For series-parallel hybrid electric vehicles (HEVs), problems of driveability are significant and difficult to solve due to clutch engagement during mode transitions. In this paper, a robust ...controller was designed for a series-parallel HEV to reduce vehicle jerk during mode transitions and improve vehicle driveability. First, a linear dynamic system model of the controlled plant was obtained for robust control design. Then, the robust controller was designed based on the mu-synthesis method and solved using the discrete D-K iteration; parameter uncertainties in the system model were considered in the design process to ensure the robustness of the control system. Finally, a hardware-in-the-loop (HIL) simulation was performed to verify the proposed controller. The HIL platform was composed of a dynamometer-simulated engine, a real transmission, a virtual electric machine, and a virtual vehicle, which was constructed based on the nonlinear dynamics of tires, road, and vehicle body. The HIL simulation results showed the effectiveness of the proposed robust mode transition control.
Reliable trajectory prediction of preceding target vehicles (PTVs) is crucial for the planning and decision making of automated vehicles. However, the future trajectory is affected by the driver's ...intention and diverse driving styles, which can hardly be predicted precisely, especially when the vehicle performs a lane change maneuver. In this study, we propose a lane crossing and final points generation (CFPG) model-based trajectory prediction approach for PTVs, in which the key influence factors such as the driver's intention and the mixed driving style are included. Firstly, we build a maneuver and stage recognition model upon the long short term memory (LSTM) to infer the current maneuver of the preceding target vehicle. Furthermore, the approach predicts the lane crossing point using a physics-based model combining with a deep conditional generative model trained by a deep neural network. Moreover, a maneuver-based model is adopted to predict the final point according to the prediction interval. In order to avoid the possible cumulative error caused by iteratively generating trajectories in traditional methods, we use a curve fitting method to obtain the predicted trajectory. Lane changing data collected from naturalistic driving scenarios are used to verify the proposed approach, and the results suggest more accurate and reliable prediction trajectories compared with conventional methods.
Purpose
The aim of this work was to investigate the risk factors for cement leakage and new-onset OVCF after Percutaneous vertebroplasty (PVP) and to develop and validate a clinical prediction model ...(Nomogram).
Methods
Patients with Osteoporotic VCF (OVCF) treated with PVP at Liuzhou People’s Hospital from June 2016 to June 2018 were reviewed and met the inclusion criteria. Relevant data affecting bone cement leakage and new onset of OVCF were collected. Predictors were screened using univariate and multi-factor logistic analysis to construct Nomogram and web calculators. The consistency of the prediction models was assessed using calibration plots, and their predictive power was assessed by tenfold cross-validation. Clinical value was assessed using Decision curve analysis (DCA) and clinical impact plots.
Results
Higher BMI was associated with lower bone mineral density (BMD). Higher BMI, lower BMD, multiple vertebral fractures, no previous anti-osteoporosis treatment, and steroid use were independent risk factors for new vertebral fractures. Cement injection volume, time to surgery, and multiple vertebral fractures were risk factors for cement leakage after PVP. The development and validation of the Nomogram also demonstrated the predictive ability and clinical value of the model.
Conclusions
The established Nomogram and web calculator (https://dr-lee.shinyapps.io/RefractureApp/) (https://dr-lee.shinyapps.io/LeakageApp/) can effectively predict the occurrence of cement leakage and new OVCF after PVP.
Catalytic ozonation is a non-selective mineralization technology of organic matter in water by using active free radicals generated by ozone degradation. Catalytic ozonation technology can be divided ...into homogeneous catalytic reactions using metal ions as catalysts and heterogeneous catalytic reactions using solid catalysts. Homogeneous catalytic ozonation technology has many problems, such as low mineralization rate, secondary pollution caused by the introduction of metal ions and low utilization efficiency of oxidants, which limit its practical application. Compared with homogeneous catalytic ozonation technology, heterogeneous catalytic ozonation technology has the advantages of easy recovery, lower cost of water treatment, higher activity and improved mineralization rate of organic matter. This overview classifies and describes catalysts for heterogeneous catalytic ozonation technology, including the different types of metal oxides, metal-free catalysts, and substrates used to immobilize catalysts. In addition, the heterogeneous catalytic ozonation process involved in the multiphase complex reaction process is discussed. The effects of different parameters on the performance of heterogeneous catalytic ozonation are also discussed.
State of charge (SOC) is a critical factor to guarantee that a battery system is operating in a safe and reliable manner. Many uncertainties and noises, such as fluctuating current, sensor ...measurement accuracy and bias, temperature effects, calibration errors or even sensor failure, etc. pose a challenge to the accurate estimation of SOC in real applications. This paper adds two contributions to the existing literature. First, the auto regressive exogenous (ARX) model is proposed here to simulate the battery nonlinear dynamics. Due to its discrete form and ease of implemention, this straightforward approach could be more suitable for real applications. Second, its order selection principle and parameter identification method is illustrated in detail in this paper. The hybrid pulse power characterization (HPPC) cycles are implemented on the 60AH LiFePO4 battery module for the model identification and validation. Based on the proposed ARX model, SOC estimation is pursued using the extended Kalman filter. Evaluation of the adaptability of the battery models and robustness of the SOC estimation algorithm are also verified. The results indicate that the SOC estimation method using the Kalman filter based on the ARX model shows great performance. It increases the model output voltage accuracy, thereby having the potential to be used in real applications, such as EVs and HEVs.
