Abstract
The paper discusses novel computationally efficient torque distribution strategies for electric vehicles with individually controlled drivetrains, aimed at minimizing the overall power losses while providing the required level of wheel torque and yaw moment. Analytical solutions of the torque control allocation problem are derived and effects of load transfers due to driving/braking and cornering are studied and discussed in detail. Influences of different drivetrain characteristics on the front and rear axles are described. The results of an analytically derived algorithm are contrasted with those from two other control allocation strategies, based on the offline numerical solution of more detailed formulations of the control allocation problem (i.e., a multiparametric nonlinear programming (mp-NLP) problem). The control allocation algorithms are experimentally validated with an electric vehicle with four identical drivetrains along multiple driving cycles and in steady-state cornering. The experiments show that the computationally efficient algorithms represent a very good compromise between low energy consumption and controller complexity.
Highlights
Electric vehicles with multiple and individually controlled drivetrains can achieve superior handling qualities through direct control of the yaw moment, called torque-vectoring
The experimental comparison of the performance of the proposed explicit control allocation (E-CA) with the performance of two control allocation strategies based on off-line numerical optimizations, called implicit control allocation (I-CA) and hybrid control allocation (H-CA), and the performance of the same electric vehicle operating in a front-wheel-drive mode and in a four-wheel-drive mode 3 with constant 50:50 front-to-rear wheel torque distribution
The analytical solution of the control allocation problem can be explicitly achieved from the coefficients of the proposed third order fitting model, including consideration of load transfers and different drivetrains on the front and rear axles
Summary
Electric vehicles with multiple and individually controlled drivetrains can achieve superior handling qualities through direct control of the yaw moment, called torque-vectoring. This paper significantly extends the preliminary results of [28] towards the implementation of simple and industrially viable control allocation formulations These must: i) be based on the results of experimental drivetrain power loss measurements for the whole drivetrain on rolling road facilities, rather than on complex formulations of the individual power loss contributions related to the inverter, motor, transmission, tires, etc., which would demand the detailed assessment of the individual components, with negative cost and time implications; and ii) not require knowledge of the precise tire slip in normal driving conditions (i.e., at low slip ratios and slip angles) as it cannot be reliably estimated with current production vehicle state estimators. The experimental comparison of the performance of the proposed E-CA with the performance of two control allocation strategies based on off-line numerical optimizations, called implicit control allocation (I-CA) and hybrid control allocation (H-CA), and the performance of the same electric vehicle operating in a front-wheel-drive mode and in a four-wheel-drive mode 3 with constant 50:50 front-to-rear wheel torque distribution
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