Real-Time Energy Management Strategy of a Fuel Cell Electric Vehicle With Global Optimal Learning

[EN] This article proposes a novel energy management strategy (EMS) for a fuel cell electric vehicle (FCEV). The strategy combines the offline optimization and online algorithms to guarantee optimal control, real-time performance, and better robustness in an unknown route. In particular, dynamic programming (DP) is applied in a database with multiple driving cycles to extract the theoretically optimal power split between the battery and fuel cell with a priori knowledge of the driving conditions. The analysis of the obtained results is then used to extract the rules to embed them in a real-time capable fuzzy controller. In this sense, at the expense of certain calibration effort in the offline phase with the DP results, the proposed strategy allows on-board applicability with suboptimal results. The proposed strategy has been tested in several actual driving cycles, and the results show energy savings between 8.48% and 10.71% in comparison to rule-based strategy and energy penalties between 1.04% and 3.37% when compared with the theoretical optimum obtained by DP. In addition, a sensitivity analysis shows that the proposed strategy can be adapted to different vehicle configurations. As the battery capacity increases, the performance can be further improved by 0.15% and 1.66% in conservative and aggressive driving styles, respectively.This work was supported in part by the National Natural Science Foundation of China under Grant 62111530196, in part by the Technology Development Program of Jilin Province under Grant 20210201111GX, and in part by the China Automobile Industry Innovation and Development Joint Fund under Grant U1864206.Hou, S.; Yin, H.; Pla Moreno, B.; Gao, J.; Chen, H. (2023). Real-Time Energy Management Strategy of a Fuel Cell Electric Vehicle With Global Optimal Learning. IEEE Transactions on Transportation Electrification (Online). 9(4):5085-5097. https://doi.org/10.1109/TTE.2023.3238101508550979

Gastroenterologists Reveal More Digestive Symptoms in COVID-19 Patients than Nongastroenterologists in Fever Clinic

The incidence of digestive symptoms may vary depending on doctors’ professional backgrounds when they inquired suspected COVID-19 patients in a fever clinic. We sought to understand the characteristics of inquiries about digestive symptoms by doctors in different specialties; therefore, inquiry records of 2 gastroenterologists and 6 nongastroenterologists were reviewed. We compared the difference in inquiry of digestive symptoms (diarrhea, vomit, distension, anorexia, and abdominal pain) between these two groups among identified COVID-19 patients. And we further compared the difference of digestive symptoms between confirmed patients and suspected cases who excluded from COVID-19. Among 495 confirmed COVID-19 cases (254 cases by gastroenterologists and 241 cases by nongastroenterologists), 22.83% patients experienced various digestive symptoms in the gastroenterologists’ group, while only 4.47% reported digestive symptoms by nongastroenterologists (p<0.0001). Additionally, among initially suspected 611 patients who presented with similar respiratory symptoms inquired by gastroenterologists, confirmed cases presented far more frequency of digestive symptoms than excluded cases (22.8% vs. 3.64%, p<0.0001). Furthermore, confirmed patients reported more percentage of watery diarrhea (56% vs. 36%, p<0.0001) and higher frequent vomit (2.77±0.97 vs. 1.80±0.45 per day, p=0.041) than excluded cases. We concluded that gastroenterologists could detect a greater proportion of gastrointestinal symptoms in COVID-19 patients during fever clinic inquiries. Moreover, confirmed COVID-19 patients are more likely to have higher severity in digestive symptoms than excluded cases. Therefore, physicians in fever clinic should pay more attention to the triage of gastrointestinal symptoms

Modulation of the microbiota across different intestinal segments by Rifaximin in PI-IBS mice

