The simplified lateral dynamic models of front and rear tires are proposed with lateral tire force information in this paper. The regression models of the recursive least squares (RLS) with forgetting factors and constraints are constructed based on simplified lateral dynamic models for estimating tire cornering stiffness. In addition, a nonlinear observer of sideslip angle is designed for four-in-wheel-motor-driven electric vehicles (FIWMD-EVs) with the estimated information on tire cornering stiffness. Sideslip angle can be estimated through a first-order Stirling's interpolation filter (DD1-filter) and a firstorder low-pass filter. The reliability, feasibility, effectiveness, and practicality of simplified lateral dynamic models are verified by contrast simulation experiments. The simplified lateral dynamic models of front and rear tires are not influenced on the change of sideslip angle, nor influenced by each other. Moreover, it can result in improving computation speed that computational burden is reduced after simplifying lateral dynamic models. With the estimated information above mentioned, sideslip angle is also estimated well. The estimated information on tire cornering stiffness and sideslip angle is benefit to the design of lateral stability control system, which can make vehicle adapt to different road conditions and control the steering motion attitude of vehicle in future works.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.