The method of yaw model is used to establish aerodynamic property of heavy truck in computational fluid dynamics and wind tunnel test. A model of multi-body system simulation for heavy truck is built based on design and measure data from body, driving system, steering system, braking system, and powertrain system with TruckSim. Aerodynamic reference point of Society of Automotive Engineers (SAE) and aerodynamic coefficients are as the interface to integrate computational fluid dynamics and multi-body system simulation. A sudden and discontinuous direction change of crosswind is set up in multi-body system simulation, and dynamic performance of the heavy truck is performed by open-loop and closed-loop simulation. Under the given simulation case, lateral offset of the truck for open-loop simulation is 1.55 m and more than that for closed-loop simulation; the roll rate range of both simulations is −1.49°/s to 1.695°/s, the range of lateral acceleration is −0.497 m/s² to 0.447 m/s² in open-loop simulation, the range of lateral acceleration is −0.467 m/s² to 0.434 m/s² in closed-loop simulation; the range of yaw rate is −1.36°/s to 1.284°/s in open-loop simulation, the range of yaw rate is −0.703°/s to 0.815°/s in closed-loop simulation. The results show that combined simulation of the heavy truck stability can be completed by computational fluid dynamics and multi-body system software under sudden and discontinuous direction change of crosswind.

A time domain analysis method of ride comfort and energy dissipation characteristics is proposed for automotive vibration proportional–integral–derivative (PID) control. A two-degrees-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined, and the Routh stability criterion method was introduced to assess the impact of PID control on vehicle stability. The PID control parameters are tuned using the differential evolution algorithm, and to improve the algorithm’s adaptive ability, an adaptive operator is introduced, so that the mutation factor of differential evolution algorithm can change with the number of iterations. The PID control parameter optimization method presented in this article is versatile and can be used to optimize PID control parameters under different conditions. This article provides the results of PID control parameter optimization under different conditions. Based on PID control and its parameter tuning, a time domain solution method for two types of vibration response variables, their root mean square values, and the average power of energy consumption vibration of automotive vibration PID control is proposed. Two kinds of simulation test schemes are designed under urban driving conditions, which are commonly used Class B road and pulse road, with a commonly used vehicle speed of 60 km/h. The ride comfort and energy dissipation characteristics of passive suspension and PID control are compared. The results show that introducing energy consumption vibration response variables as a supplement to the conventional vibration response variables is beneficial for expanding the research and application scope of the automotive vibration and its control; with the sprung mass acceleration deviation as the control input, PID control can effectively improve the vehicle ride comfort, but it makes the vibration energy dissipation characteristics worse.

This research aims to develop a new ride comfort simulation technology for a three-axle heavy vehicle. To consider the elasticity of the frame, the finite element method (FEM) is used to analyze the free mode of the frame, and the elastic information of the frame is obtained. Based on the theory of rigid-elastic synthesis, a 17-degree-of-freedom (DOF) spatial rigid-elastic model of a three-axle heavy vehicle is established. The pseudo-excitation method (PEM) is adopted to improve the efficiency of the solution, thereby solving this problem. The pseudo road excitation is constructed, the pseudo responses of the vibration system and the response variables are derived, and the power spectral densities (PSDs) and the root mean square (RMS) values of the responses are deduced. Twenty response variables are used, including accelerations, suspension dynamic deflections, and relative dynamic loads of wheels, whose PSDs and RMS variables are used as evaluation indexes. Finally, a comparative study of ride comfort simulation is conducted. A comparison of the simulation results of the rigid-elastic and rigid models indicates that the elasticity of the frame considerably influences the ride comfort of the heavy vehicle and hence cannot be ignored in the study of this issue. Meanwhile, a comparison of the results of PEM and the Fourier method for the spatial rigid-elastic model of the three-axle heavy vehicle shows that PEM is accurate yet simpler and more efficient than the Fourier method. Therefore, the innovative simulation technology proposed in this work is practical and efficient and can reflect the essence of the problem.

This paper presents a gain scheduling output feedback control method to reduce driver workload and improve driving performance by considering input saturation. The driver–vehicle system model is developed by considering tire cornering stiffness uncertainties and different driver parameter uncertainties. Meanwhile, the input saturation is also considered in the driver-vehicle system. A quadratic Lyapunov function is designed to solve the optimization problem with uncertainties and input saturation. The results, which are based on the MATLAB-CarSim co-simulation platform, indicate that the robust controller not only improves the convergence rate of the state but also reduces the steering workload of the driver.