蓄电池
蓄電池
축전지
CHINESE LABAT MAN
2014年
3期
133-137
,共5页
铅酸蓄电池%冲击激励%自由振荡%激振检测%自适应模糊推理%负载补偿%劣化程度%荷电状态
鉛痠蓄電池%遲擊激勵%自由振盪%激振檢測%自適應模糊推理%負載補償%劣化程度%荷電狀態
연산축전지%충격격려%자유진탕%격진검측%자괄응모호추리%부재보상%열화정도%하전상태
lead-acid battery%impact excitation%free oscillation%vibration detection technology%adaptive fuzzy reasoning%load compensation%SOH%SOC
文中所述检测系统基于激振过程动态跟踪铅酸蓄电池状态参数由于化学过程的变化,并进行实时计算、分析和判断,高精度量化和界定被测电池的劣化和荷电等性能指标,全程自适应确定目标和理想参数,并对其实行低损在线测试。检测过程中未对铅酸蓄电池进行大电流充放电,仅在铅酸蓄电池两端加上一个幅度较小、时间较短的冲击电压信号,所以对被测电池无损害,系统能量消耗较小;利用负载补偿方法,解决了负载对检测结果的影响,同时负载特性也得到改善,实现了在线检测;由于激振检测是基于自适应模糊推理模型实现的,该模型在输入量的选择方面综合考虑了多种因素对输出值的影响,从而实现了多种铅酸蓄电池全程电压自适应和高精度测试。
文中所述檢測繫統基于激振過程動態跟蹤鉛痠蓄電池狀態參數由于化學過程的變化,併進行實時計算、分析和判斷,高精度量化和界定被測電池的劣化和荷電等性能指標,全程自適應確定目標和理想參數,併對其實行低損在線測試。檢測過程中未對鉛痠蓄電池進行大電流充放電,僅在鉛痠蓄電池兩耑加上一箇幅度較小、時間較短的遲擊電壓信號,所以對被測電池無損害,繫統能量消耗較小;利用負載補償方法,解決瞭負載對檢測結果的影響,同時負載特性也得到改善,實現瞭在線檢測;由于激振檢測是基于自適應模糊推理模型實現的,該模型在輸入量的選擇方麵綜閤攷慮瞭多種因素對輸齣值的影響,從而實現瞭多種鉛痠蓄電池全程電壓自適應和高精度測試。
문중소술검측계통기우격진과정동태근종연산축전지상태삼수유우화학과정적변화,병진행실시계산、분석화판단,고정도양화화계정피측전지적열화화하전등성능지표,전정자괄응학정목표화이상삼수,병대기실행저손재선측시。검측과정중미대연산축전지진행대전류충방전,부재연산축전지량단가상일개폭도교소、시간교단적충격전압신호,소이대피측전지무손해,계통능량소모교소;이용부재보상방법,해결료부재대검측결과적영향,동시부재특성야득도개선,실현료재선검측;유우격진검측시기우자괄응모호추리모형실현적,해모형재수입량적선택방면종합고필료다충인소대수출치적영향,종이실현료다충연산축전지전정전압자괄응화고정도측시。
The detecting system, as stated in this paper is based on the vibration test procedure, dynamically following the electrochemical process of the lead-acid battery, and collects the real-time state parameters for calculation, analysis and judgment. It also quantizes precisely the degradation and chargeability of the battery and therefore self-adapts to the ideal target values. During the test, it has not charged and discharged large current to the lead-acid battery, it only plus a smaller and shorter time of impulse voltage signal on both ends of lead-acid battery, so the battery measured is damage free, and the system energy consumption is small; Using the load compensation technology, it has solved the inlfuence of load on the test results. What’s more, the load characteristics are improved at the same time, it realized the online detection. The vibration detection is based on the adaptive fuzzy inference model which has taken various factors into account, concerning the choices of input aspects which may influence the output value. It realized a number of lead-acid battery voltage self-adaption and accomplished a variety of high-precise tests.