日本本田公司双电机混合动力系统的先进技术

为了应对降低CO_2排放等实际环保措施,混合动力汽车(HEV)及插电式混合动力汽车(PHEV)的应用范围正在不断扩大。日本本田公司推出了1种先进的动力传动技术,该技术兼顾了顺畅强劲的加速性能及燃油经济性,其重要技术部件是适用于中型汽车的插电式智能多模式驱动系统,作为双电机的全新混合动力系统的一大优势是使效率得以显著提升。介绍了插电式智能多模式驱动系统的结构及其工作原理,该系统可根据车辆行驶状况及基于电池容量而设置3种驾驶模式,即电动车模式、发动机模式、混合动力模式,并通过在3种模式间实施最佳切换以获得高效率。

Control allocation algorithm for over-actuated electric vehicles

A control allocation algorithm based on pseudo-inverse method was proposed for the over-actuated system of four in-wheel motors independently driving and four-wheel steering-by-wire electric vehicles in order to improve the vehicle stability. The control algorithm was developed using a two-degree-of-freedom(DOF) vehicle model. A pseudo control vector was calculated by a sliding mode controller to minimize the difference between the desired and actual vehicle motions. A pseudo-inverse controller then allocated the control inputs which included driving torques and steering angles of the four wheels according to the pseudo control vector. If one or more actuators were saturated or in a failure state, the control inputs are re-allocated by the algorithm. The algorithm was evaluated in Matlab/Simulink by using an 8-DOF nonlinear vehicle model. Simulations of sinusoidal input maneuver and double lane change maneuver were executed and the results were compared with those for a sliding mode control. The simulation results show that the vehicle controlled by the control allocation algorithm has better stability and trajectory-tracking performance than the vehicle controlled by the sliding mode control. The vehicle controlled by the control allocation algorithm still has good handling and stability when one or more actuators are saturated or in a failure situation.

Research on EV Battery Swapping System and Standards Requirements

Combined with the perspective of State Grid Corporation of China （SGCC）, the paper researches the EV battery swapping mode and its advantages, analyses standards requirements of battery swapping system and proposes the corresponding standards system

Study on simulation and scheduling algorithm of CAN control for independently driving electric vehicle

Safety-critical applications such as the independently driving systems of electric vehicle （EV） require a high degree of reliability. The controller area network （CAN） is used extensively in the control sectors. A new real-time and reliable scheduling algorithm based on time-triggered scheduler with a focus on the CAN-based distributed control systems for independently driving EV is exploited. A distributed control network model for a dual-wheel independendy driving EV is established. The timing and reliabili- ty analysis in the worst case with the algorithm is used to evaluate the predictability and dependability and the simulation based on the algorithm with CANoe software is designed. The results indicate the algorithm is more predicable and dependable.

Parameters optimum matching of pure electric vehicle dual-mode coupling drive system

As an important development direction of pure electric vehicle drive system,the distributed drive system has the advantages of compact structure,high transmission efficiency,and flexible control,but there are some serious problems such as high performance requirements to the drive motors,complex control strategies,and poor reliability.To solve these problems,a two motors dual-mode coupling drive system has been developed at first,which not only has the capacity of two-speed gear shifting,but also can automatically switch between the distributed drive and the centralized drive by means of modes change control.So,the performance requirements to the drive motors can be reduced,the problem of abnormal running caused by the fault of unilateral distributed drive systems also can be resolved by replacing the drive mode with centralized drive.Then,the system parameters primary and the optimum matching under the principle of efficiency optimization have been carried out,which makes the drive system achieve predetermined functions and meet the actual demands of different operating statuses.At last,the economic comparison of a pure electric vehicle installation with a dual-mode coupling drive sytem,a single-motor centralized drive system or a dual-motor distributed drive system in the simulation conditions has been completed.Compared with other systems,the driving range of the electric vehicle driven by the designed system is significantly increased,which proves the better efficiency and application value of the system.

Energy and environmental life-cycle assessment of passenger car electrification based on Beijing driving patterns

This paper examines the energy and environmental benefits within the whole life cycle shifting from traditional gasoline vehicles to electrified advanced vehicles under regional real-world driving behaviors. The advance vehicles focus on family passenger cars and include battery electric vehicles （BEVs）, plug-in hybrid electric vehicles （PHEVs）, and hybrid electric vehicles （HEVs）. The GREET （greenhouse gases, regulated emissions, and energy use in transportation） model is adopted with regional circumstances modifications, especially the UF （utility factors） of PHEVs. The results show that the electrified vehicles offer great benefits concerning energy consumption, greenhouse gas （GHG） emissions as well as urban Particulate Matter 2,5 （PMz.s） emissions. Compared to conventional gasoline vehicles, the life-cycle total energy reduction for advance vehicles is 51% to 57%. There is little difference on energy reduction among the HEVs, PHEVs and BEVs, with the energy mix shifting from petroleum to coal for the stronger electrification. The reductions of GHG emissions are 57% for HEV, 54% to 48% for PHEVs with 10 miles to 40 miles CD range, and 40% for BEV. The life-cycle and local PM2.5 emissions are discussed separately. The life-cycle PM2.5 emissions increase with vehicle electrification and reach a maximum for the BEV which are 5% higher than the conventional vehicle （CV）. However, electric vehicles can shift PM2.5 emissions from vehicle operation to upstream operations and help mitigate PM2.5 emissions in urban areas. The local emissions of PHEVs and BEVs can be reduced by 37% to 81% and 100% compared with CVs.