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AUTOSAR is finding its way into the automotive industry. European automotive manufacturing companies were the early adopters defining and promoting AUTOSAR standard. One of the main AUTOSAR goals is to improve containment of product and process complexity and risk. Increased scalability and flexibility to integrate and transfer functions is another important goal of AUTOSAR. Working with different suppliers and vendors and respect their confidentiality makes the process of application software development even more complex. Presented in this paper is a creative way of utilizing AUTOSAR to overcome the integration challenges in a multi-party object code based software integration. The run time environment (RTE) files for the application software are generated through a set of scripts to automate the process for consecutive releases. The low level device drivers are configured by one supplier and are being used by another supplier through a set of AUTOSAR client-server operation calls.

Low temperature combustion through in-cylinder blending of gasoline and diesel offers the potential to improve engine efficiency while yielding low engine-out soot and NOx emissions. This investigation utilized 3-D KIVA combustion simulation to guide the development of viable dual-fuel low temperature combustion strategies for heavy-duty applications. Model-based combustion optimization was performed at 1531rpm and 11 bar BMEP for a 12.4 L heavy-duty truck engine. Various engine operating parameters were explored through design of experiments (DoE). The parameters involved in the optimization process included compression ratio, air-fuel ratio, EGR rate, gasoline-to-diesel ratio, and diesel injection strategy (i.e., single-diesel injection vs. two-diesel injections, diesel injection timings, and the split ratio between two-diesel injections). Optimal cases showed near zero soot emissions and very low NOx emissions.

Tighter emission norms and fuel economy demands have prompted diesel engine manufacturers to implement Aftertreatment systems for both light-duty and heavy-duty diesel applications. After implementing Diesel Particulate Filter (DPF) technology to comply with 2007 Environmental Protection Agency (EPA) emissions regulations, OEMs have turned their attention towards NOx reductions with SCR technology. Current SCR technologies include liquid based Urea injection into the exhaust stream for NOx reductions and Solid Ammonia Storage and Delivery System (ASDS) which involves dosing gaseous Ammonia. Irrespective of the technology in use, the estimation of engine-out NOx emissions plays a vital role in reductant (Urea/Ammonia) dosing estimation via feed-back controls. The general method for determination of the engine-out NOx emissions is to use commonly available NOx emission sensors (NOx Sensors). However, NOx sensors have their own drawbacks.

The TOP TIERTM Diesel fuel standard was first established in 2017 to promote better fuel quality in marketplace to address the needs of diesel engines. It provides an automotive recommended fuel specification to be used in tandem with regional diesel fuel specifications or regulations. This fuel standard was developed by TOP TIERTM Diesel Original Equipment Manufacturer (OEM) sponsors made up of representatives of diesel auto and engine manufacturers. This performance specification developed after two years of discussions with various stakeholders such as individual OEMs, members of Truck and Engine Manufacturers Association (EMA), fuel additive companies, as well as fuel producers and marketers. This paper reviews the major aspects of the development of the TOP TIERTM Diesel program including implementation and market adoption challenges.

Efficient thermal management of an engine cooling system and its surrounding components has been one of the most frequently visited topics in automotive industry. Especially, modern diesel truck engines have to deal with more heat rejection than ever to meet the rigorous emission and efficiency standards. As the maximum heat dissipated by a cooling system is limited to available inlet area to radiator, which is constrained by cab configuration, it is crucial to maximize the cooling airflow availability under given conditions. To be able to do so means to avoid additional development cost accompanying an altered cab configuration. At the same time, truck manufacturers have to deal with reduced product life cycles and develop reliable products economically.

As vehicle emissions regulations become increasingly stringent, there is a growing need to accurately model aftertreatment systems to aid in the development of ultra-low NOx vehicles. Common solutions to this problem include the development of complex chemical models or expansive neural networks. This paper aims to present the development process of a simpler Selective Catalytic Reduction (SCR) conversion efficiency Simulink model for the purposes of modeling tail pipe NOx emission levels based on various inputs, temperature shifts and SCR locations, arrangements and/or sizes in the system. The main objective is to utilize this model to predict tail pipe NOx emissions of the EPA Federal Test Procedures for heavy-duty vehicles. The model presented within is focused exclusively on heavy-duty application compression ignition engines and their corresponding aftertreatment setups.