Spatial Feature-Enhanced Base Station Deployment Optimization Method for Wireless Battery Management Systems

Wireless Battery Management Systems (wBMS) represent a transformative paradigm shift for enhancing modularity in Energy Storage Systems (ESS). However, signal attenuation and anisotropic multipath interference within metallic enclosures remain critical bottlenecks. While existing research predominantly focuses on protocol-layer logic, the pivotal impact of physical Base Station (BS) placement on link quality is often overlooked. This paper proposes a BS layout optimization framework underpinned by spatial feature enhancement. A Segmented Waveguide-Multiwall (SWMW) model is established to characterize the complex internal propagation, while a Conditional Diffusion Model (CDM) is leveraged to augment sparse RSSI fingerprints into high-resolution spatial maps. Finally, the deployment task is formulated as a multi-objective optimization problem and resolved via an Adaptive Sine-mapped Nutcracker Optimization Algorithm (AS-NOA). Experimental results demonstrate that the proposed method achieves excellent performance in spatial resolution and system robustness.