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This paper proposes a new integrated chassis control (ICC) using a predictive model-based control (MPC) for optimal allocation of sub-chassis control systems where a predictive model has 6 Degree of Freedom (DoF) for rigid body dynamics. The 6 DoF predictive vehicle model consists of longitudinal, lateral, vertical, roll, pitch, and yaw motions while previous MPC research uses a 3 DoF maximally predictive model such as longitudinal, lateral and yaw motions. The sub-chassis control systems in this paper include four wheel individual braking torque control, four wheel individual driving torque control and four corner active suspension control. Intermediate control inputs for sub-chassis control systems are simplified as wheel slip ratio changes for driving and braking controls and vertical suspension force changes for an active suspension control.

A variety of methodologies to use embedded multicore controllers efficiently has been discussed in the last years. Several assumptions are usually made in the automotive domain, such as static assignment of tasks to the cores. This paper shows an approach for efficient task allocation depending on different system modes. An engine management system (EMS) is used as application example, and the performance improvement compared to static allocation is assessed. The paper is structured as follows: First the control algorithms for the EMS will be classified according to operating modes. The classified algorithms will be allocated to the cores, depending on the operating mode. We identify mode transition points, allowing a reliable switch without neglecting timing requirements. As a next step, it will be shown that a load distribution by mode-dependent task allocation would be better balanced than a static task allocation.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.

Generally, the widely used hydraulic control system in automatic transmissions is pulse width modulation (PWM) type. It consists in a PWM solenoid valve and a reducing type second stage valve, so called pressure control valve (PCV), to amplify pressure or flow rate. In this study, the mathematical models of the PWM solenoid valve and the PCV with moderate complexity are proposed. Then, their behavior is analyzed from the steady state characteristics. Finally, we find that there are good matches between the dynamic simulation results and the experimental data.

A determination of the vehicle states and tire forces is critical to the stability of vehicle dynamic behavior and to designing automotive control systems. Researchers have studied estimation methods for the vehicle state vectors and tire forces. However, the accuracy of the estimation methods is closely related to the employed model. In this paper, tire lag dynamics is introduced in the model. Also application of estimation methods in order to improve the model accuracy is presented. The model is developed by using the global searching algorithm, a Genetic Algorithm, so that the model can be used in the nonlinear range. The extended Kalman filter and sliding mode observer theory are applied to estimate the vehicle state vectors and tire forces. The obtained results are compared with measurements and the outputs from the ADAMS full vehicle model. [15]

A Software-in-the-Loop (SIL) simulation is presented here wherein control algorithms for the Anti-lock Braking System (ABS) and Roll Stability Control (RSC) system were developed in Simulink. Vehicle dynamics models of a 6×4 cab-over tractor and two trailer combinations were developed in TruckSim and were used for control system design. Model validation was performed by doing various dynamic maneuvers like J-Turn, double lane change, decreasing radius curve, high dynamic steer input and constant radius test with increasing speed and comparing the vehicle responses obtained from TruckSim against field test data. A commercial ESC ECU contains two modules: Roll Stability Control (RSC) and Yaw Stability Control (YSC). In this research, only the RSC has been modeled. The ABS system was developed based on the results obtained from a HIL setup that was developed as a part of this research.

For the improvement of ride quality, development of vibration damping control systems and isolating methods become more important. To define basic ride vibrational modes, the effects of vehicle velocity and wheelbase on the standard road surfaces should be investigated. The different vibrational responses depending on the measurement positions of a vehicle body are presented with the bounce and the pitch motions. A methodology for the isolation of engine mount system's resonance to the road input and periodical excitations of tire/wheel nonuniformity forces are discussed. Using the computer simulation and the experimental results, a useful ride model with respect to the vehicle velocity and the stiffness of engine mount is presented.

The purpose of this report is to describe the process for the development of the automatically shifting manual transmission control system hardware and software to be used in the MTU Challenge X Equinox, a through-the-road parallel hybrid electric vehicle. The automatically shifting manual transmission was chosen for development, as it combines the ease of use of an automatic transmission with the fuel efficiency of a manual, while eliminating the parasitic losses in the torque converter and the transmission hydraulic pump. This report illustrates the process used to develop the software-in-the loop modeling that was developed for the initial proof of concept. In addition, it describes the development of the control strategy and hardware build for the prototype transmission. To begin the design process research was preformed on existing automatically shifting manuals and manual transmissions in general. From there vehicle subsystems were assembled using Simulink block diagrams.

