Improved Particle Filter Using Clustering Similarity of the State Trajectory with Application to Nonlinear Estimation: Theory, Modeling, and Applications

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="7"><hr/></td></tr><tr class="thead"><td class="align_left">Battery ID</td><td class="align_center">Experimental platform</td><td class="align_center">Temperature</td><td class="align_center">Charging</td><td class="align_center">End condition</td><td class="align_center">Discharge</td><td class="align_center">End condition</td></tr><tr><td class="thead-hr" colspan="7"><hr/></td></tr><tr><td class="align_left">M8</td><td class="align_center">Arbin BT2000</td><td class="align_center">20-25°C</td><td class="align_center">Constant current/voltage</td><td class="align_center">4.2 V/0.05 A</td><td class="align_center">Constant current</td><td class="align_center">2.7 V</td></tr><tr class="table-tr"><td colspan="7"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Experimental test conditions of CALCE dataset M8.</div>

Journal of Sensors

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Table 4

Table 4: Improved Particle Filter Using Clustering Similarity of the State Trajectory with Application to Nonlinear Estimation: Theory, Modeling, and Applications 

Table 4 | Improved Particle Filter Using Clustering Similarity of the State Trajectory with Application to Nonlinear Estimation: Theory, Modeling, and Applications 