RESUMO
The time delay (TD) in the levitation control system significantly affects the dynamic performance of the closed-loop system in electromagnetic suspension (EMS) maglev vehicles. Excessive TD can cause levitation instability, making it essential to explore effective mitigation methods. To address this issue, a Smith Predictor (SP) is integrated into the traditional PID levitation control system. The combination of theoretical analysis and numerical simulation is employed to assess the stability of the time-delay levitation control system after the integration of the Smith Predictor. Theoretical analysis reveals that when TD exceeds a critical threshold, the levitation system becomes unstable. The addition of SP alters the root trajectory of the system characteristic equation from positive to negative, and recovers the levitation system to stable status. Assuming complete knowledge of the dynamic system, the TD compensation value in the SP becomes a key parameter that determines its performance. A minimum effective value (MEV) for TD compensation is identified, correlating with the system's stability region. Under the influence of TD, more complex systems and higher running speeds of the maglev vehicle lead to a narrower stable region and a larger MEV for TD compensation. Given the simulation parameters in this paper, with a system TD of 15 ms and a maximum vehicle speed of 160 km/h, the MEV for TD compensation in the SP should be set at 12 ms.
RESUMO
The elastic deformation of the levitation electromagnet (LM) of the high-speed maglev vehicle brings uneven levitation gaps and displacement differences between measured gap signals and the real gap in the middle of the LM, and then reduces dynamic performances of the electromagnetic levitation unit. However, most of the published literature has paid little attention to the dynamic deformation of the LM under complex line conditions. In this paper, considering the flexibility of the LM and the levitation bogie, a rigid-flexible coupled dynamic model is established to simulate deformation behaviors of the LMs of the maglev vehicle passing through the 650 m radius horizontal curve. Simulated results indicate that the deflection deformation direction of the same LM on the front transition curve is always opposite to that on the rear transition curve. Similarly, the deflection deformation direction of a left LM on the transition curve is opposite to that of the corresponding right LM. Furthermore, deflection deformation amplitudes of the LMs in the middle of the vehicle are always very small (less than 0.2 mm). However, the deflection deformation of the LMs at both ends of the vehicle is considerably large, and the maximum deflection deformation is about 0.86 mm when the vehicle passes at the balance speed. This forms a considerable displacement disturbance for the nominal levitation gap of 10 mm. It is necessary to optimize the supporting structure of the LM at the end of the maglev train in the future.
RESUMO
The traditional electromagnetic force calculation method does not consider the non-linear magnetization characteristics of the ferromagnetic material or the magnetic resistance in full circuit, resulting in large calculation errors when the electromagnet operation state is far from the rated state, and causing the dynamics simulation results to diverge from the actual situation. A more accurate analytical formula for electromagnetic force is derived based on the full circuit magnetic resistance modification and considering the non-linear magnetization characteristics of ferromagnetic materials. Then combined with the finite element simulation analysis, the magnetic resistance modification (MRM) method is proposed for calculating electromagnetic levitation force and guiding force. This MRM method greatly improves the accuracy of electromagnetic force calculations and provides greater accuracy for EMS maglev vehicle dynamics simulations.
RESUMO
Clarifying the current situation of regional water pollutants and the relationship between pollutants and pollution sources is considered essential for managing the water environment. Water quality identification index (WQI), cluster analysis (CA), positive matrix factorization (PMF), and stable isotope analysis in R (SIAR) were employed to interpret a large and complex water quality data set of the Qinhuai River catchment generated during 2015 to 2019 to monitor of 11 parameters at 29 different sampling sites. WQI analysis indicated that water quality in Qinhuai River catchment is considered to have "moderate pollution," and an improving trend of water quality was observed at the interannual scale. TN was the most deteriorated of all pollution parameters. CA and PMF results on the spatial scale revealed that sampling sites located at downtown of Nanjing and Lishui District or Jangling University town were highly polluted due to the sewage from domestic sewage and business service sewage (28.88%) as well as industrial wastewater (27.43%), while sampling sites located at Hushu Street Administrative District, Ergan River, and Sangan River were slightly polluted by rural domestic wastewater and garbage (28.79%), and agricultural non-point source pollution (24.3%). The middle-lower reaches (Jiangning Development Zone and Moling Street) and middle reaches (Lukou Street Administrative District) were moderately polluted by industrial wastewater (27.25%), sewage from domestic wastewater and business service wastewater (31.62%) as well as inner sources (24.76%). The SIAR results showed that NO3--N was the main nitrogen form, and the NO3--N mainly originated from sewage (61%) and soil (34%) in the Yuntaishan River sub-catchment. These results will aid in the development of measures required to control water pollution in river catchments.