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Political and social trends in the automotive industry production and consumption have changed in the last decade, driving a demand for more efficient, low-fuel consuming, clean vehicles in most markets nowadays. Recently the demand for such vehicles has been increasing and emerging markets are no exception; automakers all around the world have invested heavily in developing new electrification technologies that would comply with the newer and stricter regulations and environmental policies, being Start-Stop systems one of the preferred approaches due to their lower complexity and cost compared to full and mild hybrids. Mexico stands out as a challenge for the implementation of this technology due to its wide range of altitudes, temperatures, traffic jams, and some other contributing factors that can hinder this type of application – especially in its bigger and more populated cities.

Starting January 2015 the government of the United Kingdom will allow driverless cars on public roads. From a first glance this can and should be seen as a great step towards the adoption of autonomous vehicles. Yet as any new technology driverless vehicles carry with them many new risks and disadvantages that need to be understood and protected against in order for the introduction of said systems into the market place to be a long lasting and fruitful one. The present work will look at the possible safety and security risks posed by the use of Light Detection and Ranging (LiDAR) systems on the open road, motivated by the fact that many projected autonomous vehicle concept systems rely on them for object detection and avoidance.

Upon their arrival, Unmanned Autonomous Systems (UAS) brought with them many benefits for those involved in a military campaign. They can use such systems to reconnoiter dangerous areas, provide 24-hr aerial security surveillance for force protection purposes or even attack enemy targets all the while avoiding friendly human losses in the process. Unfortunately, these platforms also carry the inherent risk of being built on innately vulnerable cybernetic systems. From software which can be tampered with to either steal data, damage or even outright steal the aircraft, to the data networks used for communications which can be jammed or even eavesdropped on to gain access to sensible information. All this has the potential to turn the benefits of UAS into liabilities and although the last decade has seen great advances in the development of protection and countermeasures against the described threats and beyond the risk still endures.

Energy management system designs for road vehicle applications have for some time considered the use of road data geospatial attributes such as elevation, speed limits and GPS derived online information, like traffic and position, to forecast the amount of fuel that could be consumed by a given vehicle on a specific route. This approach is especially useful when dealing with electrified platforms as on-board energy storage devices (such as fuel cells or batteries) have a lower energy density ratio [kJ/g]. Unfortunately within the tactical mobility context such information might not be readily available, either by passive obstructions, like mountains, or active ones due to jamming, etc. This paper will elaborate on an energy management system meant to deal with the uncertainty created by navigating in terrain where only basic trip information is available, such as probable distance to be travelled.

The incorporation of hydrogen fuel cells into heavy duty tactical mobility vehicles can bring about great opportunities in reducing the pollutant emissions of this kind of platforms (GVW > 30,000 kg). Furthermore the transportation of fuel to operational areas has become a key aspect for any deployment therefore optimal use of this resource is of paramount importance. Finally, it is also quite common for such platforms to serve additional purposes, besides freight delivery, such as powering external equipment (i.e. field hospitals or mobile artillery pieces). This work will describe the intelligent energy management system for a PEM Fuel Cell-Battery-Ultracapacitor Hybrid 8×8 heavy truck of the aforementioned weight class which also contemplates an internal electric/traction power generation unit. It will describe how the system optimizes the use of battery and hydrogen fuel energy while keeping system efficiency and performance at a maximum.