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Abstract Energy management strategies for charge-sustaining hybrid electric vehicles reduce fuel consumption and maintain battery pack state of charge while meeting driver output power demand. The equivalent consumption minimization strategy is a real-time energy management strategy that makes use of an equivalence ratio to quantify electric power consumption in terms of fuel power consumption. The magnitude of the equivalence ratio determines the hybrid electric vehicle mode of operation and influences the ability of the energy management strategy to reduce fuel consumption as well as maintain the battery pack state of charge. The equivalent consumption minimization strategy in this article uses three Willans line models, which have an associated marginal efficiency and constant offset, to model the performance in the hybrid electric vehicle controller.

Abstract A tandem axle suspension is an important system to the ride comfort and vehicle stability of and road damage experience from commercial vehicles. This article introduces an investigation into the use of a controlled active tandem axle suspension, which for the first time enables more effective control using two fuzzy logic controllers (FLC). The proposed controllers compute the actuator forces based on system outputs: displacements, velocities, and accelerations of movable parts of tandem axle suspension as inputs to the controllers, in order to achieve better ride comfort and vehicle stability and extend the lifetime of road surface than the conventional passive suspension. A mathematical model of a six-degree-of-freedom (6-DOF) tandem axle suspension system is derived and simulated using Matlab/Simulink software.

Abstract A critical component of vehicle dynamic control systems is the accurate and real-time knowledge of the vehicle’s key states and parameters when running on the road. Such knowledge is also essential for vehicle closed-loop feedback control. Vehicle state and parameter estimation has gradually become an important way to soft-sense some variables that are difficult to measure directly using general sensors. In this work, a seven degrees-of-freedom (7-DOF) nonlinear vehicle dynamics model is established, where consideration of the Magic formula tire model allows us to estimate several vehicle key states using a hybrid algorithm containing an unscented Kalman filter (UKF) and a genetic algorithm (GA). An estimator based on the hybrid algorithm is compared with an estimator based on just a UKF. The results show that the proposed estimator has higher accuracy and fewer computation requirements than the UKF estimator.

Abstract To reduce fuel consumption and carbon dioxide (CO2) emissions from mobile air conditioning (A/C) systems, “U.S. Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards” identified solar/thermal technologies such as solar control glazings, solar reflective paint, and active and passive cabin ventilation in an off-cycle credit menu. National Renewable Energy Laboratory (NREL) researchers developed a sophisticated analysis process to calculate U.S. light-duty A/C fuel use that was used to assess the impact of these technologies, leveraging thermal and vehicle simulation analysis tools developed under previous U.S. Department of Energy projects. Representative U.S. light-duty driving behaviors and weighting factors including time-of-day of travel, trip duration, and time between trips were characterized and integrated into the analysis.

Abstract Autonomy and connectivity are considered among the most promising technologies to improve safety and mobility and reduce fuel consumption and travel delay in transportation systems. In this paper, we devise an optimal control-based trajectory planning model that can provide safe and efficient trajectories for the subject vehicle while incorporating platoon formation and lane-changing decisions. We embed this trajectory planning model in a simulation framework to quantify its fuel efficiency and travel time reduction benefits for the subject vehicle in a dynamic traffic environment. Specifically, we compare and analyze the statistical performance of different controller designs in which lane changing or platooning may be enabled, under different values of time (VoTs) for travelers.

Abstract The article examines quarter-car dynamics with the possible separation of its tire from the road. A set of nondimensionalized differential equations has been proposed to minimize the involved parameters. Time and frequency response investigation of the system has been analyzed insightfully considering tire-road separation. To measure the separation of the tire, a time fraction index is defined, indicating the fraction of separation time in a cycle at steady-state conditions. Minimizing the index is assumed as the objective of the optimized system. An actuator is applied to the vehicle suspension in parallel with the mainspring and damper of the suspension. Particle Swarm Optimization (PSO) is used to properly tune a Proportional-Integral-Derivative (PID) controller for the active suspension system excited by a harmonic excitation.

