선택한 단어 수는 입니다.
최소 단어 이상 선택하여야 합니다.
최소 단어 이상 선택하여야 합니다.
선택한 단어 수는 30입니다.
최대 10 단어까지만 선택 가능합니다.
최대 10 단어까지만 선택 가능합니다.
제안 방법
- As already discussed three different DDCs including UDDS, HWFET and Japan 10-15 modes are applied to a Lithium battery and the data are acquired and stored in a PC. In the experiments, the UDDS profile is used for learning and validation of DNN while HWFET and Japan 10-15 DDCs are used to evaluate the performance of the DNN for SOC estimation. Fig.
- Three different Dynamometer Driving Cycles (DDCs) with some charging profiles are applied on a battery cell and the measured data are used to train and to validate the DNN. Three DDCs such as UDDS, HWFET and Japanese 10-15 SOC are selected to obtain the range of mean, power from the battery.
대상 데이터
- The Lithium battery cell used in the experiment is Samsung INR18650-29E, Nickel Manganese Cobalt Chemistry Li-ion battery, with a nominal capacity of 2.85Ah. Other specifications are shown in Table 2.
- Three different Dynamometer Driving Cycles (DDCs) with some charging profiles are applied on a battery cell and the measured data are used to train and to validate the DNN. Three DDCs such as UDDS, HWFET and Japanese 10-15 SOC are selected to obtain the range of mean, power from the battery. The UDDS is applied to a battery and the resulting data measured are used for DNN training at different ambient temperatures ranging from -20℃ to 60℃.
이론/모형
- In this paper a novel DNN based SOC estimation method for the Lithium batteries is proposed without the help of Kalman Filter or any other method. The voltage and current data obtained at different temperature are mapped to SOC.
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