Design Under Uncertainty and Assessment of Performance Reliability of a Dual-Use Medium Truck with Hydraulic-Hybrid Powertrain and Fuel Cell Auxiliary Power Unit

Abstract

Medium trucks constitute a large market segment of the commercial transportation sector, and are also used widely for military tactical operations. Recent technological advances in hybrid powertrains and fuel cell auxiliary power units have enabled design alternatives that can improve fuel economy and reduce emissions dramatically. However, deterministic design optimization of these configurations may yield designs that are optimal with respect to performance but raise concerns regarding the reliability of achieving that performance over lifetime. In this article we identify and quantify uncertainties due to modeling approximations or incomplete information. We then model their propagation using Monte Carlo simulation and perform sensitivity analysis to isolate statistically significant uncertainties. Finally, we formulate and solve a series of reliabilitybased optimization problems and quantify tradeoffs between optimality and reliability. The most relevant design parameters of the diesel engine, fuel cell, driveline and vehicle are considered. The results demonstrate the necessity for addressing uncertainty to make valid assessments and design decisions.

Comparison of early-stage design methods for a two-mode hybrid electric vehicle

“…Component models with higher fidelity are replacing off-the-shelf selection or simple scaling of baseline designs [6]. Further, increasingly advanced optimization techniques are employed for design [6][7][8]. A common practice is to combine global and local search methods in a sequential way.…”

Engine-in-the-Loop Testing for Evaluating Hybrid Propulsion Concepts and Transient Emissions - HMMWV Case Study

“…The fuel economy potential of selected hybrid electric and hydraulic hybrid configurations has been evaluated by Lin et al in [6, 19 and 20]. Hierarchical methodologies for optimally designing a complex vehicle system are explored in [8], while [21] considers design under uncertainty. Techniques for optimal power management are addressed in [19,22].…”

Design Optimization and Reliability Estimation with Incomplete Uncertainty Information

“…Therefore, we use the optimal hydraulic system design computed in a previous deterministic optimization study. Four engine design variables are selected to represent the engine design, and four parameters with the highest impact on the truck's fuel economy and performance are identified [5]. The bounds of the design variables and the nominal values of the design parameters are summarized in Table 1.…”

“…In this article we assess the impact of incomplete information on design decisions. Specifically, let us assume that the knowledge or information used in [5] to infer normally distributed random variables was insufficient, and let us hypothesize that they are all, say, uniformly distributed. To keep things relatively comparable, let us define the uniform distribution parameters of the random variables such that the ranges of attainable values correspond to the ranges of the normally distributed variables.…”

“…In [5], we considered the case where all random variables are assumed to be normally distributed. The standard deviations of the random design variables and the means and standard deviations of the random design parameters were identified with the help of the simulation model developers, and are summarized here in Tables 2 and 3.…”