Direct Yaw‐Moment Control of All‐Wheel‐Independent‐Drive Electric Vehicles with Network‐Induced Delays through Parameter‐Dependent Fuzzy SMC Approach

Abstract

This paper investigates the robust direct yaw-moment control (DYC) through parameter-dependent fuzzy sliding mode control (SMC) approach for all-wheel-independent-drive electric vehicles (AWID-EVs) subject to network-induced delays. AWID-EVs have obvious advantages in terms of DYC over the traditional centralized-drive vehicles. However it is one of the most principal issues for AWID-EVs to ensure the robustness of DYC. Furthermore, the network-induced delays would also reduce control performance of DYC and even deteriorate the EV system. To ensure robustness of DYC and deal with network-induced delays, a parameter-dependent fuzzy sliding mode control (FSMC) method based on the real-time information of vehicle states and delays is proposed in this paper. The results of cosimulations with Simulink® and CarSim® demonstrate the effectiveness of the proposed controller. Moreover, the results of comparison with a conventional FSMC controller illustrate the strength of explicitly dealing with network-induced delays.

Direct Yaw-Moment Control of 4-Wheel-Independent-Drive Electric Vehicle with Network-Induced Delays through Data-reduction Techniques

“…As indicated in [6,7], there are 4 messages containing control commands from the vehicle controller to four motor controller respectively, which will obviously cause the network delays, in order to mitigate the adverse impact caused by the network delays and utilize the limited bandwidth, we assemble the 4 control messages for four motor controller into one message using eight bytes data, two bytes data that is 16 bits will be enough to represent the torque for any motor in vehicle.…”

“…To ensure robustness of DYC and deal with network-induced delays, [6] presented a parameter-dependent fuzzy sliding mode control method based on the real-time information of vehicle states and delays. To reduce the adverse impact of message time-delays in networked control systems, varieties of methods have been developed to maximally utilize the limited network bandwidth, and message scheduling is a very important one.…”

“…As shown in Figure 1, a two-degree-of-freedom (2-DOF) vehicle model is used in the paper, where CG is the center of gravity; m is the vehicle mass; I z is the vehicle yaw inertia; M z is the yaw moment; F xf and F xr are the longitude tire forces of front and rear wheels, respectively; F yf and F yr are the lateral tire forces of front and rear wheels, respectively; α f and α r are the slip angle of front and rear wheels, respectively. With the 2-DOF vehicle model, the state space formulation of controloriented vehicle lateral dynamics model for DYC of 4WID-EV is expressed as follows [6][7][8]: C r and c f are the cornering stiffness of the rear and front tires, respectively. In vehicle lateral motion control, the desired sideslip angle is generally selected to be zero to ensure vehicle stability, while the desired yaw rate is usually defined to ensure good handling performance.…”

“…In vehicle lateral motion control, the desired sideslip angle is generally selected to be zero to ensure vehicle stability, while the desired yaw rate is usually defined to ensure good handling performance. A widespread expression of the desired yaw rate is described as [6][7][8] In this paper, only the case that the network induced time delays are less than the control cycle period T s , which commonly occurs in most networked control systems, in the network control system (NCS) of DYC for 4WID-EV, the sensor node periodically samples the vehicle states with fixed period T s , the controller node and the actuator node operate in event-driven mode which means a task will be immediately implemented once a message arrives via CAN, and the task implementation time in each node is ignored. Without considering network-induced delays, the NCS of DYC for 4WID-EV runs like an ideal centralized control system with fixed sampling period .…”

Speed Synchronization Control of Integrated Motor–Transmission Powertrain over CAN through Active Period-Scheduling Approach

“…Generally, their structures can be classified into two categories: centralized motor-driven and distributed motor-driven [1][2][3]. According to the research [1,4], as a novel configuration, distributed motor-driven EVs have advantages in terms of vehicle motion control, energy optimization, and structural flexibility [4][5][6]. However, centralized motor-driven EVs are still mainstream in the current market due to their better inheritance to conventional vehicles.…”