Abstract

Current studies have achieved energy savings of vehicle subsystems through various control strategies, but these control strategies lack a benchmark to measure whether these energy savings are sufficient. This work proposes a control design framework that uses the 1.5 °C target in the Paris Agreement as a benchmark to measure the adequacy of energy savings of vehicle subsystems. This control design framework involves two points. One is the conversion of the 1.5 °C target into a constraint on the energy consumption of a vehicle subsystem. The other is the optimal control design of the vehicle subsystem under this constraint. To describe the specific application of this control design framework, we conduct a case study concerning the control design of active suspension in a battery electric light-duty vehicle. By comparison with a widely used linear quadratic regulator (LQR) method, we find that this control design framework can both ensure the performance comparable to the LQR method and help to meet the 1.5 °C target in the Paris Climate Agreement. In addition, a sensitivity analysis shows that the control effect is hardly changed by battery electric vehicle market share and electricity CO2 intensity. This work might provide insight on ways that the automotive industry could contribute to the Paris Agreement.

Highlights

  • Global warming associated with anthropogenic emissions of carbon dioxide and other greenhouse gases (GHGs) has become a major potential challenge for humans [1]

  • Where φ j is the proportion of the energy consumption per kilometer among different drivetrain types, and j = (1, 2, 3) represents the drivetrain of battery framework electric vehicle vehicle (BEV), internal combustion engine vehicles (ICEVs), and fuel cell vehicles (FCVs), respectively; TSj is the share of type T vehicles with type j drivetrain out of all type T vehicles in 2050; ESi,j is the share of energy consumption of type i fuel out of total energy consumption by type T vehicles with type j drivetrain technology in one year, and i = (1, 2, 3, 4, 5, 6) represents electricity, gasoline, diesel, bioethanol, natural gas, and hydrogen, respectively; CFi is the CO2 intensity of type i fuel in one year; TD_VT

  • ECactive-sus is the energy consumed by active suspension per kilometer. t1 km = 107 s is the average period taken by a battery electric light-duty vehicle (BELDV) traveling one kilometer where P(t) is the power consumed by active suspension

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Summary

Introduction

Global warming associated with anthropogenic emissions of carbon dioxide and other greenhouse gases (GHGs) has become a major potential challenge for humans [1]. In order to meet the challenges of global warming, most countries in the world have ratified the Paris Climate Agreement to keep anthropogenic global warming within 2 ◦ C and pursue efforts to keep it below 1.5 ◦ C [2]. Transport currently accounts for about 14% of direct economy-wide global anthropogenic GHG emissions [3]. Driven by increases in all travel modes, the energy consumption of the transport sector is expected to increase by between 80 and 130% above the current level [4], which will cause much more GHG emissions. The Paris Agreement on climate change provides both a complex challenge and a unique opportunity for carbon mitigation action in the transport sector. Besides the powertrain, minimizing the energy consumption of other subsystems (such as the steering system, air conditioning system, braking system, and suspension system) by proper control strategies is an important catalyst for reducing GHG emissions

Literature Review
Contribution of This Work
Framework
Assumptions and Data
CO2 Emission Limits
Travel Distance
CO2 Intensity
Case Study
Control Design
Vertical Quarter-Car Model
Vertical
Design of Optimal Control
Evaluation
Road Disturbance Model
Results
Power consumption comparison between
Schedule
Sensitivity Analysis
This gives the bluethe lineblue in Figure
Conclusions
Full Text
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