| 徐迎港,储琦,梁国旗,张伟,门昌伟.基于轮胎周向频率的鲁棒间接式胎压监测算法[J].电子测量与仪器学报,2024,38(7):79-88 |
| 基于轮胎周向频率的鲁棒间接式胎压监测算法 |
| Robust indirect tire pressure monitoring method based on torsional resonance frequency |
| |
| DOI： |
| 中文关键词: 车辆工程 间接式胎压监测 车身稳定性控制系统 信号处理 频谱分析 |
| 英文关键词:vehicle engineering indirect tire pressure monitoring body stability control system signal processing spectrum analysis |
| 基金项目:国家自然科学基金（52172370，52102440）项目资助 |
|
|
| Author | Institution |
| Xu Yinggang | School of Vehicle and Mobility, Tsinghua University, Beijing 100083, China |
| Chu Qi | Beijing Automotive Research
Institute Co., Ltd., Beijing 101300, China |
| Liang Guoqi | Beijing Automotive Group Co., Ltd., Beijing 101300, China |
| Zhang Wei | Beijing Automotive Research
Institute Co., Ltd., Beijing 101300, China |
| Men Changwei | Beijing Automotive Research
Institute Co., Ltd., Beijing 101300, China |
|
| 摘要点击次数: 53 |
| 全文下载次数: 315 |
| 中文摘要: |
| 针对目前间接式胎压监测(iTPMS)在识别汽车四轮同时欠压时准确度低且易误识别的问题和发动机的震动导致的误识别问题，为提高系统对欠压轮胎识别的准确率，研究轮胎受到道路激励所产生的轮速频谱特征，提出了一种基于轮速传感器和车载硬件的间接式胎压监测算法。首先通过信号去噪、齿轮误差过滤对轮速信号进行了预处理，剔除了轮速漏齿和多齿的问题，使用最小二乘法（RLS）对齿圈进行了误差校正，然后结合轮胎的振动特性分析，使用傅里叶变换方法（FFT）得到轮速的频谱特征，使用带通滤波器（BSP）和陷波滤波器（NF）得到指定范围内的轮速频谱特征，并剔除发动机转动的影响，利用最终得到的共振频率尖峰判断轮胎气压的状态，欠压轮胎的峰值频率会正常胎压的峰值轮胎频率低2~3 Hz，基于此特征给出轮胎气压的结果。实车测试结果表明，该算法可以剔除发动机转动对轮速的影响，既可以保证在单轮、两轮和三轮欠压的识别准确性，也可以准确识别四轮同时欠压的情况，可识别工况增加约18%，对发送机转速在一定范围内时对轮胎共振产生影响的工况识别精度提高约25%，相比于传统间接式胎压监测可以更准确和及时得告知驾驶员避免轮胎爆胎风险。 |
| 英文摘要: |
| To address the current issues of low accuracy and misidentification in indirect tire pressure monitoring systems (iTPMS) when detecting underinflation in all four wheels simultaneously, as well as the misidentification caused by engine vibrations, a study was conducted on the wheel speed spectral characteristics generated by road excitation. An indirect tire pressure monitoring algorithm based on wheel speed sensors and onboard hardware is proposed to improve the accuracy of underinflated tire identification. First, the wheel speed signal is preprocessed through signal denoising and gear error filtering to eliminate the issues of gear skipping and multi-tooth interference. The gear ring error is corrected using the recursive least squares (RLS) method. Then, combined with the analysis of tire vibration characteristics, the fast fourier transform (FFT) method is used to obtain the spectral characteristics of the wheel speed. Band-pass filters (BSP) and notch filters (NF) are applied to acquire the wheel speed spectral characteristics within a specified range, eliminating the influence of engine rotation. The tire pressure status is determined by the resulting resonance frequency peaks, where the peak frequency of an underinflated tire is 2~3 Hz lower than that of a normally inflated tire. Based on this characteristic, the tire pressure result is provided. Real vehicle test results indicate that this algorithm can eliminate the impact of engine rotation on wheel speed, ensuring the identification accuracy of single, dual, and triple underinflated wheels, as well as accurately identifying simultaneous underinflation in all four wheels. The condition recognition capability increases by approximately 18%, and the accuracy of identifying conditions where engine speed affects tire resonance improves by about 25%. Compared to traditional indirect tire pressure monitoring, this algorithm can more accurately and promptly inform the driver to avoid the risk of tire blowouts. |
| 查看全文 查看/发表评论 下载PDF阅读器 |
|
|
|
