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This paper presents a HiL test bench specifically designed for closed-loop testing of the monocular-vision based ADAS sensors, whereby the animated pictures of the virtual scene is calibrated and projected onto a 120-degree circular screen, such that the camera sensor installed has the same vision as the observation of the real-world scene. A high-fidelity AEBs model is established and deployed in the real-time target of the HiL system, making intervention decisions based on the instance-level detection information transmitted from the physical sensor. By referring to the 2018 edition of the C-NCAP testing protocol, the HiL tests of the rear-end collision scenarios is performed to investigate the performance and characteristics of the longitudinal-motion sensing of the sensor sample under test.

Taking full advantage of available traffic environment information, making control decisions, and then planning trajectory systematically under structured roads conditions is a critical part of intelligent vehicle. In this article, a lane-changing decision-making method for intelligent vehicle is proposed based on acceleration field. Firstly, an acceleration field related to relative velocity and relative distance was built based on the analysis of braking process, and acceleration was taken as an indicator of safety evaluation. Then, a lane-changing decision method was set up with acceleration field while considering driver’s habits, traffic efficiency and safety. Furthermore, velocity regulation was also introduced in the lane-changing decision method to make it more flexible.

The conventional radar modeling methods for automotive applications were either function-based or physics-based. The former approach was mainly abstracted as a solution of the intersection between geometric representations of radar beam and targets, while the latter one took radar detection mechanism into consideration by means of “ray tracing”. Although they each has its unique advantages, they were often unrealistic or time-consuming to meet actual simulation requirements. This paper presents a combined geometric and physical modeling method on millimeter-wave radar systems for Frequency Modulated Continuous Wave (FMCW) modulation format under a 3D simulation environment. With the geometric approach, a link between the virtual radar and 3D environment is established. With the physical approach, on the other hand, the ideal target detection and measurement are contaminated with noise and clutters aimed to produce the signals as close to the real ones as possible.

An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.

This paper investigates the use of an adaptive proportional-integral-derivative (APID) controller to reduce a combustion engine crankshaft speed pulsation. Both computer simulations and engine test rig experiments are used to validate the proposed control scheme. The starter/alternator (S/A) is used as the actuator for engine speed control. The S/A is an induction machine. It produces a supplemental torque source to cancel out the fast engine torque variation. This machine is placed on the engine crankshaft. The impact of the slowly varying changes in engine operating conditions is accounted for by adjusting the APID controller parameters on-line. The APID control scheme tunes the PID controller parameters by using the theory of adaptive interaction. The tuning algorithm determines a set of PID parameters by minimizing an error function. The error function is a weighted combination of the plant states and the required control effort.

The objective of the research into modeling and simulation was to provide an improvement to the Wayne State EcoCAR 2 team’s math-based modeling and simulation tools for hybrid electric vehicle powertrain analysis, with a goal of improving the simulation results to be less than 10% error to experimental data. The team used the modeling and simulation tools for evaluating different outcomes based on hybrid powertrain architecture changes (hardware), and controls code development and testing (software). The first step was model validation to experimental data, as the plant models had not yet been validated. This paper includes the results of the team’s work in the U.S. Department of Energy’s EcoCAR 2 Advanced vehicle Technical Competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions.

Numerical simulations on the fluid-structure interaction were conducted using commercial software STAR-CCM+ and ABAQUS. The aeroelastic responses of a deflector under several different working conditions were simulated utilizing finite volume and finite element methods to investigate the aeroelastic problem of automotive deflectors. Results showed that the structural response of a top deflector is minimal under the influence of aerodynamics given its large structural stiffness. The size of the top deflector was optimised by using thickness as a variable. The volume and quality of the top deflector were significantly reduced, and its lightweight performance was improved to satisfy the stiffness performance requirement. The vibration of a side deflector structure was mainly induced by the turbulence on the structure surface. The amplitude of vibration was small and the vibration gradually converged in a few seconds without obvious regularity.

