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The commercial vehicle is widely used in the overland transport. A prediction is given on the 9th annual China automotive industry forum that the number of the global commercial vehicles will reach eight million by the year of 2016. However, since the distance between its gravity centre and the ground is larger than that of the passenger vehicle, considering its comparatively short wheelbase, the rollover accident, which is fatal to the drivers and always makes enormous loss of merchandises, easily occurs in the case of commercial vehicles. As the number of the commercial vehicle is increasing fast, the accidents will occur more frequently, the losses will be increasingly enormous. To solve the problem, many researches about rollover early warning systems have been done. In most cases, it is assumed that the references of the vehicle are given.

In order to improve the braking energy recovery, a parallel hybrid electric bus simulation model with electric braking system (EBS) was established by co-simulation platform for the TruckSim and Matlab/Simulink in this paper. EBS makes the front and rear shaft braking force arbitrarily distributed, which is more effective to improve the rate of energy recovery and the braking stability. A braking force distribution algorithm for hybrid electric bus based on EBS was designed in this paper. Under the premise to meet the driver's needs and the ECE regulations, this braking force distribution method focuses on making the braking force distribute to the drive shaft to a maximum extent, so as to obtain the maximum energy recovery rate by the utilization of the motor regenerative braking. At last, the simulation in different operating conditions was used to analyze the braking energy utilization and the braking performance based on the simulation model.

Taking a good longitudinal braking performance on flat and level road of tractor and semi-trailer combination as a target, in order to achieve an ideal braking force distribution among axles, while the vehicle deceleration is just depend on the driver's intention, not affected by the variation of semi-trailer mass, the paper proposes a model based vehicle mass identification and braking force distribution strategy. The strategy identifies the driver's braking intention via braking pedal, estimates semi-trailer's mass during the building process of braking pressure in brake chamber, distributes braking force among axles by using the estimated mass. And a double closed-loop regulation of the vehicle deceleration and utilization adhesion coefficient of each axle is presented, in order to eliminate the bad effect of mass estimation error, and enhance the robustness of the whole algorithm. A simulation is conducted by utilizing MATLAB/Simulink and TruckSim.

Heavy vehicles have the characteristics of with high center of gravity position, large weight and volume, wheelbase is too narrow relative to the body height and so on, so that they always prone to rollover. In response to the above heavy security problems of heavy vehicle in running process, this paper mainly analyzes roll stability and yaw stability mechanism of heavy vehicles and studies the influence of vehicle parameters on stability by establishing the vehicle dynamics model. At the same time, this paper focuses on heavy vehicles stability control methods based on simulation and differential braking technology. At last, verify the effect of heavy vehicle stability control by computer simulation. The results shows that self-developed stability control algorithm can control vehicle stability effectively, so that the heavy vehicles instability can be avoided, the vehicle driving safety and braking stability are improved.

Aiming at estimating the vehicle mass and the position of center of gravity, an on-line two-stage estimator, based on the recursive least square method, is proposed for buses in this paper. Accurate information of the center of gravity position is crucial to vehicle control, especially for buses whose center of gravity position can be varied substantially because of the payload onboard. Considering that the buses start and stop frequently, the first stage of the estimator determines the bus total mass during acceleration, and the second stage utilizes the recursive least-square methods to estimate the position of the center of gravity during braking. The proposed estimator can be validated by the co-simulation with MATLAB/Simulink and TruckSim software, simulation results exhibit good convergence and stability, so the center of gravity position can be estimated through the proposed method in a certain accuracy range.