A hierarchical control framework is applied for the distributed cooperative vehicular platoon using vehicular ad-hoc networks. The parameter-space-approach-based cooperative adaptive cruise control (CACC) controller is proposed to guarantee the D-stability and the string stability considering the influence of the communication time delay and time lag of vehicular dynamic performance. This CACC controller combines the feedforward loop of the acceleration of the preceding vehicle with the feedback loop of the following errors, in which the gain of the feedforward loop is designed to decrease matching errors and the gains of the feedback loop are selected from the feasible region in the parameter space. To verify the effectiveness of the CACC controller, a six-vehicle platoon with a simplified vehicular dynamic is simulated under speed-up and stop scenarios. The simulation results demonstrate that the disturbance is attenuated along with the platoon and the following errors are convergent with well-designed convergent performance. A CarSim/Simulink co-simulation is designed to further verify the effectiveness of the hierarchical control framework and the rationality of the CACC controller in the real vehicular platoon application. The simulation results under the highway fuel economy test drive cycle show that the CACC controller improves the drive comfort and significantly decreases the following errors.

In this paper, a discrete tire model of cornering properties for road vehicles relating to tire grip performance, which is important for driving stability and safety, is presented. The proposed tire model combines realistic rubber friction related to velocity and tire grip performance with deformation of the carcass. The model can describe the stress and strain of the carcass and tread, and the rubber friction coefficient at each point of the contact patch, which is affected by the distribution of the slip velocity. Meanwhile, the model incorporates the effects of the viscoelastic rubber material and power spectrum of the road, which are explicitly reflected in the rubber friction model. First, an improved rubber friction model based on the Persson theory of rubber friction is introduced in this paper. A discrete analytical tire model, which considers carcass compliance and the discretization of the tread, is then proposed. In addition, important phenomena of tire properties arising from the carcass compliance and rubber friction are analyzed and the effectiveness of the discrete analytical tire model is validated experimentally. The proposed model provides a new way to optimize the grip performance of a tire by adjusting the tire or rubber physical parameters even before the tire is made.

The water medium hydraulic retarder is the latest type of auxiliary braking device and has the characteristics of high power density, large braking torque, and compact structure. During traveling, this device can convert the kinetic energy of a vehicle to the heat energy of the cooling liquid and replace the service brake under non-emergency braking conditions. With regard to the constant-speed function of the water medium hydraulic retarder, this study designs a controller based on the neural network proportional–integral–derivative (PID) algorithm to achieve the steady traveling of the vehicle at constant velocity during a downhill course by controlling the flling ratio of the water medium hydraulic retarder. To validate the algorithm’s efectiveness, the dynamic model of the heavy-duty vehicle in the downhill process and the physical model of the water medium hydraulic retarder are developed. Three operating conditions, including a fxed slope, step-changing slope, and continuous changing slope, are set, and a simulation test is carried out in the MATLAB/Simulink environment. The neural network PID algorithm has better adaptability in controlling than the traditional PID algorithm. Thus, it controls the water medium hydraulic retarder such that the braking requirements of heavy-duty vehicles under a changing slope working condition are satisfed, and it performs constant-speed control when the vehicle travels downhill. Therefore, the proposed control method can signifcantly improve the safety of road trafc.

Rollover of commercial heavy vehicles can cause enormous economic losses and fatalities. It is easier for such vehicles to
rollover if the driver’s steering frequency is close to the critical frequency of the vehicle’s roll motion; however, the critical
roll frequency has rarely been investigated. In this study, the second-order transfer function between the steering input and roll angle was developed to calculate the critical frequency of the vehicle’s roll motion. The simulated spectrum and transfer function were then used to dynamically predict the peak lateral load transfer ratio. Laboratory experiments were conducted using a scaled vehicle to verify the critical roll frequency. The results suggest that the peak value of the lateral load transfer ratio during steering can be accurately determined from the driver’s input, and the critical roll frequency has a dominant efect on the dynamic rollover of heavy vehicles.

A precise energy conversion factor is required to defne the impact of greenhouse gas emissions by gasoline-powered vehicles and policies that will guide the application of future eco-innovations. The current energy conversion factor adopted by many countries is based on the Willans line approach, initially proposed in 1888 for steam engines, later adapted for internal combustion engines. The actual energy conversion factor, which defnes the energy conversion for drivers in real trafc, is missing. In this article, eight world-class engines are tested in an engine bench for the acquisition of specifc fuel consumption 3D maps. Then, their energy conversion factors, calculated by dividing the energy output by the energy input, are simulated in real and urban trafc, acquired according to the real driving emissions (RDE) cycle. In addition, a reference vehicle is instrumented to measure the energy input (fuel fow) and the energy output (mechanical energy in the half axles) under the same RDE cycle standards. The results of both procedures are very similar, respectively, 0.405 ± 0.04 L/kWh for the simulation based on eight benchmark engines, and 0.392 ± 0.04 L/kWh for the reference vehicle driven in RDE trafc conditions, with a 95% confdence interval. For turbocharged engines, the factor attained by the simulation is 0.395 ± 0.04 L/kWh. The values of the energy conversion factor for gasoline engines got in this research are higher than those obtained through the Willans line approach, suggesting a new standard value of 0.405 L/kWh, replacing the current 0.264 L/kWh. It could substantially change the greenhouse gas emissions in a tank-to-wheel approach for the entire vehicle and add-on eco-innovations.