Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Cues and the optimal timing of activities under environmental changes

Organisms time activities by using environmental cues to forecast the future availability of important resources. Presently, there is limited understanding of the relationships between cues and optimal timing, and especially about how this relationship will be affected by environmental changes. We develop a general model to explore the relation between a cue and the optimal timing of an important life history activity. The model quantifies the fitness loss for organisms failing to time behaviours optimally. We decompose the immediate change in fitness resulting from environmental changes into a component that is due to changes in the predictive power of the cue and a component that derives from the mismatch of the old response to the cue to the new environmental conditions. Our results show that consequences may range from negative, neutral to positive and are highly dependent on how cue and optimal timing and their relation are specifically affected by environmental changes.

Finding the optimal temporal partitioning of video sequences

The existing techniques for shot partitioning either process each shot boundary independently or proceed sequentially. The sequential process assumes the last shot boundary is correctly detected and utilizes the shot length distribution to adapt the threshold for detecting the next boundary. These techniques are only locally optimal and suffer from the strong assumption about the correct detection of the last boundary. Addressing these fundamental issues, in this paper, we aim to find the global optimal shot partitioning by utilizing Bayesian principles to model the probability of a particular video partition being the shot partition. A computationally efficient algorithm based on Dynamic Programming is then formulated. The experimental results on a large movie set show that our algorithm performs consistently better than the best adaptive-thresholding technique commonly used for the task.

Optimal communication amongst team members

We present a formal framework based on the theory of game with incomplete information [5] for modelling the coordination and communication problem among team of collaborative agents, and define what it means by optimal communication in this setting. Although computing an optimal communication strategy for the team is hard in general, we illustrate with an example of collaborative negotiation and meeting scheduling that computation can be substantially reduced when domain dependent assumptions are introduced.

What is the optimal level of population alcohol consumption for chronic disease prevention in England? Modelling the impact of changes in average consumption levels

Objective To estimate the impact of achieving alternative average population alcohol consumption levels on chronic disease mortality in England.

Design A macro-simulation model was built to simultaneously estimate the number of deaths from coronary heart disease, stroke, hypertensive disease, diabetes, liver cirrhosis, epilepsy and five cancers that would be averted or delayed annually as a result of changes in alcohol consumption among English adults. Counterfactual scenarios assessed the impact on alcohol-related mortalities of changing (1) the median alcohol consumption of drinkers and (2) the percentage of non-drinkers.

Data sources Risk relationships were drawn from published meta-analyses. Age- and sex-specific distributions of alcohol consumption (grams per day) for the English population in 2006 were drawn from the General Household Survey 2006, and age-, sex- and cause-specific mortality data for 2006 were provided by the Office for National Statistics.

Results The optimum median consumption level for drinkers in the model was 5 g/day (about half a unit), which would avert or delay 4579 (2544 to 6590) deaths per year. Approximately equal numbers of deaths from cancers and liver disease would be delayed or averted (∼2800 for each), while there was a small increase in cardiovascular mortality. The model showed no benefit in terms of reduced mortality when the proportion of non-drinkers in the population was increased.

Conclusions Current government recommendations for alcohol consumption are well above the level likely to minimise chronic disease. Public health targets should aim for a reduction in population alcohol consumption in order to reduce chronic disease mortality.

Optimal algorithm for a mobile intelligent gas detection device

This thesis is based on the development of a gas detection device that can be mounted on a mobile robotic platform. The focus was on development of the A.I recognition algorithm with an array of sensors to detect trace amounts of explosive and volatile gases in the environments it is exposed to.

Congestion and optimal immigration policy

This paper presents a model to explain the stylized fact that many countries have a low ratio of migrants in their population while some countries have a high ratio of migrants. Immigration improves the income of the domestic residents, but migrants also increase the congestion of public services. If migrants are unskilled and therefore pay low taxes, and the government does not limit access to these services, then the welfare of the domestic residents decreases with the number of migrants. Visa auctions can lower the cost of immigration control and substitute legal migrants for illegal migrants. If the government decides to limit the access of migrants to public services, immigration control becomes unnecessary and the optimal number of migrants can be very large.

Optimal sensor placement in range based localization for linear arrays

This paper investigates the linear separation requirements for range sensors in order to achieve the optimal performance in estimating the position of a target from multiple and typically noisy sensor measurements. We analyze the sensor-target geometry in terms of the Cramer-Rao inequality and the corresponding Fisher information matrix, in order to characterize localization performance with respect to the linear special distribution.