This content is not included in your SAE MOBILUS subscription, or you are not logged in.
A Nonlinear Slip Ratio Observer Based on ISS Method for Electric Vehicles
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors. Instead of estimating vehicle speed, the proposed method employs the estimated error of motor torque as the correction output by taking the advantage of electric vehicles that the torque of the driving motors can directly reflect the tire force. Also vehicle acceleration is directly used as a time-varying parameter of the system to reflect the longitudinal dynamic characteristics of the vehicle. The error dynamics is input-to-state stable subject to the disturbances, such that the nonlinear longitudinal characteristics of each tire can be effectively dealt with. Some extensive simulation has been conducted to verify the proposed slip ratio observer with an AMESim-based electric vehicle model. The results show that the designed nonlinear slip ratio observer has the better performance compared with the conventional EKF method.
CitationRen, B., Deng, W., Chen, H., and Wang, J., "A Nonlinear Slip Ratio Observer Based on ISS Method for Electric Vehicles," SAE Technical Paper 2018-01-0557, 2018, https://doi.org/10.4271/2018-01-0557.
Data Sets - Support Documents
|[Unnamed Dataset 1]|
|[Unnamed Dataset 2]|
|[Unnamed Dataset 3]|
- Ivanov, V.,Savitski, D., andShyrokau, B. , “A Survey of Traction Control and Antilock Braking Systems of Full Electric Vehicles with Individually Controlled Electric Motors,” IEEE Transactions on Vehicular Technology 64(9):3878-3896, 2015.
- Gao, H. et al. , “Tracking Control of WMRs on Loose Soil Based on Mixed H2/H∞ Control with Longitudinal Slip Ratio Estimation,” Acta Astronautica 140:49-58, 2017.
- Sakai, S.-i. andHori, Y. , “Advantage of Electric Motor for Anti-Skid Control of Electric Vehicle,” European Power Electronics and Drives 11(4):26-32, 2001.
- Itou, K. et al. , “A Study of Novel Traction Control Method for Electric Motor Driven Vehicle,” SAE Technical Paper 2009-26-0039 , 2009, doi:10.4271/2009-26- 0039.
- MLALi, J. et al. , “Wheel Slip Control Using Sliding-Mode Technique and Maximum Transmissible Torque Estimation,” Journal of Dynamic Systems Measurement & Control 137(11), 2015.
- Suzuki, T. andFujimoto, H. , “Slip Ratio Estimation and Regenerative Brake Control without Detection of Vehicle Velocity and Acceleration for Electric Vehicle at Urgent Brake-Turning,” IEEE International Workshop on Advanced Motion Control IEEE 273-278, 2010.
- Fujii, K. et al. , “Experimental Verification of Traction Control for Electric Vehicle Based on Slip Ratio Estimation without Vehicle Speed Detection,” JSAE Review of Automotive Engineers 29:369-373, 2008.
- Zhang, Y. et al. , “Slip Ratio Estimation for Electric Vehicle with in-Wheel Motors Based on EKF without Detection of Vehicle Velocity,” Control and Decision Conference IEEE 4427-4432, 2016.
- Rajamani, R. , “Vehicle Dynamics and Control,” (Springer Science & Business Media, 2011).
- Pacejka, H. , “Tire and Vehicle Dynamics,” (Elsevier, 2005).
- Krstic, M.,Kanellakopoulos, I., andKokotovic, P.V. , “Nonlinear and adaptive control design,” (Wiley, 1995).
- Sontag, E.D. , “Input to State Stability: Basic Concepts and Results,” . In: Nonlinear and optimal control theory. (Berlin Heidelberg, Springer, 2008), 163-220.
- Gao, B. et al. , “A Reduced-Order Nonlinear Clutch Pressure Observer for Automatic Transmission,” IEEE Transactions on Control Systems Technology 18(2):446-453, 2010.