A suspension achieves the vibration isolation induced by the road through different mechanisms to improve ride comfort or road holding of a vehicle. Different suspension technologies are present in the automotive industry: passive, semi-active, and active. The characteristics of these major types of suspension are briefly explained, including an explanation of the quarter-car model, which is widely used in suspension technology research. This paper focuses on the compilation, description, and comparison of different control theories researched in the literature, such as classical, optimal, and robust control, and distinctive characteristics for each one are discussed and compared in the context of vehicle dynamics. Finally, the analysis for each control comfort-oriented strategy is discussed in this paper.

Modern powertrain configurations for electric vehicles introduce the possibility to actuate the wheel directly by means of in-wheel motors. These machines enable stiffer and more efficient traction, with the possibility of introducing pitch motion control due to the intrinsic coupling between longitudinal, vertical, and pitch dynamics. This paper proposes a pitch rate attenuation control exploiting a Lyapunov function that attempts to cancel the pitch rate dynamics from the model. Unlike previous works, this pitch control is performed exclusively with the traction machine; it does not rely on controllable suspension systems. The controller formulation guarantees global stability of the vehicle. Furthermore, it considers the nonlinearity of the plant introduced by the dependency on the pitch angle. To facilitate the feedback of the road profile needed by the Lyapunov controller, two Kalman filters are included in the control law. This work implements the described strategy on a half car model. Simulations examine different speed and road conditions. It is demonstrated that the control strategy can blend longitudinal and pitch rate attenuation torque commands using a rear in-wheel motor, attaining a reduction of up to $41\%$ for chassis pitch rate and $36\%$ for pitch acceleration.

The electrification trend characterizing the current automotive industry creates opportunities for the implementation of innovative functionalities, enhancing aspects of energy efficiency and vehicle dynamics. Active vehicle suspensions are an important subsystem in this process. To enable proper suspension control, vehicle sensors can be used to measure the system’s response and, in some cases, preview the road conditions and the presence of possible obstacles. When assessing the performance of a suspension system, the speed bump crossing represents a challenging maneuver. A suitable trade-off between comfort and road holding must be found through different phases of the profile. The proposed work uses a fixed-gain observer obtained from Kalman filtering to identify road unevenness and adapt the control strategy when the vehicle travels through a bump. To this end, the obstacle is identified through the use of affordable sensors available in high-end vehicles: accelerometers, inertial measurement units, and stroke sensors. The proposed technique is also affordable from the computational point of view, thus enabling its use in common microprocessors tailored for the automotive field. The bump identification technique is validated through experimental data captured in a vehicle demonstrator. Subsequently, numerical results show that the proposed technique is able to enhance comfort while keeping road holding and attenuating the transient after taking the bump.