The adoption of lithium-ion batteries in vehicle electrification is fast growing due to high power and energy demand on hybrid and electric vehicles. However, the battery overall performance changes with time through the vehicle life. This paper investigates the electric vehicle battery cell aging under different usages. Battery cell experimental data including open circuit voltage and internal resistance is utilized to build a typical electric vehicle model in the AVL-Cruise platform. Four driving cycles (WLTP, UDDS, HWFET, and US06) with different ambient temperatures are simulated to acquire the battery cell terminal currents. These battery cell terminal current data are inputs to the MATLAB/Simulink battery aging model. Simulation results show that battery degrades quickly in high ambient temperatures. After 15,000 hours usage in 50 degrees Celsius ambient temperature, the usable cell capacity is reduced up to 25%.

The Electronic Mechanical Braking (EMB) system, which offers advantages such as no liquid medium and complete decoupling, can meet the high-quality active braking and high-intensity regenerative braking demands proposed by intelligent vehicles and is considered one of the ideal platforms for future chassis. However, traditional control strategies with fixed clamping force tracking parameters struggle to maintain high-quality braking performance of EMB under variable braking requests, and the nonlinear friction between mechanical components also affects the accuracy of clamping force control. Therefore, this paper presents an adaptive clamping force control strategy for the EMB system, taking into account the resistance of nonlinear friction. First, an EMB model is established as the simulation and control object, which includes the motor model, transmission model, torque balance model, stiffness model, and friction model.

Automated parking is an efficient way to solve parking difficulties and path planning is of great concern for parking maneuvers [1]. Meanwhile, the starting region of path planning greatly affects the parking process and efficiency. The present research of the starting region are mostly determined based on a single algorithm, which limits the flexibility and efficiency of planning feasible paths. This paper, taking parallel parking and vertical parking for example, proposes a method to calculate the starting region and select the most suitable path planning algorithm for parking, which can improve the parking efficiency and reduce the complexity. The collision situations of each path planning algorithm are analyzed under collision-free conditions based on parallel and vertical parking. The starting region for each algorithm can then be calculated under collision-free conditions.

The guiding mechanism of vehicle suspension can keep the wheels moving along planned trajectory. The geometrical design of the reasonable suspension guide mechanism can reduce the vibration transmitted to the body, improve trafficability and handling stability. The vehicle suspension design method was applied to the wheel-legged vehicle, enhancing ride performance. The optimization of suspension hard points can be obtained by using single variable method, adjusting each hard point coordinate independently. It is also widely recommended by using intelligent algorithm to solve well-designed multi-objective parameter optimization function. In this study, the multi-objective parameter optimization function was solved by using the NSGA-II (Non-dominated Sorted Genetic Algorithm-II). Computer simulations with half-car model were used to support the analysis in this study. ADAMS multibody dynamics software was also used to verify the reliability of the results.

Experiments were conducted to investigate the characteristics of a common rail fuel injection system using a flow rate test rig and a single cylinder research diesel engine. Experiments covered speeds and loads typical to engine conditions under Hybrid Electric Vehicle operation. Different injection modes were investigated including main injection, main-post injection and pilot-main injection. The analysis indicated that the common rail fuel pressure affects all the injection parameters including the start of fuel delivery, its duration and amount under all modes of injection. Also, the pressure waves produced in the system have an impact on the operation of the nozzle-needle and fuel delivery particularly in the main-post injection mode.

The characteristics of the diesel engine unit injector were studied both theoretically and experimentally. The transient fuel pressure in the unit injector was indirectly measured by using strain gauges placed in different locations on the drive train, between the cam and plunger. The events which take place during the injection process were analyzed and the effects of several design and operating variables on the different injection parameters were determined. Computer simulation showed a fairly good agreement between computed and experimental results.

The installation of the Electronic Braking System (EBS) could effectively improve braking response speed, shorten braking distance, and ensure driving safety of commercial vehicles. However, during longitudinal deceleration control process, the commercial vehicles face not only challenges such as large inertia mass and random road gradient resistance of the vehicle layer, but also non-linear characteristics of the EBS actuator layer. In order to solve these problems, this paper proposes a commercial vehicle’s longitudinal deceleration precise control strategy considering vehicle-actuator dynamic characteristics. First, longitudinal dynamics of commercial vehicle is analyzed, and so is the EBS’ non-linear response hysteresis characteristics. Then, we design the dual layer deceleration control strategy. In vehicle layer, the recursive least squares with forgetting factor and Kalman filtering are comprehensively applied to dynamically estimate the vehicle mass and driving road slope.

