO₂ emissions results in continued efforts to downsize engines. The downsizing efforts result in engines with lower displacement as well as lower number of cylinders. In addition to cylinder and displacement downsizing the development community embarks on continued efforts toward down-speeding. The combination of the aforementioned factors results in engines which can have high levels of torsional vibrations. Such behavior can have detrimental effects on the drivetrain particularly during the development phase of these. Driveshafts, couplings, and dynamometers are exposed to these torsional forces and depending on their frequency costly damages in these components can occur. To account for these effects, FEV employs a multi-body-system modeling approach through which base engine information is used to determine optimized drivetrain setups. All mechanical elements in the setup are analyzed based on their torsional behavior.

Exhaust emission reduction and improvements in energy consumption will continuously determine future developments of on-road and off-road engines. Fuel flexibility by substituting Diesel with Natural Gas is becoming increasingly important. To meet these future requirements engines will get more complex. Additional and more advanced accessory systems for waste heat recovery (WHR), gaseous fuel supply, exhaust after-treatment and controls will be added to the base engine. This additional complexity will increase package size, weight and cost of the complete powertrain. Another critical element in future engine development is the optimization of the base engine. Fundamental questions are how much the base engine can contribute to meet the future exhaust emission standards, including CO2 and how much of the incremental size, weight and cost of the additional accessories can be compensated by optimizing the base engine.

In recent years, more attention has been focused on environment pollution and energy source issues. As a result, increasingly stringent fuel consumption and emission legislations have been implemented all over the world. For automakers, enhancing engine’s efficiency as a must contributes to lower vehicle fuel consumption. To reach this goal, Geely auto started the development of a 3-cylinder 1.0L turbocharged direct injection (TGDI) gasoline engine to achieve a challenging fuel economy target while maintaining fun-to-drive and NVH performance. Demanding development targets for performance (specific torque 205Nm/L and specific power 100kW/L) and excellent part-load BSFC were defined, which lead to a major challenge for the design of the combustion system. Considering air/fuel mixture, fuel wall impingement and even future potential for lean burn combustion, a symmetrical layout and a central position for the injector with 200bar injection pressure was determined.

Modeling thermal systems in Battery Electric Vehicles (BEVs) is crucial for enhancing energy efficiency through predictive control strategies, thereby extending vehicle range. A major obstacle in this modeling is the often limited availability of detailed system information. This research introduces a methodology using neural networks for system identification, a powerful technique capable of approximating the physical behavior of thermal systems with minimal data requirements. By employing black-box models, this approach supports the creation of optimization-based operational strategies, such as Model Predictive Control (MPC) and Reinforcement Learning-based Control (RL). The system identification process is executed using MATLAB Simulink, with virtual training data produced by validated Simulink models to establish the method's feasibility. The neural networks utilized for system identification are implemented in MATLAB code.

For on- and off-highway applications in 2012/2014 new legislative emissions requirements will be applied for both European (EURO 6/stage 4) and US (US 2010/Tier4 final) standards. Specifically the NOX-emission limit will be lowered down to 0.46 g/kWh (net power ≻ 56 kW (EU)/130 kW (US) - 560 kW). While for the previous emissions legislation various ways could be used to stay within the emissions limits (engine internal and aftertreatment measures), DeNOX-aftertreatment systems will be mandatory to reach future limits. In these kinds of applications fuel consumption of the engines is a very decisive selling argument for customers. Total cost of ownership needs to be as low as possible. The trade-off between fuel consumption and NOX emissions forces manufacturers to find an optimal solution, especially with regard to increasing fuel prices. In state-of-the-art calibration processes the aftertreatment system is considered separately from the calibration of the thermodynamics.