The suspension system with variable damping and variable stiffness actuators can
realize four-quadrant mechanical output, effectively combining the energy
efficiency of the semi-active suspension with the performance levels approaching
those of active suspensions. However, the practical effectiveness of this system
depends heavily on the ability of the control strategy to adapt to different
driving conditions. In order to meet this challenge, this research has developed
a multi-mode suspension collaborative control strategy to optimize energy
efficiency and ride comfort in various operating scenarios. Based on the
four-quadrant characteristics of the actuator, a suspension mode switching
framework has been established, and the suspension work is divided into passive,
semi-active, pseudo-active and active modes. In order to determine the
appropriate switching boundary, first calculate the root mean square (RMS) value
of the sprung mass acceleration and suspension dynamic deflection under passive
conditions. With the existing human comfort sensitivity as a reference, the
switching threshold of sprung mass acceleration is 0.527 m/s2, and
the switching threshold of suspension dynamic deflection is
8.31×10−3m, and the corresponding conversion rules are formulated.
Then, the LQR controller optimized by the genetic algorithm is used to allocate
the control force adaptively according to the suspension mode to realize
cooperative multi-mode operation. The simulation results on B-D composite road
surfaces show that compared with traditional passive suspension, this method can
reduce the sprung mass acceleration, suspension dynamic deflection and tire
dynamic load by 10.59%, 16.65% and 32.9% respectively. These results confirm
that the collaborative control strategy significantly improves the ride comfort,
vehicle adaptability and overall performance in complex road conditions.