Abstract A time domain analysis method of ride comfort and energy dissipation characteristics is proposed for automotive vibration proportional–integral–derivative (PID) control. A two-degrees-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined, and the Routh stability criterion method was introduced to assess the impact of PID control on vehicle stability. The PID control parameters are tuned using the differential evolution algorithm, and to improve the algorithm’s adaptive ability, an adaptive operator is introduced, so that the mutation factor of differential evolution algorithm can change with the number of iterations.

Abstract Multi-agent autonomous racing still remains a largely unsolved research challenge. The high-speed and close proximity situations that arise in multi-agent autonomous racing present an ideal condition to design algorithms which trade off aggressive overtaking maneuvers and minimize the risk of collision with the opponent. In this article we study a two-vehicle autonomous racing setup and present AutoPass—a novel framework for overtaking in a multi-agent setting. AutoPass uses the structure of an automaton to break down the complex task of overtaking into sub-maneuvers that balance overtaking likelihood and risk with safety of the ego vehicle. We present real-world implementation of 1/10-scale autonomous racing cars to demonstrate the effectiveness of AutoPass for the overtaking task.

Abstract Uncertainty of fuel reserves, environmental crisis, and health concerns arise from transport demands and reliance on fossil fuels. Downsized gasoline turbocharged direct injection (GTDI) engines have been developed and applied to most modern gasoline vehicles, delivering superior efficiency in high-load operation, reduced friction, and weight. But fuel enrichment and late combustion phasing to mitigate knocking combustion have hindered the efficiency benefits at higher loads with high boost. Furthermore, the wide valve-overlap with a three-cylinder setup for the maximum scavenging efficiency produces bursts of short-circuit (SC) air to cause underestimation of the equivalence ratio by the oxygen sensor, resulting in higher tailpipe nitrogen oxides (NOx) emissions with three-way catalyst (TWC) exhaust aftertreatment. Reducing the valve overlap to limit short-circuiting and enrichment will recover the combustion efficiency and the engine ER, but at the cost of high knock onset.

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Abstract This study proposes a real-time control for plug-in hybrid electric vehicles (PHEVs) based on dynamic programming (DP). In order to obtain the optimal controls, DP is first used to solve the driving cycle, and a model-based calibration (MBC) tool is used to generate the optimal maps from the optimal trajectories. Further, a feedback energy management system (FEMS) is developed with the SoC as the feedback variable, which considers the charge and discharge reaction of the battery. To make full use of the energy stored in the battery, combined with the charge depletion-charge sustain (CDCS) strategy, the reference SoC is introduced. Finally, comparative simulation of the proposed real-time controller and DP is performed. The obtained results show that the fuel consumption of the real-time controller is 4.82 L/100 km in the worldwide harmonized light-duty vehicles’ test cycles, which is close to the fuel consumption with DP at 4.69 L/100 km.

Abstract In the automotive domain, the evolution of electrical and electronic (E/E) architecture trend is toward consolidating multiple heterogeneous applications executing on individual devices onto a centralized powerful computing platform. Many forums debate the nature of this centralized computing platform. At least for another decade, automotive powertrain functions will continue their development on a multicore controller platform (MCU) instead of many core processors. Data security and the need to meet Automotive Safety Integrity Level D (ASIL-D)-compliant powertrain functions are some of the reasons for this preference. For the centralized computing platform, virtualizing the underlying MCU will facilitate the simultaneous execution of heterogeneous powertrain applications with guaranteed spatial and temporal isolation. A common problem in virtualizing the MCU is the sharing of peripherals, which are comparatively scarce.