In this paper, a soft-switching topology is proposed for the bidirectional dc-dc converter. In order to achieve soft-switching conditions, the auxiliary circuits including a small inductor and two ...capacitors are introduced to the bidirectional dc-dc converter. By generating and keeping a recycle current in the auxiliary circuits, the proposed topology can provide soft-switching conditions for both switches of the bidirectional dc-dc converter in fixed frequency control application. Meanwhile, no auxiliary switches are introduced. Due to the existence of the auxiliary circuits, the proposed topology can also reduce the current ripple in the main inductor. Based on this soft-switching method, a family of bidirectional soft-switching dc-dc topologies is derived. These topologies have the similar structures and the same characteristics. The topology deduction, operating principles, and design guidelines are presented in detail. Finally, an experimental prototype is built to verify the analysis and characteristics of the proposed topologies.
This paper presents the mathematical modeling and analysis of a novel multimode transmission (MMT) for a hybrid electric vehicle (HEV) using a single electric machine (EM), which implies compactness ...and low cost. The single-EM solution avoids losses from another EM and its power electronics, which are employed in many existing HEVs. The topology of the MMT planetary gearset is the same as that of conventional four-speed automatic transmissions (ATs). The MMT realizes five power flow modes, which are developed into 16 operation modes, including one Motor_only mode, four Engine_only modes, four Compound driving modes, six Braking modes, and one Charging while parking mode. The properly arranged clutches transmit power flow more flexibly, allow direct mechanical power transmission from the engine to the drive shaft, and avoid spin loss for the engine and energy conversion loss for the electric components. Simulation under the New European Driving Cycle (NEDC) shows that the fuel consumption of the proposed HEV is comparable to a benchmark "THS II-like" vehicle, which uses a planetary gearset, two EMs, and no clutch, which indicates the fuel economy potential of this concept.
This paper aims to present a new type of series–parallel hybrid electric bus and its energy management strategy. This hybrid bus is a post-transmission coupled system employing a novel transmission ...as the series–parallel configuration switcher. In this paper, the vehicle architecture, transmission scheme and numerical models are presented. The energy management system governs the mode switching between the series mode and the parallel mode as well as the instantaneous power distribution. In this work, two separated controllers using fuzzy logic called Mode Decision and Parallel-driving Energy Management are employed to fulfill these two tasks. The energy management strategy and the applications of fuzzy logic are described. The strategy is validated by a forward-facing simulation program based on the software Matlab/Simulink. The results show that the energy management strategy is effective to control the engine operating in a high-efficiency region as well as to sustain the battery charge state while satisfy the drive ability. The energy consumption is theoretically reduced by 30.3% to that of the conventional bus under transit bus driving cycle. In addition, works need future study are also presented.
Abstract
Background
The prognosis of lung metastasis (LM) in patients with chondrosarcoma was poor. The aim of this study was to construct a prognostic nomogram to predict the risk of LM, which was ...imperative and helpful for clinical diagnosis and treatment.
Methods
Data of all chondrosarcoma patients diagnosed between 2010 and 2016 was queried from the Surveillance, Epidemiology, and End Results (SEER) database. In this retrospective study, a total of 944 patients were enrolled and randomly splitting into training sets (
n
= 644) and validation cohorts(
n
= 280) at a ratio of 7:3. Univariate and multivariable logistic regression analyses were performed to identify the prognostic nomogram. The predictive ability of the nomogram model was assessed by calibration plots and receiver operating characteristics (ROCs) curve, while decision curve analysis (DCA) and clinical impact curve (CIC) were applied to measure predictive accuracy and clinical practice. Moreover, the nomogram was validated by the internal cohort.
Results
Five independent risk factors including age, sex, marital, tumor size, and lymph node involvement were identified by univariate and multivariable logistic regression. Calibration plots indicated great discrimination power of nomogram, while DCA and CIC presented that the nomogram had great clinical utility. In addition, receiver operating characteristics (ROCs) curve provided a predictive ability in the training sets (AUC = 0.789, 95% confidence interval CI 0.789–0.808) and the validation cohorts (AUC = 0.796, 95% confidence interval CI 0.744–0.841).
Conclusion
In our study, the nomogram accurately predicted risk factors of LM in patients with chondrosarcoma, which may guide surgeons and oncologists to optimize individual treatment and make a better clinical decisions.
Trial registration
JOSR-D-20-02045, 29 Dec 2020.
This paper presents a novel topology for a nonisolated bidirectional dc-dc converter with soft-switching capabilities, which usually operates at a zero-voltage-switching (ZVS) condition. A ...nonisolated dc-dc converter combines a buck converter and a backward boost converter into one circuit, which consists of a half-bridge power switch, an inductor, and capacitors. In order to realize ZVS conditions, the proposed converter utilizes a coupled inductor, a small independent inductor, and auxiliary switches and diodes. Due to ZVS, switching stress on switch components is reduced, and the reverse recovery problem of MOSFET antiparallel body diodes is also eliminated. Moreover, the operating modes of the proposed converter can be switched between a ZVS mode and a conventional hard-switching mode on the basis of load conditions. The soft-switching mode is for heavy loads, and the hard-switching mode is for light-load conditions. Therefore, the highest efficiency can be obtained at almost all load ranges. The detailed theoretical analyses in each mode are presented, and a 1-kW prototype is also built to verify the principle of the circuit and the theoretical analysis.
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