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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.

Today, automated vehicles mostly rely on ego vehicle sensors such as cameras, radar or LiDAR sensors that are limited in their sensing capability and range. Vehicle-to-everything (V2X) communication has the potential to appropriately complement these sensors and even allow for a cooperative, proactive interaction of vehicles. As such, V2X communication might play a vital role on the way to smart and efficient traffic solutions. In the public funded research project UK Autodrive, we are currently investigating and experimentally evaluating V2X-based applications based on dedicated short range communication (DSRC). Moreover, the novel application intersection priority management (IPM) is part of the research project. IPM aims at automating intersections in such a way that vehicles can pass safely and even more efficiently without the use of traffic lights or signs.

Nowadays, collision avoidance systems (CAS) are an intensive research topic since the majority of all traffic accidents are collisions that are caused due to inattention or unadjusted driving behavior of the driver. Up to date prototypic CAS are based on on-board environmental sensors, such as camera or radar systems, that scan the vehicle's surrounding environment in order to assess the situation's hazardousness. The functionality of the used sensors under varying environmental conditions and the limited sensor covering area require an enormous effort to ensure a reliable detection of obstacles, and thus limit the application of the systems. In order to expand the operating field of such systems, a Galileo-based CAS will be developed within the project ‘Galileo above’ (application centre for ground based traffic).

The efficient operation of powertrain test benches in research and development is strongly influenced by the state of “health” of the functional test object. Hence, the use of Early Damage Detection Systems (EDDS) with Unit Under Test (UUT) monitoring is becoming increasingly popular. An EDDS should primarily avoid total loss of the test object and ensure that damaged parts are not completely destroyed, and can still be inspected. Therefore, any abnormality from the standard test object behavior, such as an exceeding of predefined limits, must be recognized at an early testing time, and must lead to a shutdown of the test bench operation. With sensors mounted on the test object, it is possible to isolate the damage cause in the event of its detection. Advanced EDDS configurations also optimize the predefined limits by learning new shutdown values according to the test object behavior within a very short time.

Electrification is a key enabler to reduce emissions levels and noise in commercial vehicles. With electrification, Batteries are being used in commercial hybrid vehicles like city buses and trucks for kinetic energy recovery, boosting and electric driving. A battery management system monitors and controls multiple components of a battery system like cells, relays, sensors, actuators and high voltage loads to optimize the performance of a battery system. This paper deals with the development of modular control architecture for battery management systems in commercial vehicles. The key technical challenges for software development in commercial vehicles are growing complexity, rising number of functional requirements, safety, variant diversity, software quality requirements and reduced development costs. Software architecture is critical to handle some of these challenges early in the development process.

Upcoming motor vehicle emission regulations, such as California's LEVIII, continue to tighten emission limitations in diesel vehicles. These increasingly challenging emission requirements will be met by improving the combustion process (reducing engine-out emissions), as well as improving the exhaust gas aftertreatment efficiency. Furthermore, intricate On-Board Diagnostics (OBD) systems are required to properly diagnose and meet OBD regulation requirements for complex aftertreatment systems. Under these conditions, current monitoring strategies are unable to guarantee reliable detection of partially failed systems. Additionally, new OBD regulations require aftertreatment systems to be diagnosed as a whole. This paper covers potential OBD strategies for LEVIII aftertreatment concepts with regard to regulation compliance and robustness, while striving to use existing sensor concepts.