EVS 26 Los Angeles , California , May 6-9 , 2012 Traction Control Method of Hybrid Electric Vehicle based on Multi-Objective Dynamic Coordination Control

The control method of the conventional traction control system on split-μ surfaces improves vehicle acceleration performance, but influences its stability performance. To solve this problem, a hierarchical traction control system for ISG hybrid electric vehicles based on multi-objective dynamic coordination control (MHEVTCS) is proposed. In the upper level controller, a target driving torque calculating strategy based on dynamical sliding mode control is developed. In the lower level controller, such strategies as multi-objective dynamic coordination control strategy, brake torque control strategy based on an inverse model, target engine torque design strategy and torque dynamic coordinate control strategy are proposed. Detailed simulation and hardware-in-loop experiment results show that slipping wheels are controlled quickly, accurately and smoothly by MEHVTCS. MHEVTCS solves the problem of merely pursuing acceleration performance and neglecting stability performance of conventional traction control system.


Introduction
On split-μsurfaces, traction control system of conventional internal combustion engine vehicle (ICETCS) applies brake torque on the slipping wheel of low adhesion side road to improve vehicle's acceleration performance [1] [2] .However, additional yaw moment is caused which influences its stability performance.Motor system of hybrid electric vehicle (HEV) has better dynamic performance than engine system and hydraulic system [3][4] .It can provide a large drive torque at a low speed.Compared to conventional internal combustion engine vehicle, HEV is easier to slip on slippery road [5][6] .If the control method of ICETCS on split-μ surfaces is continually used by HEV, more brake torque intervening should be used to maintain the slip ratio of slipping wheel at a desired value.And, more additional yaw moment will be caused that influences vehicle's stability severely.Thus, traction control system of HEV (HEVTCS) should be redesigned.Taking an ISG hybrid electric vehicle as the research object as shown in Figure1, the traction control method of an ISG hybrid electric vehicle is researched in this paper.

Control for the Upper Level Controller
In the target driving torque calculating strategy, a dynamical sliding mode controller of multi-input and multi-output is designed as shown in Figure3., m is the vehicle mass, x v is the vehicle longitudinal speed, J  is the inertia of the wheel assembly, r  is the wheel radius,  is the air density, A is the frontal area, C is the air resistance coefficient, f  is the front axle load proportion.
The control target is to make 2 x and 3 x to follow 1 nx together as where 1 / ( 1) , d  is the optimal slip ratio.
The switching surface are dd .The reaching law is Then the control law is    For HEV, engine is the main power supply.The most effective method to avoid wheels slipping of HEV is to reduce engine torque, but its response speed and control accuracy are worse than motor.Therefore a target engine torque design strategy based on low pass filtering is proposed.In this strategy, low frequency part of the desired driving torque is provided by engine and high frequency part of the desired driving torque is compensated by motor.The filtering method is

Torque Dynamic Coordinate Control Strategy
The aim of this torque dynamic coordinate control strategy is to achieve the desired driving torque rapidly and accurately.According to such requirements as fast response, accuracy, robustness and linear input/output transfer characteristics, a torque dynamic coordinate control strategy based on model matching 2-DOF control [7] is proposed as shown in Figure6 Then the feedforward transfer function can be calculated as Additionally, the PID control method is used in the feedback controller.

Simulations and Analysis
In order to evaluate the MHEVTCS, a simulation platform is built as shown in        In this paper, a traction control method for an ISG hybrid electric vehicle is explored.The conclusions are followed: 1) Slipping wheels can be controlled by MHEVTCS quickly, accurately and smoothly.
2) Compared with conventional traction control systems, MHEVTCS improves vehicle's acceleration performance greatly without influencing its stability severely.
3) The dynamic coordinate control problem among engine, motor and hydraulic system is solved by MHEVTCS.

Figure1:Figure2:T
Figure1: Configuration of the research object

i 2 )
is the final drive ratio.Hierarchical optimization method is used to solve this multi-objective optimization problem as the following World Electric Vehicle Journal Vol. 5 -ISSN 2032-6653 -© 2012 WEVA 1) When the road adhesion coefficient is low or the vehicle speed is high, vehicle's stability performance should be focused on.Then the multi-objective optimization problem can be described When the road adhesion coefficient is high and the vehicle speed is low, vehicle's dynamic performance should be focused on.At this time, the multi-objective optimization problem can be described as
time constant.At the same time, the engine torque demand eTCS T should be smaller than the desired engine torque eHEV Twhich is calculated by an energy management system, otherwise engine torque will increase which is against the control aim of traction control systems to decrease driving torque.To sum up, the engine torque demand

Figure6:T
Figure6: Torque dynamic coordinate control strategy based on model matching 2-DOF control

Figure7
Figure7 including driver model, energy management controller model, MHEVTCS controller model, powertrain model and 15-DOF vehicle model.

Figure9:
Figure9: Simulation results of S2 Furthermore, one hardware-in-loop test platform is built as shown in Figure10.

Figure11:
Figure11: Hardware-in-loop test result without MHEVTCS Figure12 shows that the speed of slipping wheel on low adhesion side road is controlled at target value after 0.5s with MHEVTCS.At the end of the test, vehicle speed achieves 4.8m/s.Acceleration performance and starting ability of HEV are greatly improved by MHEVTCS.
Figure12: Hardware-in-loop test result with MHEVTCS

4 Multi-Objective Dynamic Coordination Control for the Lower Level Controller
One set of hardware-in-loop tests Table2: