In this paper, an enabling multi-sensor fusion-based longitudinal vehicle speed estimator is proposed for four-wheel-independently-actuated electric vehicles using a Global Positioning System and Beidou Navigation Positioning (GPS-BD) module, and a low-cost Inertial Measurement Unit (IMU). For accurate vehicle speed estimation, an approach combing the wheel speed and the GPS-BD information is firstly put forward to compensate for the impact of road gradient on the output horizontal velocity of the GPS-BD module, and the longitudinal acceleration of the IMU. Then, a multi-sensor fusion-based longitudinal vehicle speed estimator is synthesized by employing three virtual sensors which generate three longitudinal vehicle speed tracks based on multiple sensor signals. Finally, the accuracy and reliability of the proposed longitudinal vehicle speed estimator are examined under a diverse range of driving conditions through hardware-in-the-loop tests. The results show that the proposed method has high estimation accuracy, robustness, and real-time performance.

Longitudinal Vehicle Speed Estimation for Four-Wheel-Independently-Actuated Electric Vehicles Based on Multi-Sensor Fusion

In this paper, a review on road friction virtual sensing approaches is provided. In particular, this work attempts to address whether the road grip potential can be estimated accurately under regular driving conditions in which the vehicle responses remain within low longitudinal and lateral excitation levels. This review covers in detail the most relevant effect-based estimation methods; these are methods in which the road friction characteristics are inferred from the tyre responses: tyre slip, tyre vibration, and tyre noise. Slip-based approaches (longitudinal dynamics, lateral dynamics, and tyre self-alignment moment) are covered in the first part of the review, while low frequency and high frequency vibration-based works are presented in the following sections. Finally, a brief summary containing the main advantages and drawbacks derived from each estimation method and the future envisaged research lines are presented in the last sections of the paper.

Road Friction Virtual Sensing: A Review of Estimation Techniques with Emphasis on Low Excitation Approaches

This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established Second, a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency

Decentralized Dynamic Event-Triggered Communication and Active Suspension Control of In-Wheel Motor Driven Electric Vehicles with Dynamic Damping

A combining sliding mode control approach for electric motor anti-lock braking system of battery electric vehicle

Lateral stability integrated with energy efficiency control for electric vehicles

Control of regenerative braking systems for four-wheel-independently-actuated electric vehicles

A novel nonlinear observer for the estimation of vehicle velocity together with the tire-road friction coefficient is presented in this paper. The modular observer is designed based on a longitudinal tire force estimation approach and a lateral tire friction model. Compared to the state-of-art methods, the proposed observer design provides accurate estimation of the longitudinal velocity, lateral velocity, and the tire-road friction coefficient simultaneously. Particularly, the longitudinal tire forces are first estimated based on a filter observer. Then, according to the calculation of lateral tire forces, the nonlinear observer is proposed to estimate vehicle velocity and the tire-road friction coefficient. Moreover, the stability property of the observer is analyzed using a Lyapunov-based method. Simulation results validate the effectiveness of the proposed method.

Observer-based estimation of velocity and tire-road friction coefficient for vehicle control systems

A hierarchical controller is proposed for simultaneous lateral stability and energy efficiency control of over-actuated electric vehicles (EVs), Particularly, the designed controller consists of an upper-level lateral stability controller and a lower-level torque control allocation (CA) controller. At the upper-level, the stability control problem is formulated as a constrained tracking problem based on a reference model, and solved by a model predictive control (MPC) method. At the lower-level, a torque CA strategy based on the efficiency function of the in-wheel motor of EVs is proposed to decrease the energy consumption with guaranteed lateral stability. Compared with a holistic approach, solving the problem hierarchically reduces the computational complexity. Simulation results demonstrate the effectiveness of the designed hierarchical controller in lane change scenarios with different road friction-coefficients.

Simultaneous Lateral Stability and Energy Efficiency Control of Over-Actuated Electric Vehicles

A novel nonlinear observer is presented in this paper for the estimation of vehicle velocity together with the tire-road friction coefficient based on a longitudinal tire force observer and a lateral tire friction model. First, the longitudinal tire forces are estimated based on a filter observer. Then, according to the calculation of lateral tire forces, a nonlinear observer is designed to estimate vehicle velocity and the tire-road friction coefficient. Moreover, stability properties are analyzed using a Lyapunov-based method. Simulation results validate the effectiveness of the proposed method.

Yan Ma

Papers

Control of regenerative braking systems for four-wheel-independently-actuated electric vehicles

Lateral stability integrated with energy efficiency control for electric vehicles

Observer-based estimation of velocity and tire-road friction coefficient for vehicle control systems

Simultaneous Lateral Stability and Energy Efficiency Control of Over-Actuated Electric Vehicles

Nonlinear observer for vehicle velocity and tire-road friction coefficient estimation