Designing and testing an advanced pneumatic braking system for heavy vehicles

Heavy goods vehicles exhibit poor braking performance in emergency situations when compared to other vehicles. Part of the problem is caused by sluggish pneumatic brake actuators, which limit the control bandwidth of their antilock braking systems. In addition, heuristic control algorithms are used that do not achieve the maximum braking force throughout the stop. In this article, a novel braking system is introduced for pneumatically braked heavy goods vehicles. The conventional brake actuators are improved by placing high-bandwidth, binary-actuated valves directly on the brake chambers. A made-for-purpose valve is described. It achieves a switching delay of 3-4 ms in tests, which is an order of magnitude faster than solenoids in conventional anti-lock braking systems. The heuristic braking control algorithms are replaced with a wheel slip regulator based on sliding mode control. The combined actuator and slip controller are shown to reduce stopping distances on smooth and rough, high friction (μ = 0.9) surfaces by 10% and 27% respectively in hardware-in-the-loop tests compared with conventional ABS. On smooth and rough, low friction (μ = 0.2) surfaces, stopping distances are reduced by 23% and 25%, respectively. Moreover, the overall air reservoir size required on a heavy goods vehicle is governed by its air usage during an anti-lock braking stop on a low friction, smooth surface. The 37% reduction in air usage observed in hardware-in-the-loop tests on this surface therefore represents the potential reduction in reservoir size that could be achieved by the new system. © 2012 IMechE.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

Environmental evaluation of localising production as a strategy for sustainable development: a case study of two consumer goods in Jamaica

The objective of this study was to compare the life-cycle environmental impacts of changed production structures for two consumer goods (high-density polyethylene (HDPE) shopping bags and beds) in Jamaica. A scenario technique was used to construct three alternative production structures for each product; each scenario reflecting an increase in local production in Jamaica which depended on an increased supply of input materials which may be sourced: (1) externally from overseas suppliers, (2) from post-consumer recycling, and (3) locally on the island of Jamaica. These three constructed scenarios were then compared to the existing supply chain or reference scenarios of the products. The results showed that for both case products the recycling scenario was most preferable for localising production, resulting in the lowest environmental impact. This was because the production of raw materials accounted for the largest effect on total environmental impact. As such, the most immediate environmental improvements were realised by lowering the production of virgin materials. © 2007 Elsevier Ltd. All rights reserved.