Hybrid propulsion systems are one of the critical technologies on the roadmap to future ultra-efficient trucks. While there is a significant body of work related to hybrid passenger cars and light commercial trucks, there are many open issues related to hybridisation of heavier trucks intended for both on- and off-road use. This work addresses those questions through a systematic analysis of the proposed parallel hydraulic hybrid powertrain for the Family of Medium Tactical Vehicles (FMTV). A representative duty cycle for the FMTV is generated based on information about the typical vehicle mission. A methodology for sequential optimisation of hybrid propulsion and power management systems is applied to a hydraulic hybrid configuration with post-transmission motor location. This analysis is critical in evaluating the fuel economy and mobility potential of the hybrid propulsion system, as well as enhancing our understanding of the phenomena leading to predicted fuel economy values.

With the aim of increasing the efficiency of maintenance and fuel usage in airplanes, structural health monitoring (SHM) of critical composite structures is increasingly expected and required. The optimized usage of this concept is subject of intensive work in the framework of the EU COST Action CA18203 “Optimising Design for Inspection” (ODIN). In this context, a thorough review of a broad range of energy harvesting (EH) technologies to be potentially used as power sources for the acoustic emission and guided wave propagation sensors of the considered SHM systems, as well as for the respective data elaboration and wireless communication modules, is provided in this work. EH devices based on the usage of kinetic energy, thermal gradients, solar radiation, airflow, and other viable energy sources, proposed so far in the literature, are thus described with a critical review of the respective specific power levels, of their potential placement on airplanes, as well as the consequently necessary power management architectures. The guidelines provided for the selection of the most appropriate EH and power management technologies create the preconditions to develop a new class of autonomous sensor nodes for the in-process, non-destructive SHM of airplane components.

The analytical target cascading process is applied to the redesign of a U.S. class VI truck. Necessary simulation and analysis models for predicting vehicle dynamics, powertrain, and suspension behaviour are developed. Vehicle design targets that include improved fuel economy, ride quality, driveability, and performance metrics are translated into system design specifications, and a consistent final design is obtained. Trade-offs between conflicting targets are identified. The study illustrates how the analytical target cascading process can reduce vehicle design cycle time while ensuring physical prototype matching, and how costly design iterations late in the development process can be avoided.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

A dynamic system model is proper for a particular application if it achieves the accuracy required by the application with minimal complexity. Because model complexity often—but not always—correlates inversely with simulation speed, a proper model is often alternatively defined as one balancing accuracy and speed. Such balancing is crucial for applications requiring both model accuracy and speed, such as system optimization and hardware-in-the-loop simulation. Furthermore, the simplicity of proper models conduces to control system analysis and design, particularly given the ease with which lower-order controllers can be implemented compared to higher-order ones. The literature presents many algorithms for deducing proper models from simpler ones or reducing complex models until they become proper. This paper presents a broad survey of the proper modeling literature. To simplify the presentation, the algorithms are classified into frequency, projection, optimization, and energy based, based on the metrics they use for obtaining proper models. The basic mechanics, properties, advantages, and limitations of the methods are discussed, along with the relationships between different techniques, with the intention of helping the modeler to identify the most suitable proper modeling method for a given application.

The main contributions of this paper are the development of a forward-looking hybrid vehicle simulation tool, and its application to the design of a power management control algorithm. The hybrid electric vehicle simulation tool (HE-VESIM) was developed at the Automotive Research Center of the University of Michigan to study the potential fuel economy and emission benefits of the parallel hybrid propulsion system for a medium truck. The fundamental architecture of the feed-forward simulation tool and the dynamic equations of its sub-system modules are first described. A power management control algorithm is then designed and evaluated, which is based on mimicking the behaviour of a dynamic-programming optimisation scheme. Simulation results over an urban driving cycle demonstrate that the hybrid control algorithm is able to improve vehicle fuel economy significantly, compared with the original vehicle, powered only by a diesel engine.