IoT-based virtual coupling systems enable reduced headways for high-speed trains, yet most Virtually Coupled Train Set (VCTS) studies still rely on a leader-follower paradigm where followers simply match the leader’s speed. Under position-dependent slopes/speed limits, asynchronous departures, and uncertain train dynamics, it remains difficult to jointly achieve traffic efficiency, cooperative tracking accuracy, and ride comfort. This paper proposes a hierarchical multi-objective Model Predictive Control (MPC) framework for follower trains in VCTS with amulti-stepdecision structure consisting of an offline tightening design and an online two-step regulation procedure.Offline, we solve an optimization-based tightening design that jointly determines tightened constraint sets and disturbance-affine feedback gains under Automatic Train Protection (ATP) supervision, improving traffic-efficiency potential by reducing conservatism that can otherwise trigger unnecessary braking actions and degrade throughput.Online, a two-step regulation is executed under uncertainty: first, a tracking-prioritized robust MPC enforces ATP-compliant operation; second, using the resultingoptimal and feasibletracking-cost information consistent with the offline-designed feedback gains, we construct a Lyapunov-based constraint that yields an explicit tracking-cost tolerance bound, within which a comfort-oriented MPC improves ride comfort. A comfort-aware adaptive mechanism then tunes the tolerance online for more consistent tracking-comfort behaviour. The proposed distributed framework is proved to be recursively feasible and input-to-state stable. Simulations on the Beijing-Tianjin high-speed railway line with CR400BF parameters demonstrate that, compared with representative weighted-sum and lexicographic baselines, the proposed method achieves a more reliable tracking-comfort trade-off with less conservative traffic-efficiency performance.

The synchronous arrival of trains in a virtually coupled train set (VCTS) is crucial to ensure efficient operations. The primary objective of VCTS is to decrease the inter-train spacing while stopping, aiming to minimize the time difference between arrivals. In this paper, we propose a distributed cooperative model predictive control-based (DCMPC) approach for synchronous arrival of VCTS. Firstly, the dynamics model of the unit train in VCTS is constructed, which considers external uncertainties. Then, a novel dynamic penalty matrix updating method is introduced to improve the accuracy and efficiency of unit train stopping. We also present the design of terminal constraints on the DCMPC control problem and the stability proof to ensure the feasibility of the controller. Finally, the effectiveness of the proposed method is verified through simulation experiments with concrete data from the Chengdu Metro Line NO.8 in China. Compared to conventional control approaches, the proposed DCMPC significantly reduces the arrival time difference while increasing the average stopping speed, resulting in a considerable 4% increase in the passing capacity of the line.

Real-time and accurate positioning is the key to ensuring the safe operation of trains. Traditional train positioning technology relies on track-side equipment, and there are problems such as high construction and maintenance costs and difficulties in obtaining the initial train positions. With the rapid development of enabling technologies such as AI and image recognition, visual perception-based train autonomous positioning technology has attracted widespread attention in recent years. To address the problem of large measurement errors due to camera pose changes in train visual positioning, this article proposes a monocular ranging method based on visual beacon imaging size correction. A kilometer post is used as a visual beacon, and a deep neural network is used to detect the visual beacon and extract its feature points' pixel coordinates. The PnP algorithm is used to estimate the camera pose and correct the visual beacon imaging size through the camera pose angle, the average relative error of ranging is stabilized at 2% ~ 3%, and the ranging effect is improved by about 60%, which effectively reducing the ranging error of the monocular ranging model based on known references.

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Arriving phase is an essential part of the virtually coupled train set (VCTS) operation in metros and significantly influences efficiency. This paper proposes a synchronous and precise control problem in VCTS arriving-phase operation and designs a hierarchical control approach to solve this problem. First, the control problem of VCTS arriving-phase operation is mathematically modeled, capturing the uncertain disturbances and measurement errors in train dynamics and considering input and safety constraints. Then, a two-layer control framework is designed, with the upper layer for coordinated trajectory planning and the lower layer for offset-free tracking of each train (unit) in VCTS. Specifically, in the upper layer, all units in VCTS are coordinated in an optimization problem to generate the reference trajectories that increase the synchronicity of arrival; in the lower layer, to track the reference trajectory, we propose an offset-free model predictive control (MPC) approach, which is based on an observer to handle uncertain disturbances and measurement errors. The stability of the offset-free MPC approach is proved, such that all units in VCTS can arrive at the station synchronously and precisely. Finally, experimental results demonstrate the performance of the proposed hierarchical approach.

