To achieve a successful increase in the plug-in battery electric vehicle (BEV) market, it is anticipated that a significant improvement in battery performance is required to increase the range that ...BEVs can travel and the rate at which they can be recharged. While the range that BEVs can travel on a single recharge is improving, the recharge rate is still much slower than the refueling rate of conventional internal combustion engine vehicles. To achieve comparable recharge times, we explore the vehicle considerations of charge rates of at least 400 kW. Faster recharge is expected to significantly mitigate the perceived deficiencies for long-distance transportation, to provide alternative charging in densely populated areas where overnight charging at home may not be possible, and to reduce range anxiety for travel within a city when unplanned charging may be required. This substantial increase in charging rate is expected to create technical issues in the design of the battery system and the vehicle's electrical architecture that must be resolved. This work focuses on vehicle system design and total recharge time to meet the goals of implementing improved charge rates and the impacts of these expected increases on system voltage and vehicle components.
•BEV refueling time requires 4–6 C-rate charging and large battery capacities.•Peak charge rate less important than average rate for 150–200 mile range recharge.•XFC significantly impacts BEV voltage design, which may impact other EVs.•BEV-charging infrastructure coordination must provide consistent charge experience.
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Vascular endothelial growth factor (VEGF) plays an important role in angiogenesis and is highly expressed in carcinoma, which make it an important target for tumor targeting therapy. ...Neuroblastoma is the main cause for cancer-related death in children. Like most solid tumors, it is also accompanied with the overexpression of VEGF. Doxorubicin Hydrochloride (DOX), a typical chemotherapeutic agent, exhibits efficient anticancer activities for various cancers. However, DOX, without targeting ability, usually causes severe damage to normal tissues. To overcome the shortages, we designed a novel nano-composite, which is Bevacizumab (Bev) modified SiO2@LDH nanoparticles (SiO2@LDH-Bev), loading with DOX to achieve targeting ability and curative efficiency. SiO2@LDH-DOX and SiO2@LDH-Bev-DOX nanoparticles were synthesized and the physicochemical properties were characterized by TEM detection, Zeta potential analysis, FTIR, Raman and XPS analysis. Then in vitro and in vivo anti-neuroblastoma efficiency, targeting ability and mechanisms of anti-carcinoma and anti-angiogenesis of SiO2@LDH-Bev-DOX were explored. Our results indicated that we obtained the core-shell structure SiO2@LDH-Bev with an average diameter of 253±10nm and the amount of conjugated Bev was 4.59±0.38μg/mg SiO2@LDH-Bev. SiO2@LDH-Bev-DOX could improve the cellular uptake and the targeting effect of DOX to brain and tumor, enhance the anti-neuroblastoma and anti-angiogenesis efficiency both in vitro and in vivo, and alleviate side effects of DOX sharply, especially hepatic injury. In addition, we also demonstrated that angiogenesis inhibitory effect was mediated by DOX and VEGF triggered signal pathways, including PI3K/Akt, Raf/MEK/ERK, and adhesion related pathways. In summary, SiO2@LDH-Bev could be a potential VEGF targeting nanocarrier applied in VEGF positive cancer therapy.
This paper explored that a novel core-shell structure nanomaterial SiO2@LDH and modified SiO2@LDH with Bevacizumab (Bev) to form a new tumor vasculature targeting nanocarrier SiO2@LDH-Bev as vector of DOX, which was not reported before. The results indicated that SiO2@LDH-Bev could improve the VEGF targeting ability, anti-neuroblastoma and anti-angiogenesis efficiency of DOX. At the same time, SiO2@LDH-Bev-DOX could erase the cardiac toxicity and hepatic injury coming from DOX. Tube formation showed SiO2@LDH-Bev-DOX had the strongest effect on inhibiting angiogenesis among all the four formulations. SiO2@LDH-Bev-DOX could downregulate expression of p-VEGFR and inhibit activation of the Raf/MEK/ERK, p38MAPK, PI3K/Akt and FAK signaling pathways to achieve the goal of anti-angiogenesis. This work provides a novel system for the safe and efficient use of Bev and DOX on Neuroblastoma and explores the mechanism of the function of nano carrier in cancer therapy both in vitro and in vivo.
Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending and drawing extensive attention both from industry and academia. Conventional approaches for most ...autonomous driving algorithms perform detection, segmentation, tracking, etc., in a front or perspective view. As sensor configurations get more complex, integrating multi-source information from different sensors and representing features in a unified view come of vital importance. BEV perception inherits several advantages, as representing surrounding scenes in BEV is intuitive and fusion-friendly; and representing objects in BEV is most desirable for subsequent modules as in planning and/or control. The core problems for BEV perception lie in (a) how to reconstruct the lost 3D information via view transformation from perspective view to BEV; (b) how to acquire ground truth annotations in BEV grid; (c) how to formulate the pipeline to incorporate features from different sources and views; and (d) how to adapt and generalize algorithms as sensor configurations vary across different scenarios. In this survey, we review the most recent works on BEV perception and provide an in-depth analysis of different solutions. Moreover, several systematic designs of BEV approach from the industry are depicted as well. Furthermore, we introduce a full suite of practical guidebook to improve the performance of BEV perception tasks, including camera, LiDAR and fusion inputs. At last, we point out the future research directions in this area. We hope this report will shed some light on the community and encourage more research effort on BEV perception.
Constructing a virtual world for the Metaverse based on real-world data is crucial, yet creating virtual environments for crowded scenes poses challenges in accurately tracking individuals using ...egocentric wearable cameras due to occlusions caused by crowded pedestrians. To address this, we propose a collaborative perception strategy that leverages multiple agents equipped with multi-view cameras to construct an occupancy map for a crowded environment. To fuse the multi-view perceptions of multiple agents, we propose a Collaborative Bird Eye View fusion network, called CollaborativeBEV (C-BEV), in which, we leverage a depth-based BEV network as a feature extractor, and propose a feature enhancement module to improve perception fusion in overlapping area. A designed loss function is introduced to address data imbalance during training, and a BEV enhancement strategy is proposed to augment the sample pool for training the BEV decoder. Experiment on the Sean2.0 dataset demonstrates that our C-BEV method performs better than the baseline method in terms of a 5.3% IoU increase. Our code will be released on github. https://github.com/RYaNzzZ1/CollaborativeBEV.
•Proposed a collaborative BEV method for reconstructing crowded environments.•An enhancement branch to improve perception accuracy in view overlap areas.•A BEV augmentation strategy and a designed loss to mitigate overfitting.
The increasing adoption of battery electric vehicles (BEVs) is leading to rising demand for electricity and, thus, leading to new challenges for the energy system and, particularly, the electricity ...grid. However, there is a broad consensus that the critical factor is not the additional energy demand, but the possible load peaks occurring from many simultaneous charging processes. Hence, sound knowledge about the charging behavior of BEVs and the resulting load profiles is required for a successful and smart integration of BEVs into the energy system. This requires a large amount of empirical data on charging processes and plug-in times, which is still lacking in literature. This paper is based on a comprehensive data set of 2.6 million empirical charging processes and investigates the possibility of identifying different groups of charging processes. For this, a Gaussian mixture model, as well as a k-means clustering approach, are applied and the results validated against synthetic load profiles and the original data. The identified load profiles, the flexibility potential and the charging locations of the clusters are of high relevance for energy system modelers, grid operators, utilities and many more. We identified, in this early market phase of BEVs, a surprisingly high number of opportunity chargers during daytime, as well as switching of users between charging clusters.
After several years of intensified implementing the subsidy policy for battery electric vehicles (BEVs) intending to boost China’s BEV market and the development of China’s domestic BEV industry, the ...Chinese government plans to totally abolish the government subsidy policy in 2020, one critical issue faced is that whether the BEV market can sustain without the subsidies. This work aims to answer this question, which firstly started by building a theoretical scheme for understanding the roles of China’s favorable government policies and market forces on motivating consumers to adopt BEVs based on the cues utilization theory. In particular, the commercial BEV demonstration policies and Chinese BEV brand reputation were considered in this scheme. And then by building several indexes to reflect the real effects of the market forces and government policies considered in this scheme, a structural equation model is constructed to explore how BEV sales and BEV battery technology were impacted during 2016/01–2019/12. The final results prove that China’s BEV policies succeeded a lot in providing consumers the extrinsic cues helping them to reduce perceived risks of purchasing BEVs, and thus contributed to boosting China’s BEV sales. Constructing more charging piles exerted the most significant effects, followed by the improving global reputation of Chinese BEV brands and increase in commercial BEV sales. The subsidy policy did not contribute the growth of China’s BEV sales directly, but indirectly through the mediation of improved BEV battery technologies and the magnitude is rather low, indicating that the growth of China’s BEV sales has already been less driven by the government subsidies, from which we can conclude that it is very possible for China’s BEV market to sustain without government subsidies. Policy implications for other governments are provided at the end.
•A theoretical scheme for contribution to BEV market development was constructed based on cues utilization theory.•A structural equation method was used to find the effects.•China’s BEV policies provided consumers the extrinsic cues helping them to reduce perceived risks of purchasing BEVs.•The results show that it is very possible for China’s BEV market to sustain without government subsidies.
