Battery state of charge (SOC) estimation is a crucial function of battery management systems (BMSs), since accurate estimated SOC is critical to ensure the safety and reliability of electric vehicles. A widely used technique for SOC estimation is based on online inference of battery open circuit voltage (OCV). Low-current OCV and incremental OCV tests are two common methods to observe the OCV-SOC relationship, which is an important element of the SOC estimation technique. In this paper, two OCV tests are run at three different temperatures and based on which, two SOC estimators are compared and evaluated in terms of tracking accuracy, convergence time, and robustness for online estimating battery SOC. The temperature dependency of the OCV-SOC relationship is investigated and its influence on SOC estimation results is discussed. In addition, four dynamic tests are presented, one for estimator parameter identification and the other three for estimator performance evaluation. The comparison results show that estimator 2 (based on the incremental OCV test) has higher tracking accuracy and is more robust against varied loading conditions and different initial values of SOC than estimator 1 (based on the low-current OCV test) with regard to ambient temperature. Therefore, the incremental OCV test is recommended for predetermining the OCV-SOCs for battery SOC online estimation in BMSs.