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This paper describes a novel yaw stability control strategy for a four-wheel-independent-drive electric articulated bus with four motors at the middle and rear wheels. The proposed control strategy uses a hierarchical control architecture. In the upper layer, a 3 degree-of-freedom reference model is established to obtain the desired vehicle states and the desired yaw moments of the front and rear compartments are determined by means of sliding mode control, respectively. The lower layer distributes differential longitudinal forces according to the desired yaw moments based on quadratic programming theory. The tire utilization rate is used as the optimization goal considering the actual constraints. To verify performance, three test cases are designed on the dSPACE-ASM simulation platform. The test results show the proposed control strategy can improve the yaw stability and the trajectory following performance of the bus under different driving conditions.

The friction coefficient of road is the primary factor of the traction control system. In this paper, a real-time estimation of road coefficient based on the distributed driven electric vehicle is developed. The simplified quarter car model and the Burckhardt tire model are selected and optimized. The algorithm based on recursive least square with forgetting factor is used for road estimation. The test data under a wide range of road conditions are analyzed. The results show that the algorithm is able to estimate two surfaces: asphalt and ice road. The proposed approach has several advantages such as accurate, effective, short cycle and low cost. Also, it has the ability to provide with reliable information for vehicle active safety control.

As the key technology of electric vehicles(EV) ", "control systems is always the research hotspot of EV field. When the battery component of HEV operates at charge sustaining (CS) mode, the most important problem is how to split the whole vehicle's required power between engine and battery component reasonably and effectively so as to make the good economy and driving performance. Taking battery component of Plug-in Hybrid Electric Bus as the research object", "this paper established the model of feedback control system for battery component. Then the feedback control systems gains are optimized with the objective function of equivalent fuel consumption and accumulated power requirement error", "which is based on BUSRTE driving cycle. The obtained gains are testified and verified by NEWYORK and CBDBUS driving cycle respectively. The results indicate that the optimized control system for batteries has good fuel economy and driving performance.

According to work principle of controller area network (CAN) protocol, the use of CAN in time-critical and safety-critical control applications such as independent drived electric vehicle’s powertrains presented designers with new special problems on the determination of real-time reliability rather than real-time capability. In this paper, real-time reliability analysis of the native event-triggered CAN for a 2-motor independent drive electric vehicle (IDEV) was researched and real-time reliability optimization based on rate monotonic algorithm (RMA) was discussed contrastively. The parameters including real-time capability, maximum response time, maximum bandwidth utilization, maximum periods jitter and jitter margin were evaluated respectively. The calculation results demonstrated that real-time reliability of the CAN based on RMA is better than the native CAN as underlying control network of IDEV’s powertrains. The result indicates real-time reliability analysis and optimization can improve the reliability of IDEV’s distributed control systems, provides a theory analysis foundation for the engineering design and application of IDEV.