The hardware and software for a prototype computer controlled cooling system for a diesel powered truck has been designed and tested. The basic requirements for this system have been defined and the control functions, previously investigated in a study using the computer simulation model, were incorporated into the software. Engine dynamometer tests on the MACK-676 engine, comparing the conventional cooling system and the computer controlled system, showed the following advantages of the computer controlled system: 1. The temperature level to which the engine warms up to at low ambient temperature, was increased. 2. The faster shutter response reduced the temperature peaks and decreased total fan activity time. 3. The faster fan response reduces fan engagement time which should improve truck fuel economy.

As electric vehicles become more widespread, such vehicles may be subject to “range anxiety” due to the risk of discharging during driving or the discharging when left unused for a long period. Accordingly, a vehicle equipped with a mobile charger that can provide a charge in an emergency. The vehicle with the mobile charger is usually composed of a large capacity battery, a power converter in a small truck. However, the large capacity battery and the power converter are disadvantageous in that they are large in size and expensive and should be produced as a special vehicle. In this paper, we propose a method to solve the problem using an internal EV system without requiring an additional power generation, battery and a charging-and-discharging device. The method is a novel Vehicle-to-Vehicle (V2V) fast charging control system utilizing motor and inverter in EV.

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques.

The electrical power system is the vital lifeline to most of the control systems on modern vehicles. The demands on the system are highly complex, and a detailed understanding of the system behavior is necessary both to the process of systems integration and to the economic design of a specific control system or actuator. The vehicle electric power system, which consists of two major components: a generator and a battery, has to provide numerous electrical and electronic systems with enough electrical energy. A detailed understanding of the characteristics of the electric power system, electrical load demands, and the driving environment such as road, season, and vehicle weight are required when the capacities of the generator and the battery are to be determined for a vehicle. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study.

This paper proposes a clutch control strategy during in-gear driving situations for Dual Clutch Transmissions (DCTs). The clutch is intentionally controlled to make small amount of a slip to identify the torque transfer capacity. The control objective of this phase is to ensure the clutch slip fairly remaining the specified value. To achieve this, the micro-slip controller is designed based on sliding mode control theory. Experimental verifications performed on onboard control system of the DCT equipped vehicle demonstrate that the proposed controller good tracking performance of the desired slip speed.

This paper proposes an effective nonlinear bicycle model including longitudinal, lateral, and yaw motions of a vehicle. This bicycle model uses a simplified piece-wise linear tire model and tire force tuning algorithm to produce closely matching vehicle trajectory compared to real vehicle for wide vehicle operation ranges. A simplified piece-wise tire model that well represents nonlinear tire forces was developed. The key parameters of this model can be chosen from measured tire forces. For the effects of dynamic load transfer due to sharp vehicle maneuvers, a tire force tuning algorithm that dynamically adjusts tire forces of the bicycle model based on measured vehicle lateral acceleration is proposed. Responses of the proposed bicycle model have been compared with commercial vehicle dynamics model (CarSim) through simulation in various vehicle maneuvers (ramp steer, sine-with-dwell).

This paper suggests disturbance observer which improves performance of speed limit assist control. The nonlinear disturbance observer was designed so that disturbance caused by parameter and load uncertainties is able to be estimated exponentially. With the contribution of the observer, feed-forward and integral controllers can be omitted while improving steady-state error elimination and overshoot reduction. The acceleration observer is also designed to reduce the effect of wheel slip and changing slope. The performance of the controllers has been verified not only on flat roads, but also on wave road and rapidly changing ramps.

Automotive exhaust noise is one of the major sources of noise pollution and it is controlled by passive control system (mufflers) and active control system (loudspeakers and active control algorithm). Mufflers are heavy, bulky and large in size while loudspeakers have a working temperature limitation. Carbon nanotube (CNT) speakers generate sound due to the thermoacoustic effect. CNT speakers are also lightweight, flexible, have acoustic and light transparency as well as high operating temperature. These properties make them ideal to overcome the limitations of the current exhaust noise control systems. An enclosed, coaxial CNT speaker is designed for exhaust noise cancellation application. The development of a 3D multi-physics (coupling of electrical, thermal and acoustical domains) model, for the coaxial speaker is discussed in this paper. The model is used to simulate the sound pressure level, input power versus ambient temperature and efficiency.