Abstract:To improve the use of lithium-ion batteries in electric vehicle (EV) applications, evaluations and comparisons of different equivalent circuit models are presented in this paper. Based on an analysis of the traditional lithium-ion battery equivalent circuit models such as the Rint, RC, Thevenin and PNGV models, an improved Thevenin model, named dual polarization (DP) model, is put forward by adding an extra RC to simulate the electrochemical polarization and concentration polarization separately. The model parameters are identified with a genetic algorithm, which is used to find the optimal time constant of the model, and the experimental data from a Hybrid Pulse Power Characterization (HPPC) test on a LiMn 2 O 4 battery module. Evaluations on the five models are carried out from the point of view of the dynamic performance and the state of charge (SoC) estimation. The dynamic performances of the five models are obtained by conducting the Dynamic Stress Test (DST) and the accuracy of SoC estimation with the Robust Extended Kalman Filter (REKF) approach is determined by performing a Federal Urban Driving Schedules (FUDS) experiment. By comparison, the DP model has the best dynamic performance and provides the most accurate SoC estimation. Finally, sensitivity of the different SoC initial values is investigated based on the accuracy of SoC estimation with the REKF approach based on the DP model. It is clear that the errors resulting from the SoC initial value are significantly reduced and the true SoC is convergent within an acceptable error. OPEN ACCESSEnergies 2011, 4 583

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Abstract:To explore the problems associated with applying dynamic programming (DP) in the energy management strategies of plug-in hybrid electric vehicles (PHEVs), a plug-in hybrid bus powertrain is introduced and its dynamic control model is constructed. The numerical issues, including the discretization resolution of the relevant variables and the boundary issue of their feasible regions, were considered when implementing DP to solve the optimal control problem of PHEVs. The tradeoff between the optimization accuracy when using the DP algorithm and the computational burden was systematically investigated. As a result of overcoming the numerical issues, the DP-based approach has the potential to improve the fuel-savings potential of PHEVs. The results from comparing the DP-based strategy and the traditional control strategy indicate that there is an approximately 20% improvement in fuel economy.

Detection and monitoring of esophageal cancer severity require an imaging technique sensitive enough to detect early pathological changes in the esophagus and capable of analyzing the esophagus over 360 °in a non‐invasive manner. Optoacoustic endoscopy (COE) has been shown to resolve superficial vascular structure of the esophageal lumen in rats and rabbits using catheter‐type probes. Although these systems can work well in small animals, they are unsuitable for larger lumens with thicker walls as required for human esophageal screening, due to their lack of position stability along the full organ circumference, sub‐optimal acoustic coupling and limited signal‐to‐noise ratio (SNR). In this work, we introduce a novel capsule COE system that provides high‐quality 360° images of the entire lumen, specifically designed for typical dimensions of human esophagus. The pill‐shaped encapsulated probe consists of a novel and highly sensitive ultrasound transducer fitted with an integrated miniature pre‐amplifier, which increases SNR of 10 dB by minimizing artifacts during signal transmission compared to the configuration without the preamplifier. The scanner rotates helically around the central axis of the probe to capture three‐dimensional images with uniform quality. We demonstrate for the first time ex vivo volumetric vascular network images to a depth of 2 mm in swine esophageal lining using COE. Vascular information can be resolved within the mucosa and submucosa layers as confirmed by histology of samples stained with hematoxylin and eosin and with antibody against vascular marker CD31. COE creates new opportunities for optoacoustic screening of esophageal cancer in humans.

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Plug-in hybrid electric vehicles (PHEVs) have a larger battery and can replace a certain amount of conventional fossil fuels with grid electricity, which differs from the traditional hybrid electric vehicles (HEVs). The application of the onboard electrical energy significantly influences the energy utilization efficiency and thus impacts the fuel economy. In this paper, the basic PHEV operation modes are defined as pure electric driving (PED), hybrid driving charge depleting (HDCD) and hybrid driving charge sustaining (HDCS) based on the battery state of charge (SoC) profile. For a plug-in hybrid electric bus (PHEB), three different energy management strategies, which are combined with two or three of the basic operation modes, are put forward and comparatively examined based on simulation models. If some trip information can be approximately known in advance such as the trip distance and the mean power demand, the PED + HDCD + HDCS strategy comprised optimally of the PED mode, the HDCD mode and the HDCS mode would be the best energy management strategy.

We propose the implementation of hybrid optical and acoustic resolution optoacoustic endoscopy. Laser light is transmitted to tissue by two types of illumination for achieving optical and acoustic resolution imaging. A 20 MHz ultrasound detector is used for recording optoacoustic signals. The endoscopy probe attains a 3.6 mm diameter and is fully encapsulated into a catheter system. We validate the imaging performance of the hybrid endoscope on phantoms and ex vivo, and discuss the necessity for the extended resolution and depth range of endoscopy achieved.

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