Abstract Electric vehicles (EVs) have been gaining a lot of focus and attention as they run clean and are environment friendly. EVs use in-hub motors, which can be independently controlled, improving this way the maneuverability and allowing augmented control actions. This paper discusses the development of a Model Predictive Controller (MPC) to improve vehicle handling characteristics. Wheel torques are independently controlled using direct yaw moment and side slip control method to pro-actively improve vehicle handling. At high values of side slip the steering is no more capable of generating yaw moment and vehicle becomes laterally unstable. By unequal torque distribution a restoring yaw moment is generated and vehicle stability is ensured. The MPC computes the optimal couple traction/braking torque of the four in-wheel motors, from basic driving slogans, which are, steering angle and desired speed. The reference trajectories of yaw rate and side slip angle are also inputted in the controller. The controller output is four wheel torques which are fed to the vehicle. The vehicle is modelled in ADAMS-Car® to incorporate nonlinear suspension dynamics, compliance effects, roll and pitch motions, sophisticated tire model, etc. which are the major limitations of a single track bicycle model. The vehicle model is exported in state space form to the MATLAB® environment to be integrated with the control model. The controller is able to track the reference yaw rate and desired trajectory with negligible side slip. Simulation results with control application have been discussed for a lane change event. Introduction Direct yaw moment control (DYC) is one of the modern active safety assist system introduced to control vehicle directional stability. At high values of lateral acceleration tire force approaches the adhesion limit and vehicle side-slip angle grows. As a result, the steering is no more capable of generating the desired yaw moment. This is been discussed by Shibahata et al., 1993 ([ 1]). The vehicle becomes laterally unstable as the yaw moment decreases at high values of side slip. Significant amount of research has been done in order to generate a restoring moment by differential braking also known as ESC (Electronic Stability Control) ([ 2]), Torque vectoring ([ 3]) and using 4WS (Four wheel steering) (Abe, 1999 [ 4]; Selby et al., 2001 [5]). With the advent of electric motor drives it became easy to directly control the torque given to the wheels and to generate the yaw moment by providing unequal torques to left and right wheels. The advantage of these motor drives is quick response time and reduced system complexity. Generally, yaw rate and side-slip angle are chosen as control variables for such direct yaw control systems ([6, 7, 8]). Different control designs primarily differ in control architecture. Various researchers have used different control theories like Optimal control [ 9], Model Predictive Control [ 10], Fuzzy control [ 11], LQR control [ 12], etc. We used MPC for direct yaw control. The reason for using MPC is the fact that it allows the optimization of the current timestep while keeping future timesteps into account. MPC has the ability to predict future output and takes control actions accordingly while PID, LQR and other optimal controllers cannot predict the future outputs. Vehicle and control model development is discussed in adjoining sections. Vehicle Model The mathematical model capable of simulating dynamic behavior of the vehicle has been developed in ADAMS-Car® ([ 13]), a multi-body dynamics simulation package widely used by suspension designers in automotive industry. It is a virtual prototype software which includes various interfaces for modelling, equation solving, optimization, simulation and visualizing aids. The vehicle used for the study is a FOX vehicle mounted on the chassis of a racing car Silver Car S2. The chassis is being modified for the placeme