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Rollover has for long been a major safety concern for trucks, and will be even more so as automated driving is envisaged to becoming a key element of future mobility. A natural way to address rollover is to extend the capabilities of current active-safety systems with a system that intervenes by steering or braking actuation when there is a risk of rollover. Assessing and predicting the rollover is usually performed using rollover indices calculated either from lateral acceleration or lateral load transfer. Since these indices are evaluated based on different physical observations it is not obvious how they can be compared or how well they reflect rollover events in different situations. In this paper we investigate the implication of the above mentioned rollover indices in different critical maneuvers for a heavy 8×4 twin-steer truck.

In recent years the need for testing, calibration and certification of automotive components and powertrains have increased, partly due to the development of new hybrid concepts. At the same time, the development within electrical drives enables more versatile chassis dynamometer setups with better accuracy at a reduced cost. We are developing a new chassis dynamometer laboratory for vehicle research, aiming at extending a recently commercially available dynamometer, building a new laboratory around it, and applying the resulting facility to some new challenging vehicle research problems. The projects are enabled on one hand by collaboration with the dynamometer manufacturer, and on the other hand on collaboration with automotive industry allowing access to relevant internal information and equipment. The test modes of the chassis dynamometer are under development in a joint collaboration with the manufacturer.

Hybridization and velocity management are two important techniques for energy efficiency that mainly have been treated separately. Here they are put in a common framework that from the hybridization perspective can be seen as an extension of the equivalence factor idea in the well known strategy ECMS. From the perspective of look-ahead control, the extension is that energy can be stored not only in kinetic energy, but also electrically. The key idea is to introduce more equivalence factors in a way that enables efficient computations, but also so that the equivalence factors have a physical interpretation. The latter fact makes it easy to formulate a good residual cost to be used at the end of the look-ahead horizon. The formulation has different possible uses, but it is here applied on an evaluation of the size of the electrical system. Previous such studies, for e.g.

For a fuel optimal gear shift control, when look ahead information is available, the impact of the automated manual transmission (AMT) gear-shifting process is analyzed. For a standard discrete heavy truck transmission, answers are found on when to shift gears, prior to or when in an uphill slope. The gear-shifting process of a standard AMT is modeled in order to capture the fuel and time aspects of the gear shift. A numerical optimization is performed by dynamic programming, minimizing fuel consumption and time by controlling fuel injection and gear. Since a standard AMT does not have look ahead information, it sometimes gears down unnecessarily and thus gives a significantly higher fuel consumption compared to the optimal control. However, if gearing down is inevitable, the AMT gear-shifting strategy, based on engine thresholds, is well-functioning so that the optimal control only gives marginal additional savings.

In modern Diesel engines Exhaust Gas Recirculation (EGR) and Variable Geometry Turbochargers (VGT) have been introduced to meet the new emission requirements. A control structure that coordinates and handles emission limits and low fuel consumption has been developed. This controller has a set of PID controllers with parameters that need to be tuned. To be able to achieve good performance, an optimization based tuning method is developed and tested. In the optimization the control objectives are captured by a cost function. To aid the tuning a systematic method has been developed for selecting representative and significant transients that excite different modes in the controller. The performance is evaluated on the European Transient Cycle. It is demonstrated how weighting factors in the cost function influence control behavior, and that the proposed tuning method gives a significant improvement in control performance compared to standardized tuning methods for PID controllers.

The problem addressed is how to drive a heavy truck over various road topographies such that the fuel consumption is minimized. Using a realistic model of a truck powertrain, an optimization problem for minimization of fuel consumption is formulated. Through the solutions of this problem optimal speed profiles are found. An advantage here is that explicit analytical solutions can be found, and this is done for a few constructed test roads. The test roads are constructed to be easy enough to enable analytical solutions but still capture the important properties of real roads. In this way the obtained solutions provide explanations to some behaviour obtained by ourselves and others using more elaborate modeling and numeric optimization like dynamic programming. The results show that for level road and in small gradients the optimal solution is to drive with constant speed.

New and exciting possibilities in vehicle control are revealed by the consideration of topography, for example through the combination of GPS and three dimensional road maps. How information about future road slopes can be utilized in a heavy truck is explored. The aim is set at reducing the fuel consumption over a route without increasing the total travel time. A model predictive control (MPC) scheme is used to control the longitudinal behavior of the vehicle, which entails determining accelerator and brake levels and also which gear to engage. The optimization is accomplished through discrete dynamic programming. A cost function that weighs fuel use, negative deviations from the reference velocity, velocity changes, gear shifts and brake use is used to define the optimization criterion. Computer simulations back and forth on 127 km of a typical highway route in Sweden, show that the fuel consumption in a heavy truck can be reduced with 2.5% with a negligible change in travel time.

Inverse dynamic simulation is a successful method to make fast simulations of powertrains modeled using vehicle velocity and acceleration. This method is here extended so that additional dynamics can be included, and it is compared to the standard/usual forward dynamic simulation. Simulation results show that extended inverse dynamic simulation is a good method for maintaining speed and increasing accuracy in simulations. This gives the possibility to use the inverse dynamic simulation as a tool for powertrain optimization and control strategy evaluation.

Rolling resistance of inflated tires is a factor that contributes to the total load and fuel consumption of a vehicle. Therefore, models of rolling resistance is an important area within computer simulations of vehicles used to predict fuel consumption and emissions. In these applications the coefficient of rolling resistance is usually described as a function of velocity. We have earlier shown that this is not a satisfactory solution [1, 2]. In this paper it is demonstrated that the temperature of the tires is a dominating factor for rolling resistance in real driving. The tires typically start at ambient temperature and are then warmed up by the heat generated in the tire. As the temperature increases the rolling resistance decreases (to some limit). After a long period (2 hours for truck tires) of driving at constant conditions, a stationary temperature (and rolling resistance) is reached.

Spark ignited engines require accurate control of both air and fuel, and one important component in this system is the throttle servo. A non-linear throttle model is built and used for control design. It is shown that the non-linear model-based controller improves the performance compared to a conventional gain scheduled PI controller. Furthermore a method for estimating the load torque that the air flow produces on the throttle shaft is presented.

Due to increased legal and market demands, the weight of a conventional car body will most likely increase in the future. At the same time, environmental demands will become stronger and weight reduction will play an important part in fulfilling them. These demands are contradicting and there are mainly two things that can solve it: The use of new materials and further optimization of the structure. High strength steel is the easiest way to implement improved materials in an integrated body structure. Press hardened steel is one of the most promising manufacturing techniques and in this project a B-pillar reinforcement was developed as an example. For linear analyses, structural optimization methods have been used for quite a while, but for crash simulations, trial and error has been the only alternative. One part of the project was to evaluate how the response surface method could be applied to car crash simulations. The results of the project were very good.

One important area of SI-engine diagnosis is the diagnosis of leakage in the air-intake system. This is because a leakage can cause increased emissions and drivability problems. A method for accurately detecting leaks is presented. The results are developed for a turbo-charged engine but they are also valid for a naturally aspirated SI-engine. The method is based on a physical model of the leaks and includes an estimation of leakage area. By knowing the area, it is possible to reconfigure the control algorithm such that, the effect of the leak on emissions, is suppressed. As small leaks as 2 mm in diameter can be detected and it is possible to distinguish between leakages before or after the throttle. The method is suitable for on-line implementation.