This paper details the development of the control algorithms to characterize the behavior of an electrohydraulic actuated dry clutch used in the powertrain of the Wayne State University EcoCAR 3 Pre-Transmission Parallel hybrid vehicle. The paper describes the methodology and processes behind the development of the clutch physical model and electronic control unit to support the calibration of the vehicle’s hybrid supervisory controller. The EcoCAR 3 competition challenges sixteen North American universities to re-engineer the 2016 Chevrolet Camaro to reduce its environmental impact without compromising its performance and consumer acceptability. The team is in final stages of Year Two competition, which focuses on the powertrain components integration into the selected hybrid architecture. The dry clutch used by the team to enable the coupling between the engine and the electric motor is a key component of the Pre-Transmission Parallel configuration.

Hybrid Electric Vehicles with a power split system provide a variety of possibilities to promote the fuel economy of vehicles and better adapt to various driving conditions. In this paper, a new power split system of a hybrid electric bus which consists of double planetary gear sets and a clutch is introduced. The system is able to decouple both the torque and speed of the engine from the road load, which makes it possible for the engine to operate on its optimal operation line (OOL). Considering the features of the system configuration and bus driving cycle, the driving mode of the bus is divided into Electric Vehicle (EV) mode, Electric Variable Transmission (EVT) mode and Parallel mode. By controlling the engagement of the clutch at high vehicle speed (after the mechanical point), the system operates in the parallel mode rather than EVT mode. This avoids the problem that the system efficiency sharply declines in high speed region which EVT configurations are generally faced with.

This paper developed a control system for the auxiliary power unit (APU) in off-road series hybrid electric special vehicle. A control system configuration was designed according to the requirements of the high voltage system in series hybrid electric special vehicle. Then optimal engine operating areas were defined. A gain scheduling engine speed PI controller was designed based on these areas. A closed loop voltage regulator was designed for the synchronous generator. The proposed control system was first validated on an APU control test bench. The test results showed the control system guaranteed the diesel APU good dynamic response characteristics while remaining stable output voltage. Finally, the APU control system was implemented on a diesel APU in an off-road series hybrid electric vehicle and a road test was conducted. The road test results showed the APU control system promised good performance in both vehicle dynamics and vehicle high voltage system.

Controllability of ignition timing and combustion phase by means of dual-fuel direct injection strategy in jet-controlled compression ignition mode were investigated in a light-duty prototype diesel engine. Blended fuel with lower reactivity was delivered in the early period of compression stroke to form the premixed charge, while diesel fuel which has higher reactivity was injected near TDC to trigger the ignition. The effects of several important injection parameters including pre-injection timing, jet-injection timing, pre- injection pressure and ratio of pre-injection in the total heat value of injected fuel were discussed. Numerical Simulation by using CFD software was also conducted under similar operating conditions. The experimental results indicate that the jet-injection timing shows robust controllability on the start of combustion under all the engine load conditions.

In order to improve the mode switching performance of parallel hybrid electric vehicles (PHEV) and make better use of the dynamics of the vehicle, this paper proposes a three-stage control method for the start-up mode of start-up, speed synchronization, and clutch slip based on the response characteristics of actual vehicle components and the complex working conditions of the actual road. In the speed synchronization phase, a coordinated control method of “engine speed active following + continuously variable transmission (CVT) speed ratio motor speed limiting” is proposed. The real vehicle test results show that the engine starting-up coordinated control method can significantly accelerate the speed synchronization and shorten the starting-up mode duration during the rapid acceleration, so that the vehicle’s power performance can be well played and the ride comfort can be effectively guaranteed.

Semi-active suspension system (SASS) could enhance the ride comfort of the vehicle across different operating conditions through adjusting damping characteristics. However, current SASS are often calibrated based on engineering experience when selecting parameters for its controller, which complicates the achievement of optimal performance and leads to a decline in ride comfort for the vehicle being controlled. Linear quadratic constrained optimal control is a crucial tool for enhancing the performance of semi-active suspensions. It considers various performance objectives, such as ride comfort, handling stability, and driving safety. This study presents a control strategy for determining optimal damping force in SASS to enhance driving comfort. First, we analyze the working principle of the SASS and construct a seven-degree-of-freedom model.