Thermal management is essential in electric vehicles to preserve battery life. In particular, avoiding temperature peaks is critical to prevent accelerated degradation. The battery thermal management problem is crucia...
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Thermal management is essential in electric vehicles to preserve battery life. In particular, avoiding temperature peaks is critical to prevent accelerated degradation. The battery thermal management problem is crucial in fuel cell electric trucks due to the heavy vehicle weight, especially on mountain or hilly roads. Therefore, this paper proposes an energy management strategy that reduces battery degradation by limiting its usage at high temperatures to allow its cooldown and avoid peaks. The energy management strategy is adaptive because the main control parameters for the fuel cell/battery power-split are adjusted depending on the battery temperature. The comparison between adaptive and non-adaptive strategies proves the effectiveness of the proposed formulation in avoiding temperature peaks without hindering fuel consumption or fuel cell degradation. The robustness of the proposed energy management strategy is validated with simulations of several real-world driving cycles with various speed and elevation profiles.
Today, Industrial control System (ICS) databases are incredibly complicated with quite prolonged iterative lifecycle where every new iteration is driven by a new version of the database assignment. For the correct dat...
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As power electronics technology continues to advance, the prevalence of switching quantity interface circuits has grown in diverse domains, encompassing industrial production and everyday civilian applications. An ana...
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ISBN:
(数字)9798350329988
ISBN:
(纸本)9798350329995
As power electronics technology continues to advance, the prevalence of switching quantity interface circuits has grown in diverse domains, encompassing industrial production and everyday civilian applications. An analysis of operational data from these circuits, along with an assessment of their overall health, proves instrumental in the timely detection and resolution of operational anomalies. This holds paramount significance in upholding the reliability of these interface circuits. Nevertheless, tracking the degradation trajectory of the core components during their operational lifespan poses a challenge. Typically, only two states, normal and abnormal, are readily discernible, making direct health assessment elusive. To address this issue, this study introduces a health assessment methodology for the fundamental components of switch quantity interface circuits based on active excitation testing. Through the application of active excitation, the performance decay profile of the optical coupler is ascertained, solving the problem of capturing the degradation process within these circuits. This approach facilitates the stable and precise characterization of the health status of switching quantity interface circuits. The health assessment method presented in this paper is characterized by modest computational resource demands and a reduced reliance on expert knowledge. It is adept at quantitatively delineating the health status of switch-quantity interface circuits with precision, thereby offering guidance for the maintenance and replacement of pivotal electronic components within these circuits. In doing so, it contributes to the assurance of operational dependability and an extension of the service life of switch quantity interface circuits.
Following the latest energy market trends, active distribution systems incorporate an ascending mix of flexible loads, which can participate in Demand Response (DR) strategies. The purpose of this research paper is to...
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ISBN:
(数字)9798350386493
ISBN:
(纸本)9798350386509
Following the latest energy market trends, active distribution systems incorporate an ascending mix of flexible loads, which can participate in Demand Response (DR) strategies. The purpose of this research paper is to present a DR strategy for the Distribution System Operator (DSO) in order to enhance the system's operation and mitigate power quality issues, such as voltage drops, and congestion. The proposed algorithm aims at smoothing the load curve, taking into consideration the available flexible load and the limitations of the system. The algorithm is demonstrated on a model of the distribution system of Skiathos island, Greece, in the context of ENFLATE, a Horizon Europe project, and future scenarios with photovoltaic (PV) penetration are studied as well. According to the results, the proposed DR algorithm manages to reduce the voltage drop, eliminate the number of events where the voltage drop exceeds the limits and reduce the losses of the distribution system up to 8%-9%, depending on the PV penetration.
Eco-driving is an energy-aware driving style that improves the overall vehicle efficiency to reduce operating costs and extend the driving range. This paper focuses on the eco-driving of fuel cell electric trucks, opt...
