The Intelligent Environment Friendly Vehicle

Safety, energy efficiency and environmental protection are the eternal themes in the history of the automotive industry. A booming automotive industry has brought great convenience to human transport over the years, but an increasing number of vehicles has also caused frequent traffic accidents, excessive energy consumption, serious environmental pollution and other social issues. It has become the consensus of global research institutions and automotive enterprises to solve these problems by integrating new technologies from multiple fields.

As a mobile transport platform and embodiment of complex electromechanical system, the i-EFV integrates complicated coupling structure and actuating components of sensing, communication and mechanical-electronic-electrical-hydraulic systems. Meanwhile, it also represents the interdisciplinary technology integration of intelligence, network and electric vehicle.

As a typical complex electromechanical system (Li et al., IEEE Trans Intell Transp Syst 13(1), (2012); Li et al., Structure of intelligent environmental friendly vehicle, China (2009)), i-EFV integrates mechanical, hydraulic, electronic, electric, sensing, communication, and control subsystems. Although the adoption of traditional functional superposition for its system integration solution occupies the advantage of simple design, such as an intelligent driving system can be directly superimposed on an EV, a continuous upgrade of intelligent driving system leads to more subsystems and complex system structure with inter-coupling and overlay of functions and structures.

Accurate identification of vehicle states and complex driving environment states is the necessary information base for i-EFV to carry out safe and energy-saving controls. For i-EFV that integrates complex electromechanical systems, faces time-varying traffic environment and implements multi-performance objective control, there are three main problems in the comprehensive identification vehicle states and environment information: (1) the large amount of information data obtained based on V2V communication, V2I communication, remote wireless communication and onboard sensing system is overlapping and redundant, which needs integrated analysis and processing to form a unified description of vehicle and environment; (2) the vehicle driving environment is complex and changeable, and the information obtained from existing sensing systems is seriously disturbed, which makes it necessary to obtain accurate object information based on the characteristics of redundancy of multi-source sensors; (3) the accurate information on the characteristics of driver-vehicle-road traffic environment cannot be obtained directly through the sensors, which makes it necessary to fuse multi-source information and conduct comprehensive analysis. Therefore, in order to effectively use the multi-source and redundant data information to accurately identify and predict vehicle state and traffic environment, a systematic signal processing method is required.

The optimally integrated vehicle control is the basic problem to be solved by the key i-EFV coordinated control technologies. Exploring the mechanism of multi-physical process coupling in complex electromechanical systems and the problem of multi-system coordinated control in the “human-vehicle-infrastructure” environment is the basis for achieving the performance and operational goals of i-EFV. The multi-objective and multi-system coordinated dynamics control of i-EFV achieves the integrated and optimized performance of i-EFV by optimizing the safety, comfort, energy saving and environmental protection objectives and coordinating the vehicle driving, brake, steering, suspension and other systems.

Intelligent electric vehicles using the structure-sharing architecture have shared sensor information, including information issued by the forward radar, which can be used for both active safety control and energy-efficiency control of electric vehicles, which makes it possible to make full use of system information resources to improve the energy utilization of vehicles.

Based on the established new-concept vehicle structure and key technology system of i-EFV, this chapter focuses on the ACC of intelligent hybrid electric vehicles (i-HEVs) as a typical application, aiming to design and comprehensively implement a safe, economic and comfortable overall structure of the i-HEV ACC control system based on its multi-performance objectives and the requirements of the multi-mode coordinated control of the drive/braking system.

Different from i-HEVs, the optimal control of intelligent electric vehicles requires guaranteeing the efficient and safe operation of the traffic system and the power grid system due to the existence of charging process. Therefore, a charging/battery-swapping scheduling solution is needed for intelligent electric vehicles. In this chapter, a charging/battery-swapping scheduling strategy is designed according to the different charging/battery-swapping characteristics of fast-charging, slow-charging and battery-swapping electric vehicles, as well as the different driving characteristics of electric private cars, electric taxis and electric buses, to realize the comprehensive optimization of traffic and power grid.

To solve social problems such as energy security, environmental pollution, traffic congestion, and traffic accidents caused by the widespread use of traditional internal combustion engine vehicles (ICEVs), many countries are vigorously promoting clean and environment-friendly new energy vehicles (NEVs) represented by battery electric vehicles (BEVs). Compared with ICEVs, electric vehicles (EVs) use a wide range of power sources, including wind, solar and nuclear energy, which can significantly reduce carbon dioxide emissions caused by fossil fuel consumption. Also, EVs have high energy efficiency, and braking energy regeneration can further reduce energy consumption during driving.