Current Issue : July-September Volume : 2025 Issue Number : 3 Articles : 5 Articles
Aiming at the irreversible demagnetization of permanent magnet synchronous motors (PMSMs) under extreme working conditions, a fault diagnosis method for permanent magnet demagnetization based on multi-parameter estimation is proposed in this paper. This scheme aims to provide technical support for enhancing the safety and reliability of permanent magnet motor drive systems. In the proposed scheme, multiple operating states of the motor are acquired by injecting sinusoidal current signals into the d-axis, ensuring that the parameter estimation equation satisfies the full rank condition. Furthermore, the accurate dq-axis inductance parameters are obtained based on a recursive least square method. Subsequently, a dual extended Kalman filter is employed to acquire real-time permanent magnet flux linkage data of PMSMs, and the estimation data between the two algorithms are transferred to each other to eliminate the bias of permanent magnet flux estimation caused by a parameter mismatch. Finally, accurate evaluation of the remanence level of the rotor permanent magnet and demagnetization fault diagnosis can be achieved based on the obtained permanent magnet flux linkage parameters. The experimental results show that the relative estimation errors of the dq-axis inductance and permanent magnet flux linkage are within 5%, which can realize the effective diagnosis of demagnetization fault and high-precision condition monitoring of a permanent magnet health....
This paper analyses the impact of a front brake light (FBL) on road safety from a pedestrian perspective. In addition to the traditional brake lights mounted at the rear of vehicles, an FBL can provide extra information about the driver’s intention to stop, especially to road users looking at the front of the approaching vehicle. This innovative feature aims to improve road safety by providing additional visual cues, where rear brake lights are not visible. Because pedestrians usually have a better line of sight to the front of a vehicle, the front brake light is more effective in alerting them to an impending stop. Therefore, an FBL could help them feel more confident when crossing the road by helping determine if it is safe to do so. A total of 621 questionnaires were collected from pedestrians who participated in the first real field test of FBL. The test period was conducted from November 2022 to September 2023 in two neighbouring regions of Slovakia. Their feedback allowed us to assess how the presence of an FBL influenced their perception of road safety, particularly when crossing roads. As a statistical result, more than 81% of the participants felt safer when crossing the road due to the presence of an FBL. Notably, the older generation evaluated FBLs very positively, while the youngest generation demonstrated more dangerous behaviour. Furthermore, the survey revealed that a significant proportion of respondents maintained a more reserved attitude towards the benefits of FBLs, largely due to a lack of information.This paper analyses the impact of a front brake light (FBL) on road safety from a pedestrian perspective. In addition to the traditional brake lights mounted at the rear of vehicles, an FBL can provide extra information about the driver’s intention to stop, especially to road users looking at the front of the approaching vehicle. This innovative feature aims to improve road safety by providing additional visual cues, where rear brake lights are not visible. Because pedestrians usually have a better line of sight to the front of a vehicle, the front brake light is more effective in alerting them to an impending stop. Therefore, an FBL could help them feel more confident when crossing the road by helping determine if it is safe to do so. A total of 621 questionnaires were collected from pedestrians who participated in the first real field test of FBL. The test period was conducted from November 2022 to September 2023 in two neighbouring regions of Slovakia. Their feedback allowed us to assess how the presence of an FBL influenced their perception of road safety, particularly when crossing roads. As a statistical result, more than 81% of the participants felt safer when crossing the road due to the presence of an FBL. Notably, the older generation evaluated FBLs very positively, while the youngest generation demonstrated more dangerous behaviour. Furthermore, the survey revealed that a significant proportion of respondents maintained a more reserved attitude towards the benefits of FBLs, largely due to a lack of information....
To address the limitation of 2D lane detection methods with monocular vision, which fail to capture the three-dimensional position of lane boundaries, this study proposes a convolutional neural network architecture for 3D lane detection. The deep residual network ResNet50 is employed as the feature extraction backbone, augmented with a coordinate attention mechanism to facilitate shallow feature extraction, multi-scale feature map generation, and extraction of small-scale high-order feature information. The BIFPN network is utilized for bidirectional feature fusion across different scales, significantly enhancing the accuracy of lane boundary detection. By constructing an inverse perspective transformation model (IPM), the conversion from front view to aerial view is realized. A dedicated 3D lane detection head is designed for lane boundary anchor lines, enabling efficient fusion and downsampling of multi-scale feature maps. By incorporating the bias between lane boundaries and anchor lines, the 3D position of lane boundaries is effectively detected. Validation experiments on the OpenLane dataset demonstrate that the proposed method not only detects the spatial locations of lane boundaries but also identifies attributes, such as color, solid or dashed, single or double lines, and left or right dashed configurations. Additionally, the method achieves an inference speed of 64.9 FPS on an RTX 4090 GPU, showcasing its computational efficiency....
The collision avoidance capability of autonomous vehicles in extreme traffic conditions remains a focal point of research. This paper introduces an Adaptive Cruise Control (ACC) strategy based on Model Predictive Control (MPC) and Responsibility-Sensitive Safety (RSS) models. Simulations were conducted in the CARLA environment, where the lead vehicle underwent various rapid deceleration scenarios to optimize the following vehicle’s braking strategy. By integrating the multi-step predictive optimization capabilities of MPC with the dynamic safety assessment mechanisms of RSS, the proposed strategy ensures safe following distances while achieving rapid and precise speed adjustments, thereby enhancing the system’s responsiveness and safety. The model also incorporates a secondary optimization to balance comfort and stability, thereby improving the overall performance of autonomous vehicles. The use of multi-dimensional assessment metrics, such as Time to Collision (TTC), Time Exposed TTC (TET), and Time Integrated TTC (TIT), addresses the limitations of using TTC alone, which only reflects instantaneous collision risk. The optimization of the model in this paper aims to improve the safety and comfort of the following vehicle in scenarios with various gap distances, and it has been validated through the SSM multi-indicator approach. Experimental results demonstrate that the improved ACC model significantly enhances vehicle safety and comfort in scenarios involving large gaps and short-distance emergency braking by the lead vehicle, validating the method’s effectiveness in various extreme traffic scenarios....
As the market share of electric vehicles (EVs) increases year by year, their charging load forecasting has become a research hotspot and a difficulty. Aiming at the shortcomings of the current research on the charging probability prediction of EVs with different power levels, this paper proposes a multi-power-level EV charging probability prediction method. Firstly, based on the characteristics of electric vehicles, the power of charging facilities, and the travel habits of owners, the SOC mathematical models of charging start time, as well as the start and end state of charge, are established, and the different charging power selection models are established in combination with the parking time. Then, the Monte Carlo simulation method is used to predict the charging probability of electric vehicles with different power levels on typical dates such as working days, weekends, and holidays....
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