Independent wheel torque control of 4WD electric vehicle for differential drive assisted steering

Future electric vehicles (EVs) will be linked to the electric power system infrastructure; the vehicles will operate through frequent electric charging, as is the case with electric trains. Conventional batteries require a long recharging time; therefore, supercapacitors, rather than batteries, will play an important role in the future for charging of EVs. Recently, we manufactured small EVs powered only by supercapacitors. Supercapacitors have a long operating life, large current density, and environmentally friendly composition. Further, their energy level can be estimated from their terminal voltage. Because EVs powered by supercapacitors can operate for more than 20 min after being charged for only 30 s, the requirement for constant recharging of EVs is reduced substantially, thereby increasing the efficiency of these EVs. Wireless power transfer based on magnetic resonance is an extremely important technique that needs to be considered for enhancing the efficiency of EVs. In a laboratory experiment, this technique enabled approximately 50 W power transfer with more than 95% efficiency at a distance of more than 50 cm. In order to improve energy efficiency and safety of future EVs, the implementation of novel motion control techniques for EVs is required. Since EVs are powered by electric motors, they have three major advantages: motor torque generation is quick and accurate, a motor can be attached to each wheel, and motor torque can be estimated precisely. These advantages enable the realization of highperformance antilock braking and traction control systems, control of two-dimensional chassis motion, and estimation of road surface condition. In summary, we can achieve a large-scale development of future vehicles that employ three techniques: Electric Motors, Supercapacitors, and Wireless Power Transfer. This eliminates the requirement for engines, high performance Li-ion batteries, and large charging stations.

Future vehicle society based on electric motor, capacitor and wireless power supply

This paper proposes an antilock braking system (ABS) control method for maximizing tire-road friction and minimizing yaw moment of a commercial vehicle. First, a target slip ratio-based ABS control strategy has been described based on Lyapunov theory. Under this method, slip ratio is controlled in stable range precisely and rapidly. As fixed target slip ratio of ABS controller is not able to provide optimal road friction when a vehicle brakes on butt road and μ-split road, a variable target slip ratio method has been proposed to further improve tire-road friction and decrease yaw moment caused by longitudinal tire-road friction. Vicinity estimation and actual adhesion-based estimation have been introduced to estimate optimal target slip ratio. After a series of simulation tests, the method proposed in this paper has been proven to be effective.

An ABS Control Strategy for Commercial Vehicle

The paper addresses evolution of fuzzy systems for core applications of automotive engineering. The presented study is based on the analysis of bibliography dedicated to fuzzy sets and fuzzy control for ground vehicles. A special attention is given to fuzzy approaches used in the following domains of automotive engineering: vehicle dynamics control systems, driver and driving environment identification, ride comfort control, and energy management of electric vehicles. The bibliographical analysis, supplemented with statistics of relevant research publications, has allowed to allocate the most important fuzzy application cases for each domain. In particular, it concerns driver identification, human-machine interface, recognition of road conditions, and controllers of vehicle chassis and powertrain systems. It is found out that fuzzy methods have the primary use most of all for tasks requiring identification and forecasting procedures, especially in conditions of limited informational space. Additional observation that can be also derived from the presented survey points to reasonable integration of fuzzy technique with other control engineering methods to improve the performance of automotive control systems. In the aggregate the performed review indicates that fuzzy computing can be considered as a versatile tool for automotive engineering applications of different nature.

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A review of fuzzy methods in automotive engineering applications

Why do we need to supply “big energy” to electric vehicles (EVs) “while stopping” and “for a short time”? The energy form of electricity is absolutely different from gasoline. We may not need to take the same style of gasoline vehicle. Future EVs will be linked to the electric power system infrastructure; the vehicles will operate through frequent electric charging, as is the case with electric trains. Wireless power transfer based on magnetic resonance will be an extremely important technique to receive energy from the infrastructure. In a laboratory experiment, this technique enabled approximately 1kW power transfer with more than 90% efficiency at a distance of 1 m. It opens a new way to the novel EV world. Supercapacitors, rather than batteries, will play an important role in the future for charging of EVs. Supercapacitors have a long operating life (a few million times charge/ discharge life), large current density, and environmentally friendly composition. Further, their energy level can be estimated from the terminal voltage. Our EVs powered by supercapacitors can operate for more than 20 min after being charged for only 30 s. Electric motors have three major advantages: motor torque generation is quick and accurate, a motor can be attached to each wheel, and motor torque can be estimated precisely. These advantages enable the realization of high performance antilock braking and traction control systems, control of two-dimensional chassis motion, and estimation of road surface condition. Such motion control techniques improve energy efficiency and safety of future EVs. In summary, we can achieve a large-scale development of future vehicles that employ three techniques: Electric Motors, Supercapacitors, and Wireless Power Transfer. This eliminates the requirement for engines, high performance Li-ion batteries, and quick charging stations.

Novel EV society based on motor/ capacitor/ wireless — Application of electric motor, supercapacitors, and wireless power transfer to enhance operation of future vehicles

In this paper we propose an optimal slip ratio estimation method based on fuzzy inference. One of the major advantages of electric vehicles is the quick and precise torque response of the electric motor, which realizes a novel traction control system. To prevent skidding, optimal slip ratio control has been successfully developed. It maintains the slip ratio at the optimum value that gives the maximum driving force. The remaining problem is how to generate the optimal slip ratio command sent to the controller. First we show that effective estimation of the optimal slip ratio is difficult to perform by the simple gradient method, which is a well-known optimization method. But various experimentally obtained data can be easily incorporated into fuzzy inference, and therefore its estimation performance can be easily improved by the accumulation of human experience. This is a major advantage in the nonlinear estimation of real road-tire characteristics. The effectiveness of the proposed estimation and control methods is confirmed by numerical simulation. © 2001 Scripta Technica, Electr Eng Jpn, 135(3): 56–63, 2001

Ichiro Sakai

Papers

Optimal slip ratio estimator for traction control system of electric vehicle based on fuzzy inference