Vehicle multi zone automatic Heating , Venting and Air Conditioning (HVAC) is the advanced form of the traditional air conditioning, the advantage of multi zone automatic HVAC is that it allows the passengers of a vehicle to set a desired temperature for their own zone within the vehicle compartment. This desired temperature is then maintained by the HVAC system, which determines how best to control the available environment data that leads to a higher comfort for the passengers. To achieve ultimate thermal comfort of the occupants in a vehicle, multi zone HVAC takes things a step further by adding heated, vented seats and, steering wheel to the HVAC controller hardware as well as strategies. The heating and cooling of the occupants by this more advance one integrated system is performed by complex control algorithms in form of embedded software programs and private LIN network. This paper describes the approach and tools used to develop, simulate and validate the one integrated climate control system. Included are 1- introduction of an integrated HVAC , steering wheel and…

Recently, car-sharing services using ultra-compact mobilities have been attracting attention as a means of transportation for one or two passengers in urban areas. A platooning system consisting of a manned leader vehicle and unmanned follower vehicles can reduce vehicle distributors. We have proposed a platooning system which controls vehicle motion based on the relative position and posture measured by non-contact coupling devices installed between vehicles. The feasibility of the coupling devices was validated through a HILS experiment. There are two basic requirements for realizing our platooning system; (1) all devices must remain coupled and (2) follower vehicles must be able to track the leader vehicle trajectory. Thus, this paper proposes two vehicle control method for satisfying those requirements. They are the “device coupling and trajectory tracking merging method” and the “trajectory shifting method”. The device coupling and trajectory tracking merging method consisting of a coupling keeping controller and a trajectory tracking controller. The predominant controller is chosen according to the amount of the coupling device error and the trajectory tracking error. The trajectory shifting method…

In order to reduce development cost and time, frontloading is an established methodology for automotive development programs. With this approach, particular development tasks are shifted to earlier program phases. One prerequisite for this approach is the application of Hardware-in-the-Loop test setups. Hardware-in-the-Loop methodologies have already successfully been applied to conventional as well as electrified powertrains considering various driving scenarios. Regarding driving performance and energy demand, electrified powertrains are highly dependent on the dc-link voltage. However, there is a particular shortage of studies focusing on the verification of variable dc-link voltage controls by Hardware-in-the-Loop setups. This article is intended to be a first step towards closing this gap. Thereto, a Hardware-in-the-Loop setup of a battery electric vehicle is developed. The electric powertrain consists of an interior permanent magnet synchronous machine and an inverter, which are set up as real components at a laboratory test bench. The test bench is connected to a real-time vehicle simulation including a battery model and the dc-dc converter model. The entire Hardware-in-the-Loop setup is successfully validated by vehicle measurements performed on…

Internal combustion engine (ICE) control techniques have been developed with only the first law of thermodynamics in mind, e.g. improving thermal efficiency, tracking specific load requirements, etc. The first law of thermodynamics does not account for the losses in work potential that are caused due to the in-cylinder high temperature thermodynamic processes irreversibilities. For instance, up to 25% of fuel exergy or fuel availability may be lost to irreversibilities during the combustion process. The second law of thermodynamics states that not all energy in an energy source is available to do work; its application evaluates the maximum available energy in that source after accounting for the losses caused by the irreversibilities. Therefore, including the exergy in an optimal engine control algorithm may lead to improved ICE thermal efficiencies. In this work, a model predictive controller (MPC) is developed based on the first and second laws of thermodynamics to control a detailed eight-cylinder ICE model developed in GT-Power. To make the controller practically applicable for eventual hardware in the loop (HiL) investigations, the GT-Power model is…

This paper presents an evaluation of two different Vehicle to Infrastructure (V2I) applications, namely Red Light Violation Warning (RLVW) and Green Light Optimized Speed Advisory (GLOSA). The evaluation method is to first develop and use Hardware-in-the-Loop (HIL) simulator testing, followed by extension of the HIL testing to road testing using an experimental connected vehicle. The HIL simulator used in the testing is a state-of-the-art simulator that consists of the same hardware like the road side unit and traffic cabinet as is used in real intersections and allows testing of numerous different traffic and intersection geometry and timing scenarios realistically. First, the RLVW V2I algorithm is tested in the HIL simulator and then implemented in an On-Board-Unit (OBU) in our experimental vehicle and tested at real world intersections. This same approach of HIL testing followed by testing in real intersections using our experimental vehicle is later extended to the GLOSA application. The GLOSA application that is tested in this paper has both an optimal speed advisory for passing at the green light and also includes a…