Abstract Background Rifaximin has been increasingly applied in irritable bowel syndrome (IBS) treatment. Whether there were differences in the effects of rifaximin on microbiota from different intestinal segments, especially the small intestine where rifaximin predominantly acted, has not been confirmed. Methods In this study, we used Trichinella spiralis infection to induce post infectious irritable bowel syndrome (PI-IBS) and measured visceral sensitivity of mice by means of abdominal withdrawal reflex (AWR) tests to colorectal distention (CRD). We compared the effects of rifaximin on the composition of ileal, colonic mucosal and fecal microbiota in PI-IBS mice. Results Rifaximin significantly reduced AWR scores and increased pain threshold in PI-IBS mice, and this effect was associated with the change in the relative abundance of ileal mucosal microbiota. Rifaximin could obviously decrease ileum mucosal microbiota alpha diversity assessed by Shannon microbial diversity index. Meanwhile, the analysis of beta diversity and relative abundance of microbiota at phylum, family and genus levels showed that rifaximin could improve the microbiota structure of ileal mucosa. However, for colonic mucosal and fecal microbiota, this effect of rifaximin was not obvious. Rifaximin could reshape the correlation of genera between different intestinal segments. Conclusion Rifaximin improved visceral hypersensitivity in PI-IBS mice. Rifaximin mainly affected ileal mucosal microbiota, and its improvement effect on IBS might be closely related to the improvement of ileal microbiota structure

Multihorizon predictive energy optimization and lifetime management for connected fuel cell electric vehicles

[EN] A reliable energy optimization strategy incorporating vehicle connectivity is of great importance for the performance enhancement of fuel cell electric vehicles. In this paper, a multihorizon hierarchical model predictive control framework is proposed, which reduces energy consumption while incorporating fuel cell lifetime management though real-time speed preview. Specifically, the trajectories of battery state of charge are explored via convex optimization in the upper layer to provide a suboptimal reference for real-time optimization, and the concept of multihorizon is introduced into convex optimization for the first time. At the lower level, an equivalent consumption minimum strategy-based model predictive control is designed, which improves energy utilization efficiency and prolongs the lifetime of fuel cells. The main contribution of this paper is to use multihorizon optimization to solve the energy optimization and lifetime management of fuel cell electric vehicles over different timescales. Experimental results show that the proposed strategy has great potential in cost saving, which can reduce 10.10% to 16.95% of the total cost in real driving conditions compared with the rule-based strategy.This work was supported by the National Natural Science Founda-tion of China (Grant No. 62111530196) , the Technology Development Program of Jilin Province, China (Grant No. 20200501010G X) and the China Automobile Industry Innovation and Development Joint Fund (Grant No. U1864206).Hou, S.; Yin, H.; Xu, F.; Pla Moreno, B.; Gao, J.; Chen, H. (2023). Multihorizon predictive energy optimization and lifetime management for connected fuel cell electric vehicles. Energy. 266. https://doi.org/10.1016/j.energy.2022.12646626

An Efficient Photocatalyst for Fast Reduction of Cr(VI) by Ultra-Trace Silver Enhanced Titania in Aqueous Solution

For the purpose of establishing a simple route to prepare a metal-semiconductor hybrid catalyst efficiently and reduce its cost through precise doping noble metals. In this study, ultra-trace silver doped TiO2 photocatalysts were fabricated via a &ldquo;green&rdquo; ultrasonic impregnation-assisted photoreduction strategy in an ethanol system, and its photocatalytic performance was systematically investigated by utilizing Cr(VI) as the model contaminant. A schottky energy barrier was constructed in Ag@TiO2, which served as a recombination center and possessed superior photocatalytic activity for Cr(VI) reduction. The obtained catalysts exhibited a significant e&minus;/h+ separation efficiency which directly led to an obvious photocatalytic property enhancement. Then, the resultant Ag@TiO2 (0.06 wt %, 30 min irradiation) showed about 2.5 times the activity as that of commercial P25 NPs for Cr(VI) degradation. Moreover, after five cycles, it still maintained considerably high catalytic ability (62%). This work provides a deep insight into preparation techniques of metal-semiconductor photocatalyst and broadens their application prospect