Virtual Coupling (VC) is a hot topic in railways. A virtually coupled train set operates as a single train and consists of multiple unit trains (UTs). Each UT keeps a desired gap distance with its predecessor by following a spacing policy. Constant time headway (CTH) spacing policy is widely adopted in the existing studies about VC. Arrival time difference (ATD), i.e., the difference between the time instants of two successive UTs arriving at a platform, is large when using CTH. It is not expected because the passengers loading of all UTs should operate at the same time. This paper firstly analyzes the causes of ATD mathematically and proves ATD is inevitable when adopting CTH. Then, the change tendency of ATD with respect to each parameter is analyzed. The above analysis indicates that CTH is not suitable for the arrival process. Thus, a quadratic spacing policy is designed to reduce ATD. Experimental results show that ATD can hardly be reduced by only optimizing the parameters of CTH, but the quadratic spacing policy greatly reduces it.

As the core device of power electronic converter, IGBT has been widely used in the fields of new energy generation, smart grid and aerospace. The existing research shows that the failure caused by power module failure is as high as 31%. And the module failure caused by bonding wire fault accounts for about 70%. Therefore, it is very important to study the aging, failure mechanism and health assessment method of IGBT bonding wires for safe and reliable operation of converter. In this paper, the bonding wires of IGBT module is taken as the research object. According to the actual structure and using the finite element simulation software, a three-dimensional multi- physical field electro-thermal coupling model is established. The influence of the number and position of the bonding wires falling off on the electro-thermal characteristics of IGBT chip is studied,and the results show that the uneven distribution of the bonding wires will cause the fluctuation of the junction temperature of IGBT chip.what's more, the increase of the number of the dropped bonding wires is the main reason for the rise of the junction temperature. Based on this model, a more sensitive temperature gradient model of IGBT chip is established. It is found that the temperature gradient model can accurately monitor the number of bonding wires dropped. It provides a new idea for the condition monitoring of bonding wires in IGBT .

Runtime verification is a lightweight formal method that checks whether an execution of a system satisfies a given property. A challenge in building a runtime verification system is to define a suitable monitoring specification language, i.e., a language that is expressive, of reasonable complexity, and easy to understand. In this paper, we extend live sequence charts (LSCs, [1]) for the specification of properties in systems monitoring. We define Parametrized extended LSCs (PeLSCs) by introducing the notions of necessary prechart, concatenation, and condition- and assignment-structure. With these PeLSCs, necessary and sufficient conditions of certain observations, and parametric properties can be specified in an intuitive way. We prove some results about the expressiveness of extended LSCs. In particular, we show that LSCs with necessary precharts are strictly more expressive than standard LSCs, and that iteration-free extended LSCs have the same expressive power as linear temporal logic (LTL). To generate monitors, we develop translations of PeLSCs into hybrid logic. We show that the complexity of the word problem of PeLSCs is linear with respect to the length of input traces, thus our formalism is well-suited for online monitoring of communicating systems.

When verifying the safety of ETCS, testing and formal methods have limitations to some degree. Runtime verification is effective to detect deviation between the current and the expected system behaviors. To improve the accuracy of runtime monitoring, 4-valued LTL (Linear Time Logic) semantics and formula rewriting based algorithm are proposed. Furthermore, approximation technique is presented for 4-valued LTL formulae to make the verification procedure high efficient. Finally, the method is applied to the European Train Control System (ETCS) by monitoring several scenario traces. The experimental results show that the 4-valued LTL semantics are able to generate the most accurate verification outcomes. It can also be found that the approximation technique improves the verification efficiency apparently in some cases.