Automated driving functionalities delivered through Advanced Driver Assistance System (ADAS) have been adopted more and more frequently in consumer vehicles. The development and implementation of such functionalities pose new challenges in safety and functional testing and the associated validations, due primarily to their high demands on facility and infrastructure. This paper presents a rather unique Vehicle-in-the-Loop (VIL) test setup and methodology compared those previously reported, by combining the advantages of the hardware-in-the-loop (HIL) and traditional chassis dynamometer test cell in place of on-road testing, with a multi-agent real-time simulator for the rest of test environment. Details associated with applying the proposed VIL for testing adaptive cruise control (ACC), in conjunction with approaches for creating a virtual lead vehicle, as well as results of energy consumption analysis for a 2017 Toyota Prime with stock and improved longitudinal control algorithm, are reported to illustrate the effectiveness of low-infrastructure-demand test setup and the potential in applying the setup and methodology to other ADAS functionalities

Over the last decade, tremendous amount of research and progress has been made towards developing smart technologies for autonomous vehicles such as adaptive cruise control, lane keeping assist, lane following algorithms, and decision-making algorithms. One of the fundamental objectives for the development of such technologies is to enable autonomous vehicles with the capability to avoid obstacles and maintain safety. Automobiles are real-world dynamical systems - possessing inertia, operating at varying speeds, with finite accelerations/decelerations during operations. Deployment of autonomy in vehicles increases in complexity multi-fold especially when high DOF vehicle models need to be considered for robust control. Model Predictive Control (MPC) is a powerful tool that is used extensively to control the behavior of complex, dynamic systems. As a model-based approach, the fidelity of the model and selection of model-parameters plays a role in ultimate performance. Hardware-in-the-loop testing of such algorithms can often prove to be complex in its design as well as in its implementation. Therefore, in this paper, we explore a less-used deployment toolchain that combines the power of ROS (Robot Operating…

The requirements set for the next-generation powertrain systems (e.g. performance and emissions) are becoming increasingly stringent with ever-shortening time-to-markets at reduced costs. To remain competitive automotive companies are progressively relying on model-driven development and virtual testing. Virtual test benches, such as HiL (Hardware-in the-Loop) simulators, are powerful tools to reduce the amount of physical testing and speed up engine software calibration process. The introduction of these technologies places new, often conflicting demands (such as higher predictability, faster simulation speed, and reduced calibration effort) upon simulation models used at HiL test benches. The new models are also expected to offer compliance to industry standards, performance and usability to further increase the usage of virtual tests in powertrain development. This paper presents the methodology for creating and calibrating a computational model of a heavy-duty diesel engine suitable for HiL simulations. The novelty of the study is two-fold: it relies solely on engine dynamometer test data (does not use manufacturers’ inputs) and it employs a generic builder in GT-SUITE simulation software to create a baseline real-time model for…

Today’s transportation is quickly transforming with the nascent advent of connectivity, automation, shared-mobility, and electrification. These technologies will not only affect our safety and mobility, but also our energy consumption, and environment. As a result, it is of unprecedented importance to understand the overall system impacts due to the introduction of these emerging technologies and concepts. Existing modeling tools are not able to effectively capture the implications of these technologies, not to mention accurately and reliably evaluating their effectiveness with a reasonable scope. To address these gaps, a dynamometer-in-the-loop (DiL) development and testing approach is proposed which integrates test vehicle(s), chassis dynamometer, and high fidelity traffic simulation tools, in order to achieve a balance between the model accuracy and scalability of environmental analysis for the next generation of transportation systems. With this DiL platform, a connected eco-operation system for the plug-in hybrid electric bus (PHEB) has been developed and tested, which can optimize the vehicle dynamics (and potentially powertrain control via smart energy management) to reduce the operational energy consumption as well as tailpipe emissions…

This paper presents an energy-optimal deceleration planning system (EDPS) to maximize regenerative energy for electrified vehicles on deceleration events resulted from map information and connected communication. The optimization range for EDPS is restricted within an upcoming deceleration event rather than the entire routes while considering vehicles driving in front of ego-vehicle. The EDPS is an ecological driver assistance system with level 2 or 3 automation since acceleration is operated by an adaptive cruising system or a human driver and deceleration is operated on a unit of deceleration events which are divided into static ones such as turning and warning as well as dynamic ones such as traffic light. The event-based optimal deceleration profile is obtained by a dynamic programming framework including a driving motor performance model and a gear box model, and with the detection of a front vehicle the profile is updated in real time by nonlinear model predictive control scheme which considers a connected configuration and a modified intelligent driver model. The performance of EDPS has been rigorously validated both based on real-world…