Wenjie Qi

During high-rate discharge, lithium-ion batteries exhibit a notable temperature rise accompanied by an overly large in-module temperature spread, which poses a serious obstacle to thermal management. In this context, a liquid cooling plate equipped with built-in, spaced, staggered bluff bodies is introduced here. The present work examines how four geometric attributes of the bluff body (cross-sectional profile, size, spacing, and wall thickness) influence the heat-removal behavior of the battery module. It is found that the square cross-section yields the best thermo-hydraulic performance. Increasing the bluff body side length, together with reducing both the spacing and the thickness, promotes heat removal while raising the pressure drop to differing degrees. The influence of operating conditions was then analyzed, and the factors considered comprised the coolant type, the inlet temperature, and the inlet mass flow rate. Pure water was identified as the optimum cooling medium among the candidates examined. Lowering the coolant inlet temperature brings the module peak temperature down substantially, yet the maximum temperature difference widens. Conversely, progressively diminishing returns are observed as the inlet flow rate is raised. Subsequently, an orthogonal experiment was run to determine which parameter combination yields a favorable trade-off between thermal and hydraulic behavior, and the optimum was found at a square bluff body side length of 4.0 mm, an inlet mass flow rate of 0.003 kg/s, an inlet temperature of 294.15 K, a bluff body spacing of 12.08 mm, and a bluff body thickness of 0.5 mm. Under these optimal settings, the optimal parameter achieves 299.60 K for the module maximum temperature, 3.55 K for the maximum temperature difference, and 65 Pa for the pressure drop. Compared with the bluff-body-free channel under identical operating conditions, the module maximum temperature and the maximum temperature difference are reduced by 2.26 K and 0.39 K, respectively.

In swarm planning for ground robots, the risk of collisions due to trajectory intersections and the challenges of planning in unknown environments are critical issues. To address these challenges, this paper presents a swarm planning method based on asynchronous planning to achieve collision-free swarm planning in dense unknown environments. Path points are generated based on a multi-constraint framework, and trajectory optimization is performed by combining a “spring-damping” system with convex decomposition, thereby improving the method of generating local target points. To avoid trajectory conflicts between robots, we introduce a triangular trajectory conflict model and establish a velocity control method based on the “spring-damping” system. This enables two robots whose planned trajectories conflict to either accelerate simultaneously to escape or decelerate to avoid a collision. Simulation-based and real-world experiments show that the proposed method can generate executable, collision-free trajectories at a relatively high speed in unknown environments while effectively preventing collisions between robots during swarm planning.