Abstract
V2X connectivity and powertrain electrification are emerging trends in the automotive sector, which enable the implementation of new control solutions. Most of the production electric vehicles have centralized powertrain architectures consisting of a single central on-board motor, a single-speed transmission, an open differential, half-shafts, and constant velocity joints. The torsional drivetrain dynamics and wheel dynamics are influenced by the open differential, especially in split- scenarios, i.e., with different tire-road friction coefficients on the two wheels of the same axle, and are attenuated by the so-called anti-jerk controllers. Although a rather extensive literature discusses traction control formulations for individual wheel slip control, there is a knowledge gap on: a) model based traction controllers for centralized powertrains; and b) traction controllers using the preview of the expected tire-road friction condition ahead, e.g., obtained through V2X, for enhancing the wheel slip tracking performance. This study presents nonlinear model predictive control formulations for traction control and anti-jerk control in electric powertrains with central motor and open differential, and benefitting from the preview of the tire-road friction level. The simulation results in straight line and cornering conditions, obtained with an experimentally validated vehicle model, as well as the proof-of-concept experiments on an electric quadricycle prototype, highlight the benefits of the novel controllers.
Highlights
The anti-jerk and traction control functions are well known and widely used in passenger cars [1]-[2]
Both functions are separately implemented in production electric vehicles (EVs) with centralized on-board powertrain architectures, which consist of a single electric motor per driving axle, a single-speed transmission, an open differential, half-shafts, and constant velocity joints [3]
This study proposes a set of novel proof-of-concept anti-jerk and traction controllers based on nonlinear model predictive control (NMPC), for generation EVs with V2X connectivity and centralized powertrain architectures
Summary
The anti-jerk and traction control functions are well known and widely used in passenger cars [1]-[2]. Through appropriate powertrain torque modulation, these controllers: i) attenuate the typical torsional drivetrain oscillations excited by on-board powertrains, to increase passengers’ comfort; and ii) limit wheel slip, enhancing the longitudinal acceleration and cornering responses Both functions are separately implemented in production electric vehicles (EVs) with centralized on-board powertrain architectures, which consist of a single electric motor per driving axle, a single-speed transmission, an open differential, half-shafts, and constant velocity joints [3]. Vehicle connectivity to other road users, the infrastructure, and the cloud, usually referred to as V2X, is a growing trend, which is confirmed by the number of recent review papers on the topic, e.g., see [4]-[7] This technology has several potential applications, including cooperative tire-road friction estimation [7], achieved through the fusion, e.g., in the cloud, of the sensor information from multiple preceding vehicles. The manuscript is organized as follows: section II is a short literature survey on the relevant topics, and identifies the knowledge gap; section III describes the case study EVs; section IV deals with the optimal control problem formulation, including the considered internal models, cost function, and constraints; section V describes the simulated maneuvers and performance indicators; section VI critically analyzes the different internal model formulations; section VII discusses the simulation results, while section VIII focuses on the proof-ofconcept experiments; section IX summarizes the main conclusions
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