The CKKS scheme enables approximate arithmetic over encrypted vectors, supporting SIMD computation and controlled ciphertext rotations without revealing plaintexts. Prior encrypted fuzzy-query systems for English text typically map each character to a small, contiguous code and evaluate equality or similarity with low-degree polynomials. This design does not transfer to Chinese: the Unicode space is large and discontinuous, and after normalization for CKKS distinct characters can become numerically proximate, leading to collisions under approximation noise and undermining both equality tests and fuzzy comparisons. We address these limitations with two encoding strategies Digit Decomposition Embedding (DDE) and Bit Slicing (BS) that represent each Chinese character by several low-magnitude integer components, preserving inter-character separability at low multiplicative depth and remaining compatible with non-bootstrapping CKKS. We further introduce a slot-masking and sliding-window mechanism that leverages structured slot alignment and bounded rotations to realize fuzzy matching and substring retrieval. Together, these components provide a structured Chinese encoding framework for multi-field encrypted fuzzy query that maintains numeric distinguishability, controls depth growth, and exploits CKKS batch parallelism for efficient end-to-end execution.