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ISBN:
(纸本)9781665454698
Eco-driving is an energy-aware driving style that improves the overall vehicle efficiency to reduce operating costs and extend the driving range. This paper focuses on the eco-driving of fuel cell electric trucks, optimizing the speed plan based on the route elevation, and studying the trade-off between driving time and range. In particular, the optimal speed plan is created by combining two methods from optimal control theory (dynamic programming and Pontryagin’s minimum principle) to include an energy management strategy for fuel consumption optimization. The speed plan created with the proposed method increases the vehicle range by 8% compared with a constant speed plan. Moreover, the study shows that the vehicle range can be extended up to 50% if the driving time is increased, which might be an essential solution to cope with the undeveloped hydrogen refueling infrastructure. The conclusion of this work indicates several directions to continue the research on the topic: for example, addressing robustness to traffic conditions and including component degradation mitigation targets in the optimization (e.g. SoC operating range and fuel cell voltage degradation).
In terms of surface defect detection of glazed tiles, there are problems such as false detection and insufficient ability to identify small target defects due to the rich texture on the surface of glazed tiles. In res...
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ISBN:
(数字)9798350355413
ISBN:
(纸本)9798350355420
In terms of surface defect detection of glazed tiles, there are problems such as false detection and insufficient ability to identify small target defects due to the rich texture on the surface of glazed tiles. In response to these challenges, this article has compiled a dataset of glazed ceramic tiles and proposed an improved algorithm ECANet-FPG based on Faster R-CNN. Due to the similarity in texture and defects on the surface of ceramic tiles, this algorithm introduces the Efficient Channel Attention (ECA) module into the feature extraction network of Faster R-CNN to enhance the ability to extract deep features. At the same time, a Feature Pyramid Grids (FPG) structure is adopted to achieve efficient fusion of multi-scale features, in order to improve the recognition accuracy of small target defects. The experimental results show that the improved algorithm achieves higher detection accuracy and efficiency than the baseline model, demonstrating its effectiveness and practicality in detecting surface defects on glazed ceramic tiles.
To facilitate ground station monitoring and command uploading, unmanned aerial vehicles (UAVs) need to frequently exchange individual state data between units. However, this results in a significant usage of communica...
To facilitate ground station monitoring and command uploading, unmanned aerial vehicles (UAVs) need to frequently exchange individual state data between units. However, this results in a significant usage of communication bandwidth. To address this issue, on the basis of an event-triggered strategy, this paper proposes an Extended Kalman Filter (EKF). aimed at reducing the communication burden of UAVs while maintaining high accuracy. Specifically, a state measurement triggered by an event is selected for filtering only if it contains innovation, thereby reducing the amount of data that needs to be communicated. Since UAV systems are nonlinear, EKF is adopted to fully utilize the information obtained from event-triggered strategies, thereby enhancing the estimation performance. In this paper, a physical UAV was used to verify the proposed algorithm, and it proved to have robust dynamic performance and to effectively reduce the communication rate.
This paper presents a cardiac MRI image segmentation model based on an improved U-Net architecture. Accurate segmentation of cardiac MRI images is critical for the diagnosis and treatment of cardiovascular diseases, y...
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In this paper, a fault detection and isolation scheme for multiplicative faults in dynamic systems based on data-driven K-Gap metric and k-nearest neighbour (kNN) classification is proposed. To detect multiplicative f...
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In this paper, a fault detection and isolation scheme for multiplicative faults in dynamic systems based on data-driven K-Gap metric and k-nearest neighbour (kNN) classification is proposed. To detect multiplicative faults, the standard classification task of kNN is studied from the viewpoint of system analysis. To this end, the data-driven stable kernel representation based on input/output data is presented for feature extraction capturing the dynamic of linear time-invariant (LTI) systems. Data-driven K-Gap metric is used as an alternative tool for distance measure between two kernel subspaces in the kNN algorithm. A simulation example on the three-tank system (DTS200) demonstrates the successful detection and isolation of various multiplicative faults
In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied ...
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In the present study, the finite-time asynchronous dissipative filter design problem for the Markov jump systems with conic-type nonlinearity is studied. The hidden Markov model can describe the asynchronism embodied in the system modes and the filter modes reasonably. Moreover, a suitable LyapunovKrasovskii function is utilized and linear matrix inequalities are applied to obtain adequate conditions. These techniques guarantee the finite-time boundedness and strict dissipativity of the filtering error dynamic system. Furthermore, the design problems of the passive filter and the H∞ filter are studied by adjusting the three parameters U, G and V. Finally, the filter gains and the optimal index α*are obtained and the correctness and feasibility of the designed approach are verified by a simulation example.
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