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The growing complexity of powertrain control strategies, software, and hardware is proving to be a significant challenge to the engineering community with regard to managing effective optimization to meet the desired performance. With an increased emphasis on shorter development time and the use of additional sensors and actuators becoming common, the increased dependence on physical models and use of complex interdependent control systems demands a thorough system understanding. This also encourages the use of process improvement tools to assist in an effective engineering process. In this paper, such a tool is discussed in its second phase of development. The Micro-HiL system will be discussed over a wide scope that focuses on the interests of the calibration and development community. The purpose of this paper is to provide an update on the Phase 2 activity of Micro-HiL development; Phase 1 was discussed in-depth at the 2011 SAE World Congress [2011-01-0703].

While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain.

Due to its high efficiency and superior durability the diesel engine is again becoming a prime candidate for future light-duty vehicle applications within the United States. While in Europe the overall diesel share exceeds 40%, the current diesel share in the U.S. is 1%. Despite the current situation and the very stringent Tier 2 emission standards, efforts are being made to introduce the diesel engine back into the U.S. market. In order to succeed, these vehicles have to comply with emissions standards over a 120,000 miles distance while maintaining their excellent fuel economy. The availability of technologies such as high-pressure common-rail fuel systems, low sulfur diesel fuel, NOx adsorber catalysts (NAC), and diesel particle filters (DPFs) allow the development of powertrain systems that have the potential to comply with the light-duty Tier 2 emission requirements. In support of this, the U.S.

Lignocellulosic biomass consists of (hemi-) cellulose and lignin. Accordingly, an integrated biorefinery will seek to valorize both streams into higher value fuels and chemicals. To this end, this study evaluated the overall combustion performance of both cellulose- and lignin derivatives, namely the high cetane number (CN) di-n-butyl ether (DnBE) and low CN anisole, respectively. Said compounds were blended both separately and together with EN590 diesel. Experiments were conducted in a single cylinder compression ignition engine, which has been optimized for improved combustion characteristics with respect to low emission levels and at the same time high fuel efficiency. The selected operating conditions have been adopted from previous “Tailor-Made Fuels from Biomass (TMFB)” work.

The growing number of passenger car variants and derivatives in all global markets, their high degree of software differentiability caused by regionally different legislative regulations, as well as pronounced market-specific customer expectations require a continuous optimization of the entire vehicle development process. In addition, ever stricter emission standards lead to a considerable increase in powertrain hardware and control complexity. Also, efforts to achieve market and brand specific multistep adjustable drivability characteristics as unique selling proposition, rapidly extend the scope for calibration and testing tasks during the development of powertrain control units. The resulting extent of interdependencies between the drivability calibration and other development and calibration tasks requires frontloading of development tasks.

Technologies that provide potential for significant improvements in engine efficiency include, engine downsizing/downspeeding (enabled by advanced boosting systems such as an electrically driven compressor), waste heat recovery through turbocompounding or organic Rankine cycle and 48 V mild hybridization. FEV’s Integrated Turbocompounding/Waste Heat Recovery (WHR), Electrification and Supercharging (FEV-ITES) is a novel approach for integration of these technologies in a single unit. This approach provides a reduced cost, reduced space claim and an increase in engine efficiency, when compared to the independent integration of each of these technologies. This approach is enabled through the application of a planetary gear system. Specifically, a secondary compressor is connected to the ring gear, a turbocompounding turbine or organic Rankine cycle (ORC) expander is connected to the sun gear, and an electric motor/generator is connected to the carrier gear.

The modern engine development process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. It is expected that predictive simulation tools that encompass the entire powertrain can potentially improve the efficiency of the calibration process. The testing of an ECU using a HiL system requires a real-time model. Additionally, if the initial parameters of the ECU are to be defined and tested, the model has to be more accurate than is typical for ECU functional testing. It is possible to enhance the generalization capability of the simulation, with neuronal network sub-models embedded into the architecture of a physical model, while still maintaining real-time execution. This paper emphasizes the experimental investigation and physical modeling of the port fuel injected SI engine.