Due to the ever-increasing harmful emissions affecting natural life and health seriously, it is inevitable the usage of renewable energy sources instead of fossil resources in the near future. ...Another drawback of fossil fuels is several threats like environmental pollution and global warming, which are potential risks for future generations. Given that the transportation sector makes a huge contribution to carbon emissions, the importance of battery electric vehicles (BEVs), which are an eco-friendly form of vehicles is obvious. Because the BEV market has been rapidly expanding recently, it has become a significant issue to assess BEV alternatives comprehensively from the customer's point of view. This assessment can be made by addressing the basic features of each BEV. Further, multiple criteria decision making (MCDM) techniques are efficient instruments for the right BEV purchase decision. In this work, therefore, ten BEVs are chosen as alternatives. These vehicles are then ranked using SECA, MARCOS, MAIRCA, COCOSO, ARAS, and COPRAS multi-criteria techniques on the basis of technical specifications, such as acceleration, price, battery, range, and so on. Afterward, results from various MCDM techniques are aggregated by applying the Borda count and Copeland ranking methodologies. “Price”, “permitted load,” and “energy consumption” are determined as the most three significant factors for BEV selection, respectively, whereas Tesla Model S is highlighted as the best choice. Further, the robustness and reliability of the results are performed by applying a sensitivity analysis. The proposed framework can be utilized as a basis for more detailed purchasing decisions.
•A novel integrated MCDM model for BEV selection is presented.•Six MCDM methods as well as two ranking strategies are utilized.•10 BEVs are evaluated as per 11 factors.•Price, permitted load, and energy consumption are the most significant factors.•Tesla Model S is highlighted as the best choice.
The operation of electric vehicles in cold weather is a concern, but there is not a lot of literature available regarding the precise nature of impacts on travel range. Two types of commercial ...battery electric vehicles, namely, the Nissan Leaf and the Mitsubishi i-MiEV, were driven to depletion across a broad range of temperatures that occur naturally in Winnipeg, MB, Canada, due to its climate. Analysis of data showed that the travel range can be reasonably interpreted as a function of ambient temperature using a series of simple linear segments: an upper plateau above about +20 °C, a lower plateau below about −15 °C, and a linearly varying segment in the middle. Both the Leaf and i-MiEV appeared to follow this model, with a good correlation of data for the middle (linearly varying) segment. Impacts of air conditioning on the travel range were also separately tested. This paper provides guidance for more rigorous assessments of electric-vehicle range performance into the future.
The variation in BEV energy consumption and driving range under different weather and driving conditions can affect the usefulness and consumer acceptance of these vehicles. Thus, there is a need to ...better understand and quantify seasonal factors that affect consumption and range under real-world driving conditions. In this paper, a dataset representing the real-world driving activity of 197 BEVs of the same model recorded over 12 months at a polling frequency of 0.1 Hz is analyzed to estimate BEV performance across different driving applications (personal driving, taxi operation, and ridesharing) and seasons (spring/autumn, summer, and winter). The results show that the electricity consumption, travel patterns, and charging patterns of BEVs vary significantly by both vehicle application and season. For example, BEV models with a range of 160 km, recharged every 1.6 days on average, can meet most trip demands of personal vehicles. However, the same BEV model when used for ridesharing or taxi purposes, is driven much more and recharged more frequently. The results also show that actual BEV electricity consumption (EC) differs significantly from the consumption predicted by the New European Driving Cycle (NEDC) test, with real-world EC being 7%–10% higher than predicted by the NEDC test cycle. Furthermore, the real-world range of personal-use BEVs in winter is only 64% of the NEDC-estimated range. The study found that, when the ambient temperature is lower than 10 °C, electricity consumption increases 2.4 kWh/100 km for every 5 °C decrease in temperature. When it is higher than 28 °C, EC increases 2.3 kWh/100 km for every 5 °C increase in temperature. These findings imply that manufacturers should design BEVs with application-appropriate driving ranges and make R&D investments for improving battery performance in cold environments.
HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need to perform road ...segmentation and view transformation separately, which often causes distortion and missing content. To push the limits of the technology, we present a novel framework that reconstructs a local map formed by road layout and vehicle occupancy in the bird's-eye view given a front-view monocular image only. We propose a front-to-top view projection (FTVP) module, which takes the constraint of cycle consistency between views into account and makes full use of their correlation to strengthen the view transformation and scene understanding. In addition, we apply multi-scale FTVP modules to propagate the rich spatial information of low-level features to mitigate spatial deviation of the predicted object location. Experiments on public benchmarks show that our method achieves various tasks on road layout estimation, vehicle occupancy estimation, and multi-class semantic estimation, at a performance level comparable to the state-of-the-arts, while maintaining superior efficiency.
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