On the Complexity of an Unregulated Traffic Crossing

The steady development of motor vehicle technology will enable cars of the near future to assume an ever increasing role in the decision making and control of the vehicle itself. In the foreseeable future, cars will have the ability to communicate with one another in order to better coordinate their motion. This motivates a number of interesting algorithmic problems. One of the most challenging aspects of traffic coordination involves traffic intersections. In this paper we consider two formulations of a simple and fundamental geometric optimization problem involving coordinating the motion of vehicles through an intersection. We are given a set of $n$ vehicles in the plane, each modeled as a unit length line segment that moves monotonically, either horizontally or vertically, subject to a maximum speed limit. Each vehicle is described by a start and goal position and a start time and deadline. The question is whether, subject to the speed limit, there exists a collision-free motion plan so that each vehicle travels from its start position to its goal position prior to its deadline. We present three results. We begin by showing that this problem is NP-complete with a reduction from 3-SAT. Second, we consider a constrained version in which cars traveling horizontally can alter their speeds while cars traveling vertically cannot. We present a simple algorithm that solves this problem in $O(n \log n)$ time. Finally, we provide a solution to the discrete version of the problem and prove its asymptotic optimality in terms of the maximum delay of a vehicle

Battery state-of-charge estimation using machine learning analysis of ultrasonic signatures

The potential of acoustic signatures to be used for State-of-Charge (SoC) estimation is demonstrated using artificial neural network regression models. This approach represents a streamlined method of processing the entire acoustic waveform instead of performing manual, and often arbitrary, waveform peak selection. For applications where computational economy is prioritised, simple metrics of statistical significance are used to formally identify the most informative waveform features. These alone can be exploited for SoC inference. It is further shown that signal portions representing both early and late interfacial reflections can correlate highly with the SoC and be of predictive value, challenging the more common peak selection methods which focus on the latter. Although later echoes represent greater through-thickness coverage, and are intuitively more information-rich, their presence is not guaranteed. Holistic waveform treatment offers a more robust approach to correlating acoustic signatures to electrochemical states. It is further demonstrated that transformation into the frequency domain can reduce the dimensionality of the problem significantly, while also improving the estimation accuracy. Most importantly, it is shown that acoustic signatures can be used as sole model inputs to produce highly accurate SoC estimates, without any complementary voltage information. This makes the method suitable for applications where redundancy and diversification of SoC estimation approaches is needed. Data is obtained experimentally from a 210 mAh LiCoO2/graphite pouch cell. Mean estimation errors as low as 0.75% are achieved on a SoC scale of 0–100%

The effect of nutrition and body condition of triplet-bearing ewes during late pregnancy on the behaviour of ewes and lambs

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Confirmatory factor analysis of the Test of Performance Strategies (TOPS) among adolescent athletes

The aim of the present study was to examine the factorial validity of the Test of Performance Strategies (TOPS; Thomas et al., 1999) among adolescent athletes using confirmatory factor analysis. The TOPS was designed to assess eight psychological strategies used in competition (i.e. activation, automaticity, emotional control, goal-setting, imagery, negative thinking, relaxation and self-talk,) and eight used in practice (the same strategies except negative thinking is replaced by attentional control). National-level athletes (n = 584) completed the 64-item TOPS during training camps. Fit indices provided partial support for the overall measurement model for the competition items (robust comparative fit index = 0.92, Tucker-Lewis index = 0.88, root mean square error of approximation = 0.05) but minimal support for the training items (robust comparative fit index = 0.86, Tucker-Lewis index = 0.81, root mean square error of approximation = 0.06). For the competition items, the automaticity, goal-setting, relaxation and self-talk scales showed good fit, whereas the activation, emotional control, imagery and negative thinking scales did not. For the practice items, the attentional control, emotional control, goal-setting, imagery and self-talk scales showed good fit, whereas the activation, automaticity and relaxation scales did not. Overall, it appears that the factorial validity of the TOPS for use with adolescents is questionable at present and further development is required

Visualising coke-induced degradation of catalysts used for CO2-reforming of methane with X-ray nano-computed tomography

The switch from a carbon-based to a hydrogen-based economy requires environmentally friendly methods for hydrogen production. CO2-reforming of methane promises to be a greener alternative to steam-methane reforming, which accounts for the majority of hydrogen production today. For this dry process to become industrially competitive, challenges such as catalyst deactivation and degradation through coke formation must be better understood and ultimately overcome. While bulk characterisation methods provide a wealth of useful information about the carbon formed during coking, spatially resolved techniques are required to understand the type and extent of degradation of supported catalyst particles themselves under coking conditions. Here, lab-based X-ray nano-computed tomography, in conjunction with a range of complementary techniques, is utilised to understand the effects of the nickel-to-cobalt ratio on the degradation of individual supported catalyst particles. Findings suggest that a bimetallic system greatly outperforms monometallic catalysts, with the ratio between nickel and cobalt having a significant impact on the type and quantity of the carbon formed and on the extent of supported catalyst breakdown

