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The emergence of tougher environmental legislations and ever increasing demand for increased ride comfort, fuel efficiency, and low emissions have triggered exploration and advances towards more efficient vehicle gearbox technologies. The growing complexity and spatial distribution of such a mechatronic gearbox demands precise timing and coordination of the embedded electronics, integrated sensors and actuators as well as excellent overall reliability. The increased gearbox distributed systems have seen an increased dependence on sensors for feedback control, predominantly relying on hardware redundancy for faults diagnosis. However, the conventional hardware redundancy has disadvantages due to increased costs, weight, volume, power requirements and failure rates. This paper presents a virtual position sensor-based Fault Detection, Isolation and Accommodation (FDIA), which generates an analytical redundancy for comparison against the actual sensor output.

Electro-hydraulic actuated systems are widely used in industrial applications due to high torque density, higher speeds and wide bandwidth operation. However, the complexities and the parametric uncertainties of the hydraulic actuated systems pose challenges in establishing analytical mathematical models. Unlike electro-mechanical and pneumatic systems, the nonlinear dynamics due to dead band, hysteresis, nonlinear pressure flow relations, leakages and friction affects the pressure sensitivity and flow gain by altering the system's transient response, which can introduce asymmetric oscillatory behavior and a lag in the system response. The parametric uncertainties make it imperative to have condition monitoring with in-built diagnostics capability. Timely faults detection and isolation can help mitigate catastrophic failures. This paper presents a signal-based fault diagnostic scheme for a gearbox hydraulic actuator leakage detection using the wavelet transform.

Commercial vehicle operators and governments around the world are looking for ways to cut down on fuel consumption for economic and environmental reasons. Two main factors affecting the fuel consumption of a vehicle are the drive route and the driver behavior. The drive route can be specified by information such as speed limit, road grade, road curvature, traffic etc. The driver behavior, on the other hand, is difficult to classify and can be responsible for as much as 35% variation in fuel consumption. In this work, nearly 600,000 miles of drive data is utilized to identify driving behaviors that significantly affect fuel consumption. Based on this analysis, driving scenarios and related driver behaviors are identified that result in the most efficient vehicle operation. A driver assistance system is presented in this paper that assists the driver in driving more efficiently by issuing scenario specific advice.

This book provides a broad and comprehensive look at hybrid powertrain technologies for commercial vehicles. It begins with the fundamentals of hybrid powertrain systems, government regulations, and driving cycles, then provides design guidelines and key components of hybrid powertrains for commercial vehicles. It was written for vehicle and component engineers and developers, researchers, students, policymakers, and business executives in the commercial vehicle and transportation industries to help them understand the fundamentals of hybrid powertrain technologies and market requirements for commercial vehicles. It is useful for anyone who designs or is interested in hybrid powertrains and their key components. The term ‘commercial vehicle’ applies to everything from light delivery vehicles to class 8 long haul trucks, buses, and coaches. These vehicles are used for a wide range of duties, including transporting goods or people and infrastructure service.