A novel approach to the Integration of Turbocompounding/WHR, Electrification and Supercharging technologies (ITES) to reduce fuel consumption in a medium heavy-duty diesel engine was previously published by FEV. This paper describes a modified approach to ITES to reduce fuel consumption on a heavy-duty diesel engine applied in a Class 8 tractor. The original implementation of the ITES incorporated a turbocompound turbine as the means for waste heat recovery. In this new approach, the turbocompound unit connected to the sun gear of the planetary gear set has been replaced by an organic Rankine cycle (ORC) turbine expander. The secondary compressor and the electric motor-generator are connected to the ring gear and the carrier gear respectively. The ITES unit is equipped with dry clutch and band brake allowing flexibility in mechanical and electrical integration of the ORC expander, secondary compressor and electric motor-generator to the engine.

Automatic engine start/stop systems are becoming more prevalent and increasing market share of these systems is predicted due to demands on improving fuel efficiency of vehicles. Integration of an engine start/stop system into a “conventional” drivetrain with internal combustion engine and 12V board system is a relatively cost effective measure to reduce fuel consumption. Comfort and NVH aspects will continue to play an important role for customer acceptance of these systems. Possible delay during vehicle launch due to the engine re-start is not only a safety relevant issue but a hesitating launch feel characteristic will result in reduced customer acceptance of these systems. The engine stop and re-start behavior should be imperceptible to the driver from both a tactile and acoustic standpoint. The lack of masking effects of the engine during the engine stop phases can cause other “unwanted” noise to become noticeable or more prominent.

With the implementation of the “Worldwide harmonized Light duty Test Procedure” (WLTP) and the highly dynamic “Real Driving Emissions” (RDE) tests in Europe, different engineering methodologies from virtual calibration approaches to Engine-in-the-loop (EiL) methods have to be considered to define and calibrate efficient exhaust gas aftertreatment technologies without the availability of prototype vehicles in early project phases. Since different types of testing facilities can be used, the effects of test benches as well as real and virtual vehicle operators have to be determined. Moreover, in order to effectively reduce harmful emissions, the reproducibility of test cycles is essential for an accurate and efficient application of exhaust gas aftertreatment systems and the calibration of internal combustion engines.

Tightening of emission norms necessitate intensified research in the field of emissions reduction. Fuel research opens up a vast area of potential improvement, since combustion behavior and the nature of the combustion products can be heavily influenced by fuel composition. In this paper, the effects of fuel properties on combustion and emissions shall be discussed, based on the study of standard diesel fuel, two types of diesel-like fuels and a kerosene fuel. Investigations were conducted on a single cylinder heavy duty direct-injected diesel engine operating under part-homogeneous combustion in the part-load operating range. For this purpose, a statistical design of experiments method (DOE) was utilized in order to evaluate the influence of each fuel property and, thus, develop a model for all selected fuels. Variation in EGR rates, injection and air patterns have significant effects on the combustion in the fuels under investigation.

The modern engine design process is characterized by shorter development cycles and a reduced number of prototypes. However, simultaneously exhaust after-treatment and emission testing is becoming increasingly more sophisticated. The introduction of predictive real-time simulation tools that represent the entire powertrain can likely contribute to improving the efficiency of the calibration process. Engine models, which are purely based on physical first principles, are usually not capable of real-time applications, especially if the simulation is focused on cold start and warm-up behavior. However, the initial data definition for the ECU using a Hardware-in-the-Loop (HiL)-Simulator requires a model with both real-time capability and sufficient accuracy. The use of artificial intelligence systems becomes necessary, e.g. neural networks. Methods, structures and the realization of a hybrid real-time model are presented in this paper, which combines physical and neural network models.