Failure and hazard characterisation of high-power lithium-ion cells via coupling accelerating rate calorimetry with in-line mass spectrometry, statistical and post-mortem analyses

Lithium-ion battery safety continues to be an obstacle for electric vehicles and electrified aerospace. Cell failure must be studied in order to engineer improved cells, battery packs and management systems. In this work, the thermal runaway of commercially available, high-power cells is studied, to understand the optimal areas to develop mitigation strategies. Accelerating rate calorimetry is coupled with mass spectrometry to examine self-heating and the corresponding evolution of gases. A statistical analysis of cell failure is then conducted, combined with post-mortem examinations. The methodology forms a robust assessment of cell failure, including the expected worst- and best-cases, and the associated real-world hazards. Cells produce a highly flammable, toxic gas mixture which varies over the course of self-heating. Failure also produces particulate matter which poses a severe health hazard. Critically, the onset of self-heating is detectable more than a day in advance of full thermal runaway. Likewise, voltage drops and leaks are detectable prior to venting, highlighting the potential for highly effective early onset detection. Furthermore, the behaviour of the cap during thermal runaway indicates that ejection of material likely reduces the chance of thermal runaway propagation to neighbouring cells. These findings also emphasise that research must be conducted safely

In Situ Ultrasound Acoustic Measurement of the Lithium-Ion Battery Electrode Drying Process

The electrode drying process is a crucial step in the manufacturing of lithium-ion batteries and can significantly affect the performance of an electrode once stacked in a cell. High drying rates may induce binder migration, which is largely governed by the temperature. Additionally, elevated drying rates will result in a heterogeneous distribution of the soluble and dispersed binder throughout the electrode, potentially accumulating at the surface. The optimized drying rate during the electrode manufacturing process will promote balanced homogeneous binder distribution throughout the electrode film; however, there is a need to develop more informative in situ metrologies to better understand the dynamics of the drying process. Here, ultrasound acoustic-based techniques were developed as an in situ tool to study the electrode drying process using NMC622-based cathodes and graphite-based anodes. The drying dynamic evolution for cathodes dried at 40 and 60 °C and anodes dried at 60 °C were investigated, with the attenuation of the reflective acoustic signals used to indicate the evolution of the physical properties of the electrode-coating film. The drying-induced acoustic signal shifts were discussed critically and correlated to the reported three-stage drying mechanism, offering a new mode for investigating the dynamic drying process. Ultrasound acoustic-based measurements have been successfully shown to be a novel in situ metrology to acquire dynamic drying profiles of lithium-ion battery electrodes. The findings would potentially fulfil the research gaps between acquiring dynamic data continuously for a drying mechanism study and the existing research metrology, as most of the published drying mechanism research studies are based on simulated drying processes. It shows great potential for further development and understanding of the drying process to achieve a more controllable electrode manufacturing process

Correlative electrochemical acoustic time-of-flight spectroscopy and X-ray imaging to monitor the performance of single-crystal and polycrystalline NMC811/Gr lithium-ion batteries

LiNixMnyCozO2 (NMC) electrodes typically consist of anisotropic single-crystal primary particles aggregated to form polycrystalline secondary particles. Electrodes composed of polycrystalline NMC particles have a comparatively high gravimetric capacity and good rate capabilities but do not perform as well as single crystal equivalents in terms of volumetric energy density and cycling stability. This has prompted research into well-dispersed single-crystalline NMC products as an alternative solution for high-energy-density batteries. Here, for the first time known to the authors, electrochemical acoustic time-of-flight (EA-ToF) spectroscopy has been shown to be effective in distinguishing between Li-ion batteries composed of either single-crystal NMC811 (SC-NMC811) or polycrystalline NMC811 (PC-NMC811) electrodes. Cells composed of PC-NMC811 electrodes had a higher degree of gas evolution compared to cells containing SC-NMC811 electrodes. Cells composed of PC-NMC811 electrodes also underwent larger changes in the acoustic signal's time-of-flight (ToF) during constant current cycling at a range of C-rates indicating expansion, fracture or dislocation of the reflective interfaces inside the cell. In addition, X-ray computed tomography (X-ray CT) has been used to confirm significant morphological differences between SC-NMC811 electrodes and PC-NMC811 electrodes including the electrode's particle size distribution (PSD) that is suggested to have an effect on acoustic signal interaction with these electrode interfaces