Localization is a fundamental requirement for an autonomous vehicle system. One of the most often used systems for autonomous vehicle localization is the global positioning system (GPS). Nevertheless, the functionality of GPS is strongly dependent on the availability of satellites, making it unreliable in some situations. As a result, autonomous vehicles must possess autonomous self-localization capabilities to ensure their independent operation. Odometry techniques are employed to achieve vehicle localization by predicting the vehicle position and orientation based on sensor measurements of the vehicle motion. One of the approaches employed in odometry is known as wheel odometry. Wheel odometry has a lower degree of reliance on the surrounding environment than visual odometry and laser odometry. This study aims to evaluate the performance of wheel odometry implementation for an autonomous wheelchair in the context of the localization process. The differential drive kinematic model is employed to determine the predicted pose of a wheelchair. This prediction is derived from the measurement of the linear and angular velocity of the wheelchair. Several experiments have been conducted to evaluate the performance of wheel odometry-based localization. Prior to experimenting, calibration procedures have also been performed to ensure accurate measurements of the sensor.