With rising gasoline prices in the US the need for increasingly fuel efficient powertrain concepts has never been more critical. Evaluation of the market on the other hand shows that the vehicle-buying consumer is unwilling to compromise engine power output for this needed fuel efficiency. Boosted, direct-injected gasoline engines with high specific output and low end torque seem to be the most logical path to satisfying both good part load fuel economy and generous power and torque characteristics. Turbo lag and subsequent lack of torque during transient acceleration (with low initial engine speeds) are characteristics of current turbocharged gasoline engines. These phenomena have prevented successful penetration of these boosted powertrains into the marketplace. Larger displacement, naturally aspirated gasoline engines have been the preferred choice.

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.

Fuel economy improvement of Class 8 long-haul trucks has been a constant topic of discussion in the commercial vehicle industry due to the significant potential it offers in reducing GHG emissions and operational costs. Among the different vehicle categories in on-road transportation, Class 8 long-haul trucks are a significant contributor to overall GHG emissions. Furthermore, with the upcoming 2027 GHG emission and low-NOx regulations, advanced powertrain technologies will be needed to meet these stringent standards. Connectivity-based powertrain optimization is one such technology that many fleets are adopting to achieve significant fuel savings at a relatively lower technology cost. With advancements in vehicle connectivity technologies for onboard computing and sensing, the full potential of connected vehicles in reducing fuel consumption can be realized through V2X (Vehicle-to-Everything) communication.

Electrification of heavy-duty trucks has received significant attention in the past year as a result of future regulations in some states. For example, California will require a certain percentage of tractor trailers, delivery trucks and vans sold to be zero emission by 2035. However, the relatively low energy density of batteries in comparison to diesel fuel, as well as the operating profiles of heavy-duty trucks, make the application of electrified powertrain in these applications more challenging. Heavy-duty vehicles can be broadly classified into two main categories; long-haul tractors and vocational vehicles. Long-haul tractors offer limited benefit from electrification due to the majority of operation occurring at constant cruise speeds, long range requirements and the high efficiency provided by the diesel engine.

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.

In order to allow continued production of the AM General Optimizer 6500 during MY 2007 through 2010 this IDI engine (Indirect Injection - swirl chamber) requires sophisticated aftertreatment controls while maintaining its fuel economy and durability. The main purpose of the development program was to retain the relatively inexpensive and simple base engine with distributor pump and waste-gated turbocharger, while adding hardware and software components that allow achievement of the phase-in emission standards for 2007 through 2010. The aftertreatment system consists of Diesel Oxidation Catalyst (DOC), NOx Adsorber Catalyst (or DeNOx Trap - DNT) and Diesel Particle Filter (DPF). In addition to the base hardware, an intake air throttle valve and an in-exhaust fuel injector were installed. The presented work will document the development process for a 2004 certified 6.5 l IDI heavy-duty diesel engine to comply with the 2007 heavy-duty emission standards.

Increasing fuel costs, the need to reduce dependence on foreign oil as well as the high efficiency and the desire for superior durability have caused the diesel engine to again become a prime target for light-duty vehicle applications in the United States. In support of this the U.S. Department of Energy (DOE) has engaged in a test project under the Advanced Petroleum Based Fuels-Diesel Emission Control (APBF-DEC) activity to develop a passenger car with the capability to demonstrate compliance with Tier 2 Bin 5 emission targets with a fresh emission control catalyst system. In order to achieve this goal, a prototype engine was installed in a passenger car and optimized to provide the lowest practical level of engine-out emissions.

Beginning in 2010, implementation of on-board diagnostics (OBD) is mandatory for all the heavy-duty engine applications in the United States. The task of developing OBD strategies and calibrating them is a challenging one. The process involves a strong interdependency on base engine emissions, controls and regulations. On top of that the strategies developed as a result of the regulatory requirements need to go through a stringent and time-intensive process of software implementation and integration. The recent increasing demands to minimize the development process have been pushing the envelope on the methodologies used in developing the strategies and the calibration for robust monitoring. The goal of this paper is to provide a concise overview of a process utilized to help the development, testing and calibration of the OBD strategies on a 2010 model year heavy-duty diesel engine.