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Control Allocation for Multi-Axle Hub Motor Driven Land Vehicles

SAE International Journal of Alternative Powertrains

US Army, TARDEC-Amandeep Singh
Clemson University-Qian Wang, Beshah Ayalew
  • Journal Article
  • 2016-01-1670
Published 2016-04-05 by SAE International in United States
This paper outlines a real-time hierarchical control allocation algorithm for multi-axle land vehicles with independent hub motor wheel drives. At the top level, the driver’s input such as pedal position or steering wheel position are interpreted into desired global state responses based on a reference model. Then, a locally linearized rigid body model is used to design a linear quadratic regulator that generates the desired global control efforts, i.e., the total tire forces and moments required track the desired state responses. At the lower level, an optimal control allocation algorithm coordinates the motor torques in such a manner that the forces generated at tire-road contacts produce the desired global control efforts under some physical constraints of the actuation and the tire/wheel dynamics. The performance of the proposed control system design is verified via simulation analysis of a 3-axle heavy vehicle with independent hub-motor drives.
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Design under Uncertainty using a Combination of Evidence Theory and a Bayesian Approach

SAE International Journal of Materials and Manufacturing

US Army, TARDEC-Clifton Ellis
Oakland University-Jun Zhou, Zissimos P. Mourelatos
  • Journal Article
  • 2008-01-0377
Published 2008-04-14 by SAE International in United States
Early in the engineering design cycle, it is difficult to quantify product reliability due to insufficient data or information to model uncertainties. Probability theory can not be therefore, used. Design decisions are usually based on fuzzy information which is imprecise and incomplete. Various design methods such as Possibility-Based Design Optimization (PBDO) and Evidence-Based Design Optimization (EBDO) have been developed to systematically treat design with non-probabilistic uncertainties. In practical engineering applications, information regarding the uncertain variables and parameters may exist in the form of sample points, and uncertainties with sufficient and insufficient information may exist simultaneously. Most of the existing optimal design methods under uncertainty can not handle this form of incomplete information. They have to either discard some valuable information or postulate the existence of additional information. In this paper, a design optimization method is proposed based on evidence theory, which can handle a mixture of epistemic and random uncertainties. Instead of using “expert” opinions to form the basic probability assignment, a Bayesian approach is used with a limited number of sample points. A pressure…
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Transient Fluid Flow and Heat Transfer in the EGR Cooler

SAE International Journal of Engines

US Army, TARDEC-Walter Bryzik
Wayne State University-Radu Florea, Dinu Taraza, Naeim A. Henein
  • Journal Article
  • 2008-01-0956
Published 2008-04-14 by SAE International in United States
EGR is a proven technology used to reduce NOx formation in both compression and spark ignition engines by reducing the combustion temperature. In order to further increase its efficiency the recirculated gases are subjected to cooling. However, this leads to a higher load on the cooling system of the engine, thus requiring a larger radiator. In the case of turbocharged engines the large variations of the pressures, especially in the exhaust manifold, produce a highly pulsating EGR flow leading to non-steady-state heat transfer in the cooler. The current research presents a method of determining the pulsating flow field and the instantaneous heat transfer in the EGR heat exchanger. The processes are simulated using the CFD code FIRE (AVL) and the results are subjected to validation by comparison with the experimental data obtained on a 2.5 liter, four cylinder, common rail and turbocharged diesel engine.
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