Abstract Commercial vehicles require continual improvements in order to meet fuel consumption standards, improve diesel aftertreatment (AT) system performance, and optimize vehicle fuel economy. Simultaneous reductions in both CO2 and NOX emissions will be required to meet the upcoming regulatory targets for both EPA Phase 2 Greenhouse Gas Standards and new Low NOX Standards being proposed by the California Air Resources Board (CARB). In addition, CARB recently proposed a new certification cycle that will require high NOX conversion while vehicles are operating at lower loads than current regulatory cycles require. Cylinder deactivation (CDA) offers a powerful technology lever for meeting these two regulatory targets on commercial diesel engines. There have been numerous works in the past year showing the benefits of diesel CDA for elevating exhaust temperatures during low-load operation where it is normally too cold for AT to function at peak efficiency.

Abstract Due to the transition of the driver to a passenger as well as the option of non-driving tasks, automated driving will necessitate adjustments of driving dynamics. In order to face higher comfort requirements and mitigate motion sickness not only horizontal dynamics but also vertical dynamics should be concerned. Therefore, we developed a novel control algorithm for active suspension systems, which takes the requirements of autonomous vehicles into account. Due to safety, cost reasons, and the unavailability of automated test vehicles, the controller was built up, tested, and tuned in simulation before final in-car testing. In this article we introduce a combined simulation and testing process for suspension control systems with focus on comfort measures. We successfully apply the method to the mentioned active suspension control algorithm with good accordance between simulation and measurement for low-frequency excitation.

Abstract In order to further improve the active safety protection of the vehicle’s active collision avoidance system for vulnerable road users, consider the limitations of on-board sensors, a pedestrian active collision avoidance control strategy based on vehicle-to-vehicle (V2V) communication technology is proposed for the blind-spot dangerous scenario where pedestrians pass through the front of a stationary obstacle vehicle and collide with the host vehicle. Firstly, the relative position relationship model between the host vehicle and the pedestrian is established according to the pedestrian information detected by the obstacle vehicle sensor and the global positioning system (GPS) position information of the obstacle vehicle and the host vehicle so that the host vehicle can obtain the state information of the pedestrian in front of the obstacle vehicle through V2V communication.

Abstract The airline industry faces a crisis in the future as consumer demand is increasing, but the environmental effects and depleting resources of kerosene mean that growth is unsustainable. Hydrogen is touted as the leading candidate to replace kerosene, but it needs significant technological and economical endeavors. In such a scenario, cryogenic liquid hydrogen (LH2) is predicted to be the most feasible method of using hydrogen. The major challenge of LH2 as an aircraft fuel is that it requires approximately four times the storage volume of kerosene—due to its lower density. Thus the design of cryogenic storage tanks to handle larger quantities of fuel is becoming increasingly important. But the increase in drag associated with larger storage tanks causes an increase in fuel consumption. Hence, this paper aims to evaluate the aerodynamic performance of different storage configurations and aid in the selection of an economic and efficient storage system.

Abstract Hybrid Electric Vehicles (HEVs) achieve better fuel economy than conventional vehicles by utilizing two different power sources: an internal combustion engine and an electrical motor. The power distribution between these two components must be controlled using some algorithm, be it rule based, optimization based, or reinforcement learning based. In the design of such control algorithms, it is important to evaluate the impact that variations of certain design parameters will have on the system performance, in this case, fuel economy. Traditional methods of sensitivity analysis have been applied to various power flow control algorithms to determine their robustness to the variations of HEV design parameters. This article presents a sensitivity analysis of three power flow control algorithms: twin delayed deep deterministic policy gradient (TD3), deep deterministic policy gradient (DDPG), and adaptive equivalent consumption minimization strategy (A-ECMS).

Abstract The RADIALcvt is a traction drive continuously variable transmission (CVT) implemented in a new novel radial configuration mechanical assembly. The RADIALcvt functions as a multi-parallel power path (at least six) type of CVT, which consists of only one steel-on-steel, line contact, traction drive interface in each power path. A constant input radius on the traction drive input makes it possible to use a constant clamping force, which is provided by mechanical springs, thus eliminating the need for a hydraulic control system. The RADIALcvt has a very large radius variation on the traction drive output, which provides the ratio variation. The test and simulation results of the first RADIALcvt prototype was published in [1] and presented mechanical efficiencies above 90%.