Vehicle sideslip is a valuable measurement for ground vehicles in both passenger vehicle and racing contexts. At relevant speeds, the total vehicle sideslip, beta, can help drivers and engineers know how close to the limits of yaw stability a vehicle is during the driving maneuver. For production vehicles or racing contexts, this measurement can trigger Electronic Stability Control (ESC). For racing contexts, the method can be used for driver training to compare driver techniques and vehicle cornering performance. In a fleet context with Connected and Autonomous Vehicles (CAVS) any vehicle telemetry reporting large vehicle sideslip can indicate an emergency scenario. Traditionally, sideslip estimation methods involve expensive and complex sensors, often including precise inertial measurement units (IMUs) and dead reckoning, plus complicated sensor fusion techniques. Standard GPS measurements can provide Course Over Ground (COG) with quite high accuracy and, surprisingly, the most challenging measurement is the vehicle orientation.
This study presents a low- or moderate-cost method for real-time vehicle sideslip estimation using Real-Time Kinematic (RTK) Global Position System (GPS) receivers. The approach involves a pair of specialized GPS receivers with a moving base and moving rover RTK setup. RTK corrections are provided via an online wireless internet connection. The moving base is positioned at the vehicle's rear axle and the companion rover GPS device is located at the vehicle's center of gravity (CG). This arrangement provides both vehicle orientation and vehicle course over ground at 7Hz. RTK provides direct measurement of both quantities needed to compute vehicle sideslip in real time. The results demonstrate the feasibility of this approach and offers a practical solution for real-world automotive systems. A simple set of driving experiments demonstrate the method’s effectiveness. This approach is a cost-effective solution for sideslip estimation, with applications in ESC, CAVs, driver training and